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Bertilacchi MS, Vannucci G, Piccarducci R, Germelli L, Giacomelli C, Romei C, Bartholmai B, Barbieri G, Martini C, Baccini M. Serum Lactate Dehydrogenase Levels Reflect the Lung Injury Extension in COVID-19 Patients at Hospital Admission. Immun Inflamm Dis 2025; 13:e70168. [PMID: 40071734 PMCID: PMC11898011 DOI: 10.1002/iid3.70168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Revised: 01/24/2025] [Accepted: 02/27/2025] [Indexed: 03/15/2025] Open
Abstract
BACKGROUND Several hematological and biochemical parameters have been related to the COVID-19 infection severity and outcomes. However, less is known about clinical indicators reflecting lung involvement of COVID-19 patients at hospital admission. Computed tomography (CT) represents an established imaging tool for the detection of lung injury, and the quantitative analysis software CALIPER has been used to assess lung involvement in COVID-19 patients. Herein, the relationship between the lung involvement expressed by CALIPER interstitial lung disease (ILD) percentage and a set of blood parameters related to tissue oxygenation and damage in COVID-19 patients at hospital admission was evaluated. METHODS We performed a retrospective and a prospective study involving 321 and 75, respectively, COVID-19-positive patients recruited from Pisa University Hospital. The association between CALIPER ILD percentages and selected blood parameters was investigated by a regression tree approach, after multiple imputations of the dataset missing values. RESULTS High serum lactate dehydrogenase (LDH) values appeared to be predictive of high CALIPER ILD percentages at hospital admission in both retrospective and prospective datasets, even if the predictive performance of the algorithm was not optimal. CONCLUSIONS LDH levels could be evaluated as a tool for early identification of COVID-19 patients at risk of extensive lung injury, as well as in fast screening procedures before hospitalization.
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Affiliation(s)
| | - Giulia Vannucci
- Department of Electrical and Information Technology DIETIUniversity of Naples Federico IINapoliItaly
| | | | | | | | - Chiara Romei
- Department of RadiologyPisa University HospitalPisaItaly
| | - Brian Bartholmai
- Division of Radiology, Mayo Clinic RochesterRochesterMinnesotaUSA
| | - Greta Barbieri
- Department of Emergency Medicine DepartmentPisa University HospitalPisaItaly
| | | | - Michela Baccini
- Department of StatisticsComputer Science, ApplicationsUniversity of FlorenceFlorenceItaly
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Tan Z, Yu Y, Meng J, Liu S, Li W. Self-supervised learning with self-distillation on COVID-19 medical image classification. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107876. [PMID: 37875036 DOI: 10.1016/j.cmpb.2023.107876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 10/11/2023] [Accepted: 10/17/2023] [Indexed: 10/26/2023]
Abstract
BACKGROUND AND OBJECTIVE Currently, COVID-19 is a highly infectious disease that can be clinically diagnosed based on diagnostic radiology. Deep learning is capable of mining the rich information implied in inpatient imaging data and accomplishing the classification of different stages of the disease process. However, a large amount of training data is essential to train an excellent deep-learning model. Unfortunately, due to factors such as privacy and labeling difficulties, annotated data for COVID-19 is extremely scarce, which encourages us to propose a more effective deep learning model that can effectively assist specialist physicians in COVID-19 diagnosis. METHODS In this study,we introduce Masked Autoencoder (MAE) for pre-training and fine-tuning directly on small-scale target datasets. Based on this, we propose Self-Supervised Learning with Self-Distillation on COVID-19 medical image classification (SSSD-COVID). In addition to the reconstruction loss computation on the masked image patches, SSSD-COVID further performs self-distillation loss calculations on the latent representation of the encoder and decoder outputs. The additional loss calculation can transfer the knowledge from the global attention of the decoder to the encoder which acquires only local attention. RESULTS Our model achieves 97.78 % recognition accuracy on the SARS-COV-CT dataset containing 2481 images and is further validated on the COVID-CT dataset containing 746 images, which achieves 81.76 % recognition accuracy. Further introduction of external knowledge resulted in experimental accuracies of 99.6% and 95.27 % on these two datasets, respectively. CONCLUSIONS SSSD-COVID can obtain good results on the target dataset alone, and when external information is introduced, the performance of the model can be further improved to significantly outperform other models.Overall, the experimental results show that our method can effectively mine COVID-19 features from rare data and can assist professional physicians in decision-making to improve the efficiency of COVID-19 disease detection.
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Affiliation(s)
- Zhiyong Tan
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Yuhai Yu
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Jiana Meng
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China.
| | - Shuang Liu
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Wei Li
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
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Eizaguirre S, Sabater G, Belda S, Calderón JC, Pineda V, Comas-Cufí M, Bonnin M, Orriols R. Long-term respiratory consequences of COVID-19 related pneumonia: a cohort study. BMC Pulm Med 2023; 23:439. [PMID: 37951891 PMCID: PMC10638724 DOI: 10.1186/s12890-023-02627-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/31/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND Our aims were to describe respiratory sequelae up to 12 months after discharge in COVID-19 patients with severe pneumonia requiring non-invasive respiratory support therapies. METHODS This study was undertaken at University Hospital Doctor Josep Trueta (Girona, Spain) between March 2020 and June 2020. Three months after discharge, we evaluated their dyspnoea and performed Saint George's respiratory questionnaire, pulmonary function tests, blood test, 6-min walking test, and a high-resolution CT (HRCT). At the six and 12-month follow-up, we repeated all tests except for pulmonary function, 6-min walking test, and HRCT, which were performed only if abnormal findings had been previously detected. RESULTS Out of the 94 patients recruited, 73% were male, the median age was 62.9 years old, and most were non-smokers (58%). When comparing data three and 12 months after discharge, the percentage of patients presenting dyspnoea ≥ 2 decreased (19% vs 7%), the quality-of-life total score improved (22.8% vs 18.9%; p = 0.019), there were less abnormal results in the pulmonary function tests (47% vs 23%), the 6-min walking test distance was enhanced (368.3 m vs 390.7 m, p = 0.020), ground glass opacities findings waned (51.6% vs 11.5%), and traction bronchiectasis increased (5.6% vs 15.9%). Only age showed significant differences between patients with and without pulmonary fibrotic-like changes. CONCLUSION Most patients improved their clinical condition, pulmonary function, exercise capacity and quality of life one year after discharge. Nonetheless, pulmonary fibrotic-like changes were observed during the follow-ups.
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Affiliation(s)
- Saioa Eizaguirre
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
| | - Gladis Sabater
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
| | - Sònia Belda
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
| | - Juan Carlos Calderón
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
| | - Victor Pineda
- Department of Radiology, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
- Department of Medical Sciences, Faculty of Medicine, University of Girona, Girona, Catalonia, Spain
| | - Marc Comas-Cufí
- Department of Computer Science, Mathematics and Statistics, University of Girona, Girona, Catalonia, Spain
| | - Marc Bonnin
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain
| | - Ramon Orriols
- Department of Respiratory, Dr. Josep, Trueta University Hospital of Girona, and Santa Caterina Hospital of Salt, Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain.
- Department of Medical Sciences, Faculty of Medicine, University of Girona, Girona, Catalonia, Spain.
- Biomedical Research Networking Centre On Respiratory Diseases (CIBERES), Madrid, Spain.
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Hazem M, Ali SI, AlAlwan QM, Al Jabr IK, Alshehri SAF, AlAlwan MQ, Alsaeed MI, Aldawood M, Turkistani JA, Amin YA. Diagnostic Performance of the Radiological Society of North America Consensus Statement for Reporting COVID-19 Chest CT Findings: A Revisit. J Clin Med 2023; 12:5180. [PMID: 37629222 PMCID: PMC10455816 DOI: 10.3390/jcm12165180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 07/24/2023] [Accepted: 08/05/2023] [Indexed: 08/27/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) is a highly contagious respiratory disease that leads to variable degrees of illness, and which may be fatal. We evaluated the diagnostic performance of each chest computed tomography (CT) reporting category recommended by the Expert Consensus of the Radiological Society of North America (RSNA) in comparison with that of reverse transcription polymerase chain reaction (RT-PCR). We aimed to add an analysis of this form of reporting in the Middle East, as few studies have been performed there. Between July 2021 and February 2022, 184 patients with a mean age of 55.56 ± 16.71 years and probable COVID-19 infections were included in this retrospective study. Approximately 64.67% (119 patients) were male, while 35.33% (65 patients) were female. Within 7 days, all patients underwent CT and RT-PCR examinations. According to a statement by the RSNA, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of each CT reporting category were calculated, and the RT-PCR results were used as a standard reference. The RT-PCR results confirmed a final diagnosis of COVID-19 infection in 60.33% of the patients. For COVID-19 diagnoses, the typical category (n = 88) had a sensitivity, specificity, PPV, and accuracy of 74.8%, 93.2%, 94.3%, and 92.5%, respectively. For non-COVID-19 diagnoses, the PPVs for the atypical (n = 22) and negative (n = 46) categories were 81.8% and 89.1%, respectively. The PPV for the indeterminate (n = 28) category was 67.9%, with a low sensitivity of 17.1%. However, the RSNA's four chest CT reporting categories provide a strong diagnostic foundation and are highly correlated with the RT-PCR results for the typical, atypical, and negative categories, but they are weaker for the indeterminate category.
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Affiliation(s)
- Mohammed Hazem
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, Sohag University, Sohag 82524, Egypt;
| | - Sayed Ibrahim Ali
- Department of Family and Community Medicine, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (S.I.A.); (J.A.T.)
- Educational Psychology Department, College of Education, Helwan University, Cairo 11795, Egypt
| | - Qasem M. AlAlwan
- Department of Radiology, King Fahd Hospital Hofuf, Al-Ahsa 36441, Saudi Arabia; (Q.M.A.); (M.Q.A.)
| | - Ibrahim Khalid Al Jabr
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
| | - Sarah Abdulrahman F. Alshehri
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
| | - Mohammed Q. AlAlwan
- Department of Radiology, King Fahd Hospital Hofuf, Al-Ahsa 36441, Saudi Arabia; (Q.M.A.); (M.Q.A.)
| | | | - Mohammed Aldawood
- Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia;
| | - Jamela A. Turkistani
- Department of Family and Community Medicine, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (S.I.A.); (J.A.T.)
| | - Yasser Abdelkarim Amin
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, Sohag University, Sohag 82524, Egypt;
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Zeng LL, Gao K, Hu D, Feng Z, Hou C, Rong P, Wang W. SS-TBN: A Semi-Supervised Tri-Branch Network for COVID-19 Screening and Lesion Segmentation. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2023; 45:10427-10442. [PMID: 37022260 DOI: 10.1109/tpami.2023.3240886] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Insufficient annotated data and minor lung lesions pose big challenges for computed tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To address this issue, we propose a Semi-Supervised Tri-Branch Network (SS-TBN). First, we develop a joint TBN model for dual-task application scenarios of image segmentation and classification such as CT-based COVID-19 diagnosis, in which pixel-level lesion segmentation and slice-level infection classification branches are simultaneously trained via lesion attention, and individual-level diagnosis branch aggregates slice-level outputs for COVID-19 screening. Second, we propose a novel hybrid semi-supervised learning method to make full use of unlabeled data, combining a new double-threshold pseudo labeling method specifically designed to the joint model and a new inter-slice consistency regularization method specifically tailored to CT images. Besides two publicly available external datasets, we collect internal and our own external datasets including 210,395 images (1,420 cases versus 498 controls) from ten hospitals. Experimental results show that the proposed method achieves state-of-the-art performance in COVID-19 classification with limited annotated data even if lesions are subtle, and that segmentation results promote interpretability for diagnosis, suggesting the potential of the SS-TBN in early screening in insufficient labeled data situations at the early stage of a pandemic outbreak like COVID-19.
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Brogna B, Bignardi E, Megliola A, Laporta A, La Rocca A, Volpe M, Musto LA. A Pictorial Essay Describing the CT Imaging Features of COVID-19 Cases throughout the Pandemic with a Special Focus on Lung Manifestations and Extrapulmonary Vascular Abdominal Complications. Biomedicines 2023; 11:2113. [PMID: 37626610 PMCID: PMC10452395 DOI: 10.3390/biomedicines11082113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/27/2023] Open
Abstract
With the Omicron wave, SARS-CoV-2 infections improved, with less lung involvement and few cases of severe manifestations. In this pictorial review, there is a summary of the pathogenesis with particular focus on the interaction of the immune system and gut and lung axis in both pulmonary and extrapulmonary manifestations of COVID-19 and the computed tomography (CT) imaging features of COVID-19 pneumonia from the beginning of the pandemic, describing the typical features of COVID-19 pneumonia following the Delta variant and the atypical features appearing during the Omicron wave. There is also an outline of the typical features of COVID-19 pneumonia in cases of breakthrough infection, including secondary lung complications such as acute respiratory distress disease (ARDS), pneumomediastinum, pneumothorax, and lung pulmonary thromboembolism, which were more frequent during the first waves of the pandemic. Finally, there is a description of vascular extrapulmonary complications, including both ischemic and hemorrhagic abdominal complications.
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Affiliation(s)
- Barbara Brogna
- Department of Interventional and Emergency Radiology, San Giuseppe Moscati Hospital, 83100 Avellino, Italy; (A.L.); (A.L.R.); (L.A.M.)
| | - Elio Bignardi
- Department of Radiology, Francesco Ferrari Hospital, ASL Lecce, 73042 Casarano, Italy;
| | - Antonia Megliola
- Radiology Unit, “Frangipane” Hospital, ASL Avellino, 83031 Ariano Irpino, Italy; (A.M.); (M.V.)
| | - Antonietta Laporta
- Department of Interventional and Emergency Radiology, San Giuseppe Moscati Hospital, 83100 Avellino, Italy; (A.L.); (A.L.R.); (L.A.M.)
| | - Andrea La Rocca
- Department of Interventional and Emergency Radiology, San Giuseppe Moscati Hospital, 83100 Avellino, Italy; (A.L.); (A.L.R.); (L.A.M.)
| | - Mena Volpe
- Radiology Unit, “Frangipane” Hospital, ASL Avellino, 83031 Ariano Irpino, Italy; (A.M.); (M.V.)
| | - Lanfranco Aquilino Musto
- Department of Interventional and Emergency Radiology, San Giuseppe Moscati Hospital, 83100 Avellino, Italy; (A.L.); (A.L.R.); (L.A.M.)
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Doğan S, Güldiken GS, Alpaslan B, Barış SA, Doğan NÖ. Impact of COVID-19 pneumonia on interstitial lung disease: semi-quantitative evaluation with computed tomography. Eur Radiol 2023:10.1007/s00330-023-09441-2. [PMID: 36764951 PMCID: PMC9918400 DOI: 10.1007/s00330-023-09441-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 01/04/2023] [Accepted: 01/14/2023] [Indexed: 02/12/2023]
Abstract
OBJECTIVES To evaluate the CT scores and fibrotic pattern changes in interstitial lung disease (ILD) patients, with and without previous COVID-19 pneumonia. METHODS Patients with ILD (idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated ILD (CTD-ILD)) were retrospectively enrolled in the study which consisted of patients who had COVID-19 pneumonia while the control group had not. All patients had two CT scans, initial and follow-up, which were evaluated semi-quantitatively for severity, extent, and total CT scores, fibrosis patterns, and traction bronchiectasis. RESULTS A total of 102 patients (pneumonia group n = 48; control group n = 54) were enrolled in the study. For both groups, baseline characteristics were similar and CT scores were increased. While there was a 4.5 ± 4.6 point change in the total CT score of the COVID-19 group, there was a 1.2 ± 2.7 point change in the control group (p < 0.001). In the IPF subgroup, the change in total CT score was 7.0 points (95% CI: 4.1 to 9.9) in the COVID-19 group and 2.1 points (95% CI: 0.8 to 3.4) in the control group. Seven patients (14.6%) in the COVID-19 group progressed to a higher fibrosis pattern, but none in the control group. CONCLUSIONS Semi-quantitative chest CT scores in ILD patients demonstrated a significant increase after having COVID-19 pneumonia compared to ILD patients who had not had COVID-19 pneumonia. The increase in CT scores was more prominent in the IPF subgroup. There was also a worsening in the fibrosis pattern in the COVID-19 group. KEY POINTS • The impact of COVID-19 pneumonia on existing interstitial lung diseases and fibrosis is unclear. • COVID-19 pneumonia may worsen existing interstitial lung involvement with direct lung damage and indirect inflammatory effect. • COVID-19 pneumonia may affect existing lung fibrosis by triggering inflammatory pathways.
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Affiliation(s)
- Sevtap Doğan
- Department of Radiology, Faculty of Medicine, Kocaeli University, 41380, Kocaeli, Turkey.
| | - Gözde Selvi Güldiken
- grid.411105.00000 0001 0691 9040Department of Pulmonary Diseases, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey
| | - Burcu Alpaslan
- grid.411105.00000 0001 0691 9040Department of Radiology, Faculty of Medicine, Kocaeli University, 41380 Kocaeli, Turkey
| | - Serap Argun Barış
- grid.411105.00000 0001 0691 9040Department of Pulmonary Diseases, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey
| | - Nurettin Özgür Doğan
- grid.411105.00000 0001 0691 9040Department of Emergency Medicine, Faculty of Medicine, Kocaeli University, Kocaeli, Turkey
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Ficial B, Whebell S, Taylor D, Fernández-Garda R, Okiror L, Meadows CIS. Bronchoscopic Endobronchial Valve Therapy for Persistent Air Leaks in COVID-19 Patients Requiring Veno-Venous Extracorporeal Membrane Oxygenation. J Clin Med 2023; 12:jcm12041348. [PMID: 36835885 PMCID: PMC9962378 DOI: 10.3390/jcm12041348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/21/2023] [Accepted: 01/23/2023] [Indexed: 02/11/2023] Open
Abstract
COVID-19 acute respiratory distress syndrome (ARDS) can be associated with extensive lung damage, pneumothorax, pneumomediastinum and, in severe cases, persistent air leaks (PALs) via bronchopleural fistulae (BPF). PALs can impede weaning from invasive ventilation or extracorporeal membrane oxygenation (ECMO). We present a series of patients requiring veno-venous ECMO for COVID-19 ARDS who underwent endobronchial valve (EBV) management of PAL. This is a single-centre retrospective observational study. Data were collated from electronic health records. Patients treated with EBV met the following criteria: ECMO for COVID-19 ARDS; the presence of BPF causing PAL; air leak refractory to conventional management preventing ECMO and ventilator weaning. Between March 2020 and March 2022, 10 out of 152 patients requiring ECMO for COVID-19 developed refractory PALs, which were successfully treated with bronchoscopic EBV placement. The mean age was 38.3 years, 60% were male, and half had no prior co-morbidities. The average duration of air leaks prior to EBV deployment was 18 days. EBV placement resulted in the immediate cessation of air leaks in all patients with no peri-procedural complications. Weaning of ECMO, successful ventilator recruitment and removal of pleural drains were subsequently possible. A total of 80% of patients survived to hospital discharge and follow-up. Two patients died from multi-organ failure unrelated to EBV use. This case series presents the feasibility of EBV placement in severe parenchymal lung disease with PAL in patients requiring ECMO for COVID-19 ARDS and its potential to expedite weaning from both ECMO and mechanical ventilation, recovery from respiratory failure and ICU/hospital discharge.
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Affiliation(s)
- Barbara Ficial
- Department of Adult Critical Care, Guy’s and St Thomas’ NHS Foundation Trust, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Stephen Whebell
- Department of Adult Critical Care, Guy’s and St Thomas’ NHS Foundation Trust, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
- Intensive Care Unit, Townsville University Hospital, 100 Angus Smith Drive, Douglas, QLD 4814, Australia
| | - Daniel Taylor
- Department of Adult Critical Care, Guy’s and St Thomas’ NHS Foundation Trust, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Rita Fernández-Garda
- Department of Adult Critical Care, Guy’s and St Thomas’ NHS Foundation Trust, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Lawrence Okiror
- Department of Thoracic Surgery, Guy’s and St Thomas’ NHS Foundation Trust, Guy’s Hospital, Great Maze Pond, London SE1 9RT, UK
| | - Christopher I. S. Meadows
- Department of Adult Critical Care, Guy’s and St Thomas’ NHS Foundation Trust, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
- Correspondence:
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9
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Ying WF, Chen Q, Jiang ZK, Hao DG, Zhang Y, Han Q. Chest computed tomography findings of the Omicron variants of SARS-CoV-2 with different cycle threshold values. World J Clin Cases 2023; 11:756-763. [PMID: 36818628 PMCID: PMC9928689 DOI: 10.12998/wjcc.v11.i4.756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/29/2022] [Accepted: 01/12/2023] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mainly infects the upper respiratory tract. This study aimed to determine whether the probability of pulmonary infection and the cycle threshold (Ct) measured using the fluorescent polymerase chain reaction (PCR) method were related to pulmonary infections diagnosed via computed tomography (CT). AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values, as determined via PCR. METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2 Omicron variant infections were retrospectively collected and categorized into low (< 25), medium (25.00-34.99), and high (≥ 35) Ct groups. The characteristics of chest CT images in each group were statistically analyzed. RESULTS The PCR Ct values ranged from 13.36 to 39.81, with 99 patients in the low, 155 in the medium, and 77 in the high Ct groups. Six abnormal chest CT signs were detected, namely, focal infection, patchy consolidation shadows, patchy ground-glass shadows, mixed consolidation ground-glass shadows, subpleural interstitial changes, and pleural changes. Focal infections were less frequent in the low Ct group than in the medium and high Ct groups; these infections were the most common sign in the medium and high Ct groups. Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups. The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups. CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARS-CoV-2 varied depending on the Ct values. Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.
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Affiliation(s)
- Wei-Feng Ying
- Department of Radiology, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
| | - Qiong Chen
- Department of Radiology, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
| | - Zhi-Kui Jiang
- Department of Clinical Laboratory, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
| | - Da-Guang Hao
- Department of Radiology, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
| | - Ying Zhang
- Department of Radiology, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
| | - Qian Han
- Department of Clinical Laboratory, Shanghai Xuhui Dahua Hospital, Shanghai 200237, China
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Oliveira RKF, Nyasulu PS, Iqbal AA, Hamdan Gul M, Ferreira EVM, Leclair JW, Htun ZM, Howard LS, Mocumbi AO, Bryant AJ, Tamuzi JL, Avdeev S, Petrosillo N, Hassan A, Butrous G, de Jesus Perez V. Cardiopulmonary disease as sequelae of long-term COVID-19: Current perspectives and challenges. Front Med (Lausanne) 2022; 9:1041236. [PMID: 36530872 PMCID: PMC9748443 DOI: 10.3389/fmed.2022.1041236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 11/14/2022] [Indexed: 12/03/2022] Open
Abstract
COVID-19 infection primarily targets the lungs, which in severe cases progresses to cytokine storm, acute respiratory distress syndrome, multiorgan dysfunction, and shock. Survivors are now presenting evidence of cardiopulmonary sequelae such as persistent right ventricular dysfunction, chronic thrombosis, lung fibrosis, and pulmonary hypertension. This review will summarize the current knowledge on long-term cardiopulmonary sequelae of COVID-19 and provide a framework for approaching the diagnosis and management of these entities. We will also identify research priorities to address areas of uncertainty and improve the quality of care provided to these patients.
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Affiliation(s)
- Rudolf K. F. Oliveira
- Division of Respiratory Diseases, Department of Medicine, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Peter S. Nyasulu
- Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Adeel Ahmed Iqbal
- National Health System (NHS), Global Clinical Network, London, United Kingdom
| | - Muhammad Hamdan Gul
- Department of Internal Medicine, University of Kentucky, Lexington, KY, United States
| | - Eloara V. M. Ferreira
- Division of Respiratory Diseases, Department of Medicine, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | | | - Zin Mar Htun
- Division of Pulmonary and Critical Care, National Institute of Health, University of Maryland, College Park, College Park, MD, United States
| | - Luke S. Howard
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Ana O. Mocumbi
- Faculty of Medicine, Universidade Eduardo Mondlane, Maputo, Mozambique
- Non-communicable Diseases Division, Instituto Nacional de Saúde, Marracuene, Mozambique
| | - Andrew J. Bryant
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Jacques L. Tamuzi
- Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Sergey Avdeev
- Department of Pulmonology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Nicola Petrosillo
- Infection Prevention and Control-Infectious Disease Service, Foundation University Hospital Campus Bio-Medico, Rome, Italy
| | - Ahmed Hassan
- Department of Cardiology, Cairo University, Cairo, Egypt
| | - Ghazwan Butrous
- Medway School of Pharmacy, University of Kent at Canterbury, Canterbury, United Kingdom
| | - Vinicio de Jesus Perez
- Division of Pulmonary, Allergy and Critical Care Medicine, Stanford University Medical Center, Stanford, CA, United States
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11
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Zhong H, Zhou Y, Mei SY, Tang R, Feng JH, He ZY, Xu QY, Xing SP. Scars of COVID-19: A bibliometric analysis of post-COVID-19 fibrosis. Front Public Health 2022; 10:967829. [PMID: 36203683 PMCID: PMC9530282 DOI: 10.3389/fpubh.2022.967829] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/19/2022] [Indexed: 01/25/2023] Open
Abstract
Background The coronavirus disease 2019 (COVID-19) becomes a worldwide public health threat. Increasing evidence proves that COVID-19-induced acute injuries could be reversed by a couple of therapies. After that, post-COVID-19 fibrosis (PCF), a sequela of "Long COVID," earns rapidly emerging concerns. PCF is associated with deteriorative lung function and worse quality of life. But the process of PCF remains speculative. Therefore, we aim to conduct a bibliometric analysis to explore the overall structure, hotspots, and trend topics of PCF. Materials and methods A comprehensive search was performed in the Web of Science core database to collect literature on PCF. Search syntax included COVID-19 relevant terms: "COVID 19," "COVID-19 Virus Disease," "COVID-19 Virus Infection," "Coronavirus Disease-19," "2019 Novel Coronavirus Disease," "2019 Novel Coronavirus Infection," "SARS Coronavirus 2 Infection," "COVID-19 Pandemic," "Coronavirus," "2019-nCoV," and "SARS-CoV-2"; and fibrosis relevant terms: "Fibrosis," "Fibroses," and "Cirrhosis." Articles in English were included. Totally 1,088 publications were enrolled. Searching results were subsequentially exported and collected for the bibliometric analysis. National, organizational, and individual level data were analyzed and visualized through biblioshiny package in the R, VOSviewer software, the CiteSpace software, and the Graphical Clustering Toolkit (gCLUTO) software, respectively. Results The intrinsic structure and development in the field of PCF were investigated in the present bibliometric analysis. The topmost keywords were "COVID-19" (occurrences, 636) surrounded by "SARS-CoV-2" (occurrences, 242), "coronavirus" (occurrences, 123), "fibrosis" (occurrences, 120), and "pneumonia" (occurrences, 94). The epidemiology, physiopathology, diagnosis, and therapy of PCF were extensively studied. After this, based on dynamic analysis of keywords, hot topics sharply changed from "Wuhan," "inflammation," and "cytokine storm" to "quality of life" and "infection" through burst detection; from "acute respiratory syndrome," "cystic-fibrosis" and "fibrosis" to "infection," "COVID-19," "quality-of-life" through thematic evolution; from "enzyme" to "post COVID." Similarly, co-cited references analysis showed that topics of references with most citations shift from "pulmonary pathology" (cluster 0) to "COVID-19 vaccination" (cluster 6). Additionally, the overview of contributors, impact, and collaboration was revealed. Summarily, the USA stood out as the most prolific, influential, and collaborative country. The Udice French Research University, Imperial College London, Harvard University, and the University of Washington represented the largest volume of publications, citations, H-index, and co-authorships, respectively. Dana Albon was the most productive and cited author with the strongest co-authorship link strength. Journal of Cystic Fibrosis topped the list of prolific and influential journals. Conclusion Outcomes gained from this study assisted professionals in better realizing PCF and would guide future practices. Epidemiology, pathogenesis, and therapeutics were study hotspots in the early phase of PCF research. As the spread of the COVID-19 pandemic and progress in this field, recent attention shifted to the quality of life of patients and post-COVID comorbidities. Nevertheless, COVID-19 relevant infection and vaccination were speculated to be research trends with current and future interest. International cooperation as well as in-depth laboratory experiments were encouraged to promote further explorations in the field of PCF.
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Yegiazaryan A, Abnousian A, Alexander LJ, Badaoui A, Flaig B, Sheren N, Aghazarian A, Alsaigh D, Amin A, Mundra A, Nazaryan A, Guilford FT, Venketaraman V. Recent Developments in the Understanding of Immunity, Pathogenesis and Management of COVID-19. Int J Mol Sci 2022; 23:9297. [PMID: 36012562 PMCID: PMC9409103 DOI: 10.3390/ijms23169297] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 08/16/2022] [Accepted: 08/16/2022] [Indexed: 02/03/2023] Open
Abstract
Coronaviruses represent a diverse family of enveloped positive-sense single stranded RNA viruses. COVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus-2, is a highly contagious respiratory disease transmissible mainly via close contact and respiratory droplets which can result in severe, life-threatening respiratory pathologies. It is understood that glutathione, a naturally occurring antioxidant known for its role in immune response and cellular detoxification, is the target of various proinflammatory cytokines and transcription factors resulting in the infection, replication, and production of reactive oxygen species. This leads to more severe symptoms of COVID-19 and increased susceptibility to other illnesses such as tuberculosis. The emergence of vaccines against COVID-19, usage of monoclonal antibodies as treatments for infection, and implementation of pharmaceutical drugs have been effective methods for preventing and treating symptoms. However, with the mutating nature of the virus, other treatment modalities have been in research. With its role in antiviral defense and immune response, glutathione has been heavily explored in regard to COVID-19. Glutathione has demonstrated protective effects on inflammation and downregulation of reactive oxygen species, thereby resulting in less severe symptoms of COVID-19 infection and warranting the discussion of glutathione as a treatment mechanism.
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Affiliation(s)
- Aram Yegiazaryan
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Arbi Abnousian
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Logan J. Alexander
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Ali Badaoui
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Brandon Flaig
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Nisar Sheren
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Armin Aghazarian
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Dijla Alsaigh
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Arman Amin
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Akaash Mundra
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Anthony Nazaryan
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
| | | | - Vishwanath Venketaraman
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA
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13
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Bonnefoy PB, Bahloul A, Denizot B, Barres B, Moreau-Triby C, Girma A, Pallardy A, Ceyra Q, Sarda-Mantel L, Razzouk-Cadet M, Zsigmond R, Cachin F, Karcher G, Salaun PY, Le Roux PY. Functional Alterations Due to COVID-19 Lung Lesions-Lessons From a Multicenter V/Q Scan-Based Registry. Clin Nucl Med 2022; 47:e540-e547. [PMID: 35605049 PMCID: PMC9275799 DOI: 10.1097/rlu.0000000000004261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/06/2022] [Indexed: 01/08/2023]
Abstract
PURPOSE In coronavirus disease 2019 (COVID-19) patients, clinical manifestations as well as chest CT lesions are variable. Lung scintigraphy allows to assess and compare the regional distribution of ventilation and perfusion throughout the lungs. Our main objective was to describe ventilation and perfusion injury by type of chest CT lesions of COVID-19 infection using V/Q SPECT/CT imaging. PATIENTS AND METHODS We explored a national registry including V/Q SPECT/CT performed during a proven acute SARS-CoV-2 infection. Chest CT findings of COVID-19 disease were classified in 3 elementary lesions: ground-glass opacities, crazy-paving (CP), and consolidation. For each type of chest CT lesions, a semiquantitative evaluation of ventilation and perfusion was visually performed using a 5-point scale score (0 = normal to 4 = absent function). RESULTS V/Q SPECT/CT was performed in 145 patients recruited in 9 nuclear medicine departments. Parenchymal lesions were visible in 126 patients (86.9%). Ground-glass opacities were visible in 33 patients (22.8%) and were responsible for minimal perfusion impairment (perfusion score [mean ± SD], 0.9 ± 0.6) and moderate ventilation impairment (ventilation score, 1.7 ± 1); CP was visible in 43 patients (29.7%) and caused moderate perfusion impairment (2.1 ± 1.1) and moderate-to-severe ventilation impairment (2.5 ± 1.1); consolidation was visible in 89 patients (61.4%) and was associated with moderate perfusion impairment (2.1 ± 1) and severe ventilation impairment (3.0 ± 0.9). CONCLUSIONS In COVID-19 patients assessed with V/Q SPECT/CT, a large proportion demonstrated parenchymal lung lesions on CT, responsible for ventilation and perfusion injury. COVID-19-related pulmonary lesions were, in order of frequency and functional impairment, consolidations, CP, and ground-glass opacity, with typically a reverse mismatched or matched pattern.
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Affiliation(s)
| | | | - Benoit Denizot
- Service de Médecine Nucléaire, Centre Hospitalier Alpes Léman, Contamine-sur-Arve
| | - Bertrand Barres
- Service de Médecine Nucléaire, Centre Jean Perrin, Clermont-Ferrand
| | | | - Astrid Girma
- Service de Médecine Nucléaire, Hôpital Foch, Suresnes
| | | | | | | | | | | | - Florent Cachin
- Service de Médecine Nucléaire, Centre Jean Perrin, Clermont-Ferrand
| | | | - Pierre-Yves Salaun
- Service de Médecine Nucléaire, Université Européenne de Bretagne, Université de Brest, EA3878 (GETBO) IFR 148, CHRU de Brest, Brest, France
| | - Pierre-Yves Le Roux
- Service de Médecine Nucléaire, Université Européenne de Bretagne, Université de Brest, EA3878 (GETBO) IFR 148, CHRU de Brest, Brest, France
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14
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Kaya AT, Akman B. Mediastinal lymph node enlargement in COVID-19: Relationships with mortality and CT findings. Heart Lung 2022; 54:19-26. [PMID: 35306375 PMCID: PMC8907027 DOI: 10.1016/j.hrtlng.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND The presence of mediastinal lymph node enlargement (MLNE) in computed tomography (CT) of Coronavirus disease 2019 (COVID-19) patients can be associated with disease severity. OBJECTIVES To investigate the relationship between MLNE with intensive care unit admission (ICU), mortality rates, and CT findings, especially in early-stage COVID-19 patients. METHODS This single-center retrospective case-control study, included aged ≥18 years, 250 COVID-19 patients with positive RT-PCR tests. We included two patient groups, 125/250 with and without MLNE. Demographic information of the patients, laboratory findings, length of stay in hospital or ICU, mortality rates, initial CT imaging findings and CT severity scores (CT-SS) were recorded and their relationship with MLNE was investigated. RESULTS Patients with MLNE were older (69.61 ± 11.16; p < 0.001) and had a higher CT-SS (14.67 ± 7.55; p < 0.001). There was a significant difference between the presence of MLNE with mortality (58/77, 75.3%; p < 0.001) and ICU admission (49/61, 80.3%; p < 0.001). Also, a statistical association was found between MLNE with ICU admission (p = 0.001) and (p < 0.001) mortality rates in patients with CORADS≤2 CT findings. In multivariate logistic regression analysis, MLNE was 8.8-fold (95% CI: 1.62-47.86, p = 0.01) more correlated with linear opacity and 0.25-fold with bronchial wall thickening (95% CI: 0.07-0.92, p = 0.04). CONCLUSION Mediastinal lymph node enlargement is an important CT finding that can predict the severe prognosis of COVID-19 patients. Even in patients without lung involvement on initial CT, the presence of MLNE should be carefully examined as it is associated with disease severity.
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Affiliation(s)
- Ahmet Turan Kaya
- Department of Radiology, Faculty of Medicine, Amasya University, Sabuncuoğlu Şerefeddin Research and Education Hospital, Amasya, Turkey.
| | - Burcu Akman
- Department of Radiology, Faculty of Medicine, Amasya University, Sabuncuoğlu Şerefeddin Research and Education Hospital, Amasya, Turkey
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15
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Meng J, Tan Z, Yu Y, Wang P, Liu S. TL-med: A Two-stage transfer learning recognition model for medical images of COVID-19. Biocybern Biomed Eng 2022; 42:842-855. [PMID: 35506115 PMCID: PMC9051950 DOI: 10.1016/j.bbe.2022.04.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 04/16/2022] [Accepted: 04/20/2022] [Indexed: 12/16/2022]
Abstract
The recognition of medical images with deep learning techniques can assist physicians in clinical diagnosis, but the effectiveness of recognition models relies on massive amounts of labeled data. With the rampant development of the novel coronavirus (COVID-19) worldwide, rapid COVID-19 diagnosis has become an effective measure to combat the outbreak. However, labeled COVID-19 data are scarce. Therefore, we propose a two-stage transfer learning recognition model for medical images of COVID-19 (TL-Med) based on the concept of "generic domain-target-related domain-target domain". First, we use the Vision Transformer (ViT) pretraining model to obtain generic features from massive heterogeneous data and then learn medical features from large-scale homogeneous data. Two-stage transfer learning uses the learned primary features and the underlying information for COVID-19 image recognition to solve the problem by which data insufficiency leads to the inability of the model to learn underlying target dataset information. The experimental results obtained on a COVID-19 dataset using the TL-Med model produce a recognition accuracy of 93.24%, which shows that the proposed method is more effective in detecting COVID-19 images than other approaches and may greatly alleviate the problem of data scarcity in this field.
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Affiliation(s)
- Jiana Meng
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Zhiyong Tan
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Yuhai Yu
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Pengjie Wang
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
| | - Shuang Liu
- School of Computer Science and Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
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16
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Baghdadi NA, Malki A, Abdelaliem SF, Magdy Balaha H, Badawy M, Elhosseini M. An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network. Comput Biol Med 2022; 144:105383. [PMID: 35290811 PMCID: PMC8906898 DOI: 10.1016/j.compbiomed.2022.105383] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 02/15/2022] [Accepted: 03/02/2022] [Indexed: 02/06/2023]
Abstract
Researchers have developed more intelligent, highly responsive, and efficient detection methods owing to the COVID-19 demands for more widespread diagnosis. The work done deals with developing an AI-based framework that can help radiologists and other healthcare professionals diagnose COVID-19 cases at a high level of accuracy. However, in the absence of publicly available CT datasets, the development of such AI tools can prove challenging. Therefore, an algorithm for performing automatic and accurate COVID-19 classification using Convolutional Neural Network (CNN), pre-trained model, and Sparrow search algorithm (SSA) on CT lung images was proposed. The pre-trained CNN models used are SeresNext50, SeresNext101, SeNet154, MobileNet, MobileNetV2, MobileNetV3Small, and MobileNetV3Large. In addition, the SSA will be used to optimize the different CNN and transfer learning(TL) hyperparameters to find the best configuration for the pre-trained model used and enhance its performance. Two datasets are used in the experiments. There are two classes in the first dataset, while three in the second. The authors combined two publicly available COVID-19 datasets as the first dataset, namely the COVID-19 Lung CT Scans and COVID-19 CT Scan Dataset. In total, 14,486 images were included in this study. The authors analyzed the Large COVID-19 CT scan slice dataset in the second dataset, which utilized 17,104 images. Compared to other pre-trained models on both classes datasets, MobileNetV3Large pre-trained is the best model. As far as the three-classes dataset is concerned, a model trained on SeNet154 is the best available. Results show that, when compared to other CNN models like LeNet-5 CNN, COVID faster R–CNN, Light CNN, Fuzzy + CNN, Dynamic CNN, CNN and Optimized CNN, the proposed Framework achieves the best accuracy of 99.74% (two classes) and 98% (three classes).
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Affiliation(s)
- Nadiah A Baghdadi
- Princess Nourah bint Abdulrahman University, College of Nursing, Riyadh, 11671, Riyadh, P.O. BOX 84428, Saudi Arabia.
| | - Amer Malki
- Taibah University, College of Computer Science and Engineering, Yanbu, 46421, Saudi Arabia
| | - Sally F Abdelaliem
- Princess Nourah bint Abdulrahman University, College of Nursing, Riyadh, 11671, Riyadh, P.O. BOX 84428, Saudi Arabia
| | - Hossam Magdy Balaha
- Mansoura University, Faculty of Engineering, Computers and Control Systems Engineering Department, Mansoura, 46421, Egypt
| | - Mahmoud Badawy
- Mansoura University, Faculty of Engineering, Computers and Control Systems Engineering Department, Mansoura, 46421, Egypt.
| | - Mostafa Elhosseini
- Taibah University, College of Computer Science and Engineering, Yanbu, 46421, Saudi Arabia; Mansoura University, Faculty of Engineering, Computers and Control Systems Engineering Department, Mansoura, 46421, Egypt
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Fogante M, Cavagna E, Rinaldi G. COVID-19 follow-up: Chest X-ray findings with clinical and radiological relationship three months after recovery. Radiography (Lond) 2022; 28:531-536. [PMID: 34728138 PMCID: PMC8531194 DOI: 10.1016/j.radi.2021.10.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 11/20/2022]
Abstract
INTRODUCTION To evaluate the radiological sequelae of coronavirus disease (COVID-19) in a mid-term follow-up and investigate their relationship with clinical-radiological findings. METHODS This prospective study included COVID-19 patients who underwent a CXR three months after discharge. The relationship between CXR score at three months after discharge and clinical findings and previous CXR scores, at admission and before the discharge, were evaluated. Then, based on mid-term follow-up CXR score, patients were divided in Group A (score = 0) and Group B (score≥1), and clinical-radiological findings were compared between two Groups. Finally, we calculated the CXR scores at admission and before the discharge with the highest sensitivity and specificity to predict normal and abnormal CXR score at mid-term follow-up. RESULTS The study included 119 patients, mean age 65.9 ± 14.6 years. The oxygen saturation (SaO2) (p = 0.0006), the days of hospitalization (p < 0.0001) and the CXR score before the discharge (p = 0.0091) were independent factors to predict the mid-term follow-up CXR score. The Group A, 59 (49.6%) patients, had CXR scores at admission and before the discharge lower than Group B. The CXR scores at admission and before the discharge with the highest sensitivity and specificity to predict normal and abnormal CXR score at mid-term follow-up were, respectively, 3 and 2 (p < 0.0001). CONCLUSIONS The radiological abnormalities were present in about half patients three months after discharge, which had higher age, previous CXR scores and longer hospitalization. The SO2, days of hospitalization and previous CXR scores were independent factors for predicting the CXR at three months. IMPLICATIONS FOR PRACTICE The radiologist with CXR could play a central role in mid to long-term follow-up of COVID-19, assessing the radiological sequelae of patients and identifying those who might require a closer follow-up.
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Affiliation(s)
- M Fogante
- Azienda Ospedaliera "Ospedali Riuniti", Ancona, Italy.
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18
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Eroglu SE, Ademoglu E, Baslilar S, Aksel G, Eker A, Algın A, Islam MM, Ozdemir S. Can 1st and 6th month pulmonary function test follow-ups give an idea about the long-term respiratory effects of COVID-19 pneumonia? REVISTA DA ASSOCIACAO MEDICA BRASILEIRA (1992) 2022; 68:183-190. [PMID: 35239879 DOI: 10.1590/1806-9282.20210890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 11/02/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE The aim of this study was to ascertain the long-term respiratory effects of COVID-19 pneumonia through pulmonary function tests in follow-ups at 1 and 6 months. METHODS Our study was conducted between August 1, 2020 and April 30, 2021. At 1 month after discharge, follow-up evaluations, PFTs, and lung imaging were performed on patients aged above 18 years who had been diagnosed with COVID-19 pneumonia. In the 6th month, the PFTs were repeated for those with pulmonary dysfunction. RESULTS A total of 219 patients (mean age, 49±11.9 years) were included. Pathological PFT results were noted in the 1st month for 80 patients and in the 6th month for 46 (7 had obstructive disorder, 15 had restrictive disorder, and 28 had small airway obstruction) patients. A significant difference was found between abnormal PFT results and patient-described dyspnea in the 1st month of follow-up. The 6-month PFT values (especially those for forced vital capacity) were statistically significantly lower in the patients for whom imaging did not indicate complete radiological improvement at the 1-month follow-up. No statistically significant difference was found between the severity of the first computed tomography findings or clinical condition on emergency admission and pulmonary dysfunction (Pearson's chi-square test, P=0.904; Fisher's exact test, P=0.727). CONCLUSION It is important that patients with COVID-19 pneumonia be followed up for at least 1 month after discharge to be monitored for potential long-term lung damage. PFTs should be administered to those in whom ongoing dyspnea, which started with COVID-19, and/or full recovery were not identified in pulmonary imaging.
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Affiliation(s)
- Serkan Emre Eroglu
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Enis Ademoglu
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Seyma Baslilar
- University of Health Sciences Umraniye Training and Research Hospital, Department of Pulmonary Medicine - Istanbul, Turkey
| | - Gokhan Aksel
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Aysen Eker
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Abdullah Algın
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Mehmet Muzaffer Islam
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
| | - Serdar Ozdemir
- University of Health Sciences Umraniye Training and Research Hospital, Department of Emergency Medicine - Istanbul, Turkey
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19
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Savastano MC, Larici AR, Crincoli E, De Filippis A, Cicchetti G, Gambini G, Savastano A, Marano R, Natale L, Rizzo S. Retinal vascular impairment matched to the pulmonary damage in early post-COVID 19 patients. Eur J Ophthalmol 2022; 32:3574-3583. [PMID: 35174719 DOI: 10.1177/11206721221079153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Endothelium damage is a crucial element in the pathogenesis of SARS-Cov-2 infection. Most casualties in critical COVID-19 cases are due to ARDS, diffuse coagulopathy and cytokine storm. ARDS itself is a consequence of pulmonary endothelial cells damage. Damage to retinal capillary microcirculation in post-infective period has been investigated through Optical Coherence Tomography Angiography (OCTA). The aim of the present study is to find a correlation between signs of retinal vascular damage and pulmonary impairment. METHODS Patients admitted to hospital and subsequently recovered from COVID-19 infection were summoned 1 month later to undergo coherence tomography (CT) scan and OCTA examination. RESULTS The study population included 87 COVID-19 patients with a mean age of 54.28 ± 14.44 years. Oxygen therapy, non-invasive and invasive mechanical ventilation were necessary in 33, 11 and 4 patients respectively to provide respiratory support during the acute course of the disease. Pulmonary involvement interested 54 patients (62.1%). Peripheral (27.6%) or diffuse (29.9%) involvement and ground glass (GG) opacities (47.1%) represented the prevalent radiological finding. A reduced RCPI FI was independently correlated with the presence of reticulation pattern in CT scan (p = .019). Also, RNFL and GCC were thinner in patients who displayed reticulation pattern (respectively p = .025 and p = .015). CONCLUSIONS A reduction in RPCP-FI and RNFL and GCC thickness were independently correlated to the presence of CT reticulation pattern. This association can reflect cytokine induced remodeling in both organs as a consequence of systemic endothelial damage and inflammation.
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Affiliation(s)
- Maria Cristina Savastano
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù
| | - Anna Rita Larici
- 60234Catholic University of "Sacro Cuore", Rome, Italyù.,Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.,Department of Radiological and Hematological Sciences, Section of Radiology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Emanuele Crincoli
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù
| | - Alessandro De Filippis
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù
| | - Giuseppe Cicchetti
- Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.,Department of Radiological and Hematological Sciences, Section of Radiology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Gloria Gambini
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù
| | - Alfonso Savastano
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù
| | - Riccardo Marano
- Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.,Department of Radiological and Hematological Sciences, Section of Radiology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Luigi Natale
- Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.,Department of Radiological and Hematological Sciences, Section of Radiology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Stanislao Rizzo
- Ophthalmology Unit, 18654"Fondazione Policlinico Universitario A. Gemelli IRCCS", Rome, Italy.,60234Catholic University of "Sacro Cuore", Rome, Italyù.,"Consiglio Nazionale delle Ricerche, Istituto di Neuroscienze", Pisa, Italy
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20
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Diagnostic performance of thorax CT in mildly symptomatic COVID-19 patients: The importance of atypical CT findings. North Clin Istanb 2021; 8:425-434. [PMID: 34909580 PMCID: PMC8630726 DOI: 10.14744/nci.2021.81557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 01/23/2021] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE: Computed tomography of the thorax (Thorax CT) is frequently used to diagnose viral pneumonia in moderate to severe COVID-19 patients, but its diagnostic performance in mildly symptomatic COVID-19 patients is still unclear. Assessing the diagnostic performance of thorax CT in mildly symptomatic COVID-19 patients was the purpose of our study. METHODS: Mildly symptomatic and clinically stable, suspected COVID-19 patients scanned with Thorax CTs between March 11, 2020, and April 13, 2020, were included in this study. The sensitivity, specificity, positive and negative likelihood ratios, positive and negative predictive values, and the respective accuracies were calculated for diagnostic purposes. RESULTS: Among the 1119 patients enrolled in our study, abnormal thorax CT scans were 527 out of which 363/527 (68.9%) had typical CT features for COVID-19. According to analysis of typical COVID findings, sensitivity, specificity, positive predictive values, negative predictive value, and the accuracy of Thorax CTs with were 51.45%, 86.07%, 78.24%, 64.55%, and 68.99%, respectively. When typical CT findings and atypical CT findings were combined for the statistical analysis, the sensitivity, specificity, and accuracy observed 68.84%, 74%, and 71.49%. CONCLUSION: Diagnosing pneumonia can be challenging in mildly symptomatic COVID-19 patients since the Reverse Transcription Polymerase Chain Reaction test results, when compared with symptoms are not always evident. According to our study, thorax CT sensitivity was higher when atypical COVID-19 CT findings were included compared to those with typical COVID-19 CT findings alone. Our study which included the largest number of patients among all other similar studies indicates that not only typical but also atypical CT findings should be considered for an accured diagnosis of COVID-19 pneumonia.
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21
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Dey A, Chattopadhyay S, Singh PK, Ahmadian A, Ferrara M, Senu N, Sarkar R. MRFGRO: a hybrid meta-heuristic feature selection method for screening COVID-19 using deep features. Sci Rep 2021; 11:24065. [PMID: 34911977 PMCID: PMC8674247 DOI: 10.1038/s41598-021-02731-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 11/17/2021] [Indexed: 12/24/2022] Open
Abstract
COVID-19 is a respiratory disease that causes infection in both lungs and the upper respiratory tract. The World Health Organization (WHO) has declared it a global pandemic because of its rapid spread across the globe. The most common way for COVID-19 diagnosis is real-time reverse transcription-polymerase chain reaction (RT-PCR) which takes a significant amount of time to get the result. Computer based medical image analysis is more beneficial for the diagnosis of such disease as it can give better results in less time. Computed Tomography (CT) scans are used to monitor lung diseases including COVID-19. In this work, a hybrid model for COVID-19 detection has developed which has two key stages. In the first stage, we have fine-tuned the parameters of the pre-trained convolutional neural networks (CNNs) to extract some features from the COVID-19 affected lungs. As pre-trained CNNs, we have used two standard CNNs namely, GoogleNet and ResNet18. Then, we have proposed a hybrid meta-heuristic feature selection (FS) algorithm, named as Manta Ray Foraging based Golden Ratio Optimizer (MRFGRO) to select the most significant feature subset. The proposed model is implemented over three publicly available datasets, namely, COVID-CT dataset, SARS-COV-2 dataset, and MOSMED dataset, and attains state-of-the-art classification accuracies of 99.15%, 99.42% and 95.57% respectively. Obtained results confirm that the proposed approach is quite efficient when compared to the local texture descriptors used for COVID-19 detection from chest CT-scan images.
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Affiliation(s)
- Arijit Dey
- Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, 700064, India
| | - Soham Chattopadhyay
- Department of Electrical Engineering, Jadavpur University, 188, Raja S. C. Mallick Road, Kolkata, West Bengal, 700032, India
| | - Pawan Kumar Singh
- Department of Information Technology, Jadavpur University, Jadavpur University Second Campus, Plot No. 8, Salt Lake Bypass, LB Block, Sector III, Salt Lake City, Kolkata, West Bengal, 700106, India
| | - Ali Ahmadian
- Institute of IR 4.0, The National University of Malaysia, 43600, Bangi, Malaysia.
- Department of Mathematics, Near East University, Nicosia, TRNC, Mersin 10, Turkey.
- Institute for Mathematical Research, Universiti Putra Malaysia (UPM), 43400, Selangor, Malaysia.
| | - Massimiliano Ferrara
- Department of Management and Technology, ICRIOS - The Invernizzi Centre for Research in Innovation, Organization, Strategy and Entrepreneurship, Bocconi University, Via Sarfatti, 25, Milan, MI, 20136, Italy.
| | - Norazak Senu
- Institute for Mathematical Research, Universiti Putra Malaysia (UPM), 43400, Selangor, Malaysia
| | - Ram Sarkar
- Department of Computer Science and Engineering, Jadavpur University, 188, Raja S.C. Mallick Road, Kolkata, West Bengal, 700032, India
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22
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Samir A, Naguib NNN, Elnekeidy A, Baess AI, Shawky A. COVID-19 versus H1N1: challenges in radiological diagnosis—comparative study on 130 patients using chest HRCT. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [PMCID: PMC7966920 DOI: 10.1186/s43055-021-00455-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
During the current second wave of COVID-19, the radiologists are expected to face great challenges in differentiation between COVID-19 and other virulent influenza viruses, mainly H1N1. Accordingly, this study was performed in order to find any differentiating CT criteria that would help during the expected clinical overlap during the current Influenza season.
Results
This study was retrospectively conducted during the period from June till November 2020, on acute symptomatic 130 patients with no history of previous pulmonary diseases; 65 patients had positive PCR for COVID-19 including 50 mild patients and 15 critical or severe patients; meanwhile, the other 65 patients had positive PCR for H1N1 including 50 mild patients and 15 critical or severe patients. They included 74 males and 56 females (56.9%:43.1%). Their age ranged 14–90 years (mean age 38.9 ± 20.3 SD). HRCT findings were analyzed by four expert consultant radiologists in consensus. All patients with COVID-19 showed parenchymal or alveolar HRCT findings; only one of them had associated airway involvement. Among the 65 patients with H1N1; 56 patients (86.2%) had parenchymal or alveolar HRCT findings while six patients (9.2%) presented only by HRCT signs of airway involvement and three patients (4.6%) had mixed parenchymal and airway involvement. Regarding HRCT findings of airway involvement (namely tree in bud nodules, air trapping, bronchial wall thickening, traction bronchiectasis, and mucous plugging), all showed significant p value (ranging from 0.008 to 0.04). On the other hand, HRCT findings of parenchymal or alveolar involvement (mainly ground glass opacities) showed no significant relation.
Conclusion
HRCT can help in differentiation between non-severe COVID-19 and H1N1 based on signs of airway involvement.
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23
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Machado-Alba JE, Valladales-Restrepo LF, Machado-Duque ME, Gaviria-Mendoza A, Sánchez-Ramírez N, Usma-Valencia AF, Rodríguez-Martínez E, Rengifo-Franco E, Forero-Supelano VH, Gómez-Ramirez DM, Sabogal-Ortiz A. Factors associated with admission to the intensive care unit and mortality in patients with COVID-19, Colombia. PLoS One 2021; 16:e0260169. [PMID: 34797857 PMCID: PMC8604321 DOI: 10.1371/journal.pone.0260169] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 11/03/2021] [Indexed: 12/15/2022] Open
Abstract
Introduction Coronavirus disease 2019 (COVID-19) has affected millions of people worldwide, and several sociodemographic variables, comorbidities and care variables have been associated with complications and mortality. Objective To identify the factors associated with admission to intensive care units (ICUs) and mortality in patients with COVID-19 from 4 clinics in Colombia. Methods This was a follow-up study of a cohort of patients diagnosed with COVID-19 between March and August 2020. Sociodemographic, clinical (Charlson comorbidity index and NEWS 2 score) and pharmacological variables were identified. Multivariate analyses were performed to identify variables associated with the risk of admission to the ICU and death (p<0.05). Results A total of 780 patients were analyzed, with a median age of 57.0 years; 61.2% were male. On admission, 54.9% were classified as severely ill, 65.3% were diagnosed with acute respiratory distress syndrome, 32.4% were admitted to the ICU, and 26.0% died. The factors associated with a greater likelihood of ICU admission were severe pneumonia (OR: 9.86; 95%CI:5.99–16.23), each 1-point increase in the NEWS 2 score (OR:1.09; 95%CI:1.002–1.19), history of ischemic heart disease (OR:3.24; 95%CI:1.16–9.00), and chronic obstructive pulmonary disease (OR:2.07; 95%CI:1.09–3.90). The risk of dying increased in those older than 65 years (OR:3.08; 95%CI:1.66–5.71), in patients with acute renal failure (OR:6.96; 95%CI:4.41–11.78), admitted to the ICU (OR:6.31; 95%CI:3.63–10.95), and for each 1-point increase in the Charlson comorbidity index (OR:1.16; 95%CI:1.002–1.35). Conclusions Factors related to increasing the probability of requiring ICU care or dying in patients with COVID-19 were identified, facilitating the development of anticipatory intervention measures that favor comprehensive care and improve patient prognosis.
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Affiliation(s)
- Jorge Enrique Machado-Alba
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia
| | - Luis Fernando Valladales-Restrepo
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia.,Grupo de Investigación Biomedicina, Facultad de Medicina, Fundación Universitaria Autónoma de las Américas, Pereira, Colombia
| | - Manuel Enrique Machado-Duque
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia.,Grupo de Investigación Biomedicina, Facultad de Medicina, Fundación Universitaria Autónoma de las Américas, Pereira, Colombia
| | - Andrés Gaviria-Mendoza
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia.,Grupo de Investigación Biomedicina, Facultad de Medicina, Fundación Universitaria Autónoma de las Américas, Pereira, Colombia
| | - Nicolás Sánchez-Ramírez
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia
| | - Andrés Felipe Usma-Valencia
- Grupo de Investigación en Farmacoepidemiología y Farmacovigilancia, Universidad Tecnológica de Pereira-Audifarma S.A, Pereira, Risaralda, Colombia
| | - Esteban Rodríguez-Martínez
- Semillero de Investigación en Farmacología Geriátrica, Facultad de Medicina, Fundación Universitaria Autónoma de las Américas, Pereira, Risaralda, Colombia
| | - Eliana Rengifo-Franco
- Semillero de Investigación en Farmacología Geriátrica, Facultad de Medicina, Fundación Universitaria Autónoma de las Américas, Pereira, Risaralda, Colombia
| | | | - Diego Mauricio Gómez-Ramirez
- Grupo Ospedale, Grupo Operador Clínico Hospitalario por Outsourcing S.A.S - G-Ocho S.A.S, Área de Salud, Cali, Valle del Cauca, Colombia
| | - Alejandra Sabogal-Ortiz
- Grupo Ospedale, Grupo Operador Clínico Hospitalario por Outsourcing S.A.S - G-Ocho S.A.S, Área de Salud, Cali, Valle del Cauca, Colombia
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24
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Vianello A, Guarnieri G, Braccioni F, Lococo S, Molena B, Cecchetto A, Giraudo C, Bertagna De Marchi L, Caminati M, Senna G. The pathogenesis, epidemiology and biomarkers of susceptibility of pulmonary fibrosis in COVID-19 survivors. Clin Chem Lab Med 2021; 60:307-316. [PMID: 34783228 DOI: 10.1515/cclm-2021-1021] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/08/2021] [Indexed: 12/15/2022]
Abstract
Pulmonary fibrosis (PF), a pathological outcome of chronic and acute interstitial lung diseases associated to compromised wound healing, is a key component of the "post-acute COVID-19 syndrome" that may severely complicate patients' clinical course. Although inconclusive, available data suggest that more than a third of hospitalized COVID-19 patients develop lung fibrotic abnormalities after their discharge from hospital. The pathogenesis of PF in patients recovering from a severe acute case of COVID-19 is complex, and several hypotheses have been formulated to explain its development. An analysis of the data that is presently available suggests that biomarkers of susceptibility could help to identify subjects with increased probability of developing PF and may represent a means to personalize the management of COVID-19's long-term effects. Our review highlights the importance of both patient-related and disease-related contributing risk factors for PF in COVID-19 survivors and makes it definitely clear the possible use of acute phase and follow-up biomarkers for identifying the patients at greatest risk of developing this disease.
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Affiliation(s)
- Andrea Vianello
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Gabriella Guarnieri
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Fausto Braccioni
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Sara Lococo
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Beatrice Molena
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Antonella Cecchetto
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy
| | - Chiara Giraudo
- Department of Medicine DIMED, University of Padova, Padova, Italy
| | | | - Marco Caminati
- Asthma Center and Allergy Unit, University of Verona, Verona, Italy
| | - Gianenrico Senna
- Asthma Center and Allergy Unit, University of Verona, Verona, Italy
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25
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Lee JH, Hong H, Kim H, Lee CH, Goo JM, Yoon SH. CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict. TAEHAN YONGSANG UIHAKHOE CHI 2021; 82:1505-1523. [PMID: 36238884 PMCID: PMC9431975 DOI: 10.3348/jksr.2021.0096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 07/25/2021] [Accepted: 07/28/2021] [Indexed: 05/31/2023]
Abstract
Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. Materials and Methods We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy. Results From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. Conclusion Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.
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26
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Abstract
The acute course of COVID-19 is variable and ranges from asymptomatic infection to fulminant respiratory failure. Patients recovering from COVID-19 can have persistent symptoms and CT abnormalities of variable severity. At 3 months after acute infection, a subset of patients will have CT abnormalities that include ground-glass opacity (GGO) and subpleural bands with concomitant pulmonary function abnormalities. At 6 months after acute infection, some patients have persistent CT changes to include the resolution of GGOs seen in the early recovery phase and the persistence or development of changes suggestive of fibrosis, such as reticulation with or without parenchymal distortion. The etiology of lung disease after COVID-19 may be a sequela of prolonged mechanical ventilation, COVID-19-induced acute respiratory distress syndrome (ARDS), or direct injury from the virus. Predictors of lung disease after COVID-19 include need for intensive care unit admission, mechanical ventilation, higher inflammatory markers, longer hospital stay, and a diagnosis of ARDS. Treatments of lung disease after COVID-19 are being investigated, including the potential of antifibrotic agents for prevention of lung fibrosis after COVID-19. Future research is needed to determine the long-term persistence of lung disease after COVID-19, its impact on patients, and methods to either prevent or treat it. © RSNA, 2021.
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Affiliation(s)
| | - Brooke Heyman
- Division of Pulmonary, Sleep and Critical Care Medicine, Department
of Medicine, NYU Langone Health, NYU Grossman School of Medicine, New York,
NY
| | - Jane P. Ko
- Department of Radiology, NYU Langone Health, NYU Grossman School of
Medicine, New York, NY
| | - Rany Condos
- Division of Pulmonary, Sleep and Critical Care Medicine, Department
of Medicine, NYU Langone Health, NYU Grossman School of Medicine, New York,
NY
| | - David A. Lynch
- Department of Radiology, National Jewish Health, Denver, CO,
USA
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27
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Tamal M, Alshammari M, Alabdullah M, Hourani R, Alola HA, Hegazi TM. An integrated framework with machine learning and radiomics for accurate and rapid early diagnosis of COVID-19 from Chest X-ray. EXPERT SYSTEMS WITH APPLICATIONS 2021; 180:115152. [PMID: 33967406 PMCID: PMC8095015 DOI: 10.1016/j.eswa.2021.115152] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 05/01/2021] [Accepted: 05/01/2021] [Indexed: 05/24/2023]
Abstract
The objective of the research article is to propose and validate a combination of machine learning and radiomics features to detect COVID-19 early and rapidly from chest X-ray (CXR) in presence of other viral/bacterial pneumonia and at different severity levels of diseases. It is vital to assess the performance of any diagnosis method on an independent data set and at very early stage of the disease when the disease severity of is very low. In such cases, most of the diagnosis methods fail. A total of 378 CXR images containing both normal lung and pneumonia (both COVID-19 and others lung conditions) were collected from publically available data set. 71 radiomics features for each lung segment were chosen from 100 extracted features based on Z-score heatmap and one way ANOVA test that can detect COVID-19. Three best performing classical machine learning algorithms during the training phase - 1) fine Gaussian support vector machine (SVM), 2) fine k-nearest neighbor (KNN) and 3) ensemble bagged model (EBM) trees were chosen for further evaluation on an independent test data set. The independent test data set consists of 115 COVID-19 CXR images collected from a local hospital and 100 CXR images collected from publically available data set containing normal lung and viral/bacterial pneumonia. Severity was scored between 0 to 4 by two experienced radiologists for each lung with pneumonia (both COVID-19 and non COVID-19) for the test data set. Ensemble Bagging Model Trees (EBM) with the selected radiomics features is the most suitable to distinguish between COVID-19 and other lung infections with an overall sensitivity of 87.8% and specificity of 97% (95.2% accuracy and 0.9228 area under curve) and is robust across severity levels. The method also can detect COVID-19 from CXR when two experienced radiologists were unable to detect any abnormality in the lung CXR (represented by severity score of 0). Once the CXR is acquired and lung is segmented, it takes less than two minutes for extracting radiomics features and providing diagnosis result. Since the proposed method does not require any manual intervention (e.g., sample collection etc.), it can be straightway integrated with standard X-ray reporting system to be used as an efficient, cost-effective and rapid early diagnosis device.
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Affiliation(s)
- Mahbubunnabi Tamal
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
| | - Maha Alshammari
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
| | - Meernah Alabdullah
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
| | - Rana Hourani
- Department of Biomedical Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
| | - Hossain Abu Alola
- Department of Radiology, College of Medicine, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
| | - Tarek M Hegazi
- Department of Radiology, College of Medicine, Imam Abdulrahman Bin Faisal University, PO Box 1982, Dammam 31441, Saudi Arabia
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28
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AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia. J Comput Assist Tomogr 2021; 45:970-978. [PMID: 34581706 PMCID: PMC8607923 DOI: 10.1097/rct.0000000000001224] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Objective To quantitatively evaluate computed tomography (CT) parameters of coronavirus disease 2019 (COVID-19) pneumonia an artificial intelligence (AI)-based software in different clinical severity groups during the disease course. Methods From March 11 to April 15, 2020, 51 patients (age, 18–84 years; 28 men) diagnosed and hospitalized with COVID-19 pneumonia with a total of 116 CT scans were enrolled in the study. Patients were divided into mild (n = 12), moderate (n = 31), and severe (n = 8) groups based on clinical severity. An AI-based quantitative CT analysis, including lung volume, opacity score, opacity volume, percentage of opacity, and mean lung density, was performed in initial and follow-up CTs obtained at different time points. Receiver operating characteristic analysis was performed to find the diagnostic ability of quantitative CT parameters for discriminating severe from nonsevere pneumonia. Results In baseline assessment, the severe group had significantly higher opacity score, opacity volume, higher percentage of opacity, and higher mean lung density than the moderate group (all P ≤ 0.001). Through consecutive time points, the severe group had a significant decrease in lung volume (P = 0.006), a significant increase in total opacity score (P = 0.003), and percentage of opacity (P = 0.007). A significant increase in total opacity score was also observed for the mild group (P = 0.011). Residual opacities were observed in all groups. The involvement of more than 4 lobes (sensitivity, 100%; specificity, 65.26%), total opacity score greater than 4 (sensitivity, 100%; specificity, 64.21), total opacity volume greater than 337.4 mL (sensitivity, 80.95%; specificity, 84.21%), percentage of opacity greater than 11% (sensitivity, 80.95%; specificity, 88.42%), total high opacity volume greater than 10.5 mL (sensitivity, 95.24%; specificity, 66.32%), percentage of high opacity greater than 0.8% (sensitivity, 85.71%; specificity, 80.00%) and mean lung density HU greater than −705 HU (sensitivity, 57.14%; specificity, 90.53%) were related to severe pneumonia. Conclusions An AI-based quantitative CT analysis is an objective tool in demonstrating disease severity and can also assist the clinician in follow-up by providing information about the disease course and prognosis according to different clinical severity groups.
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29
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Li J, Yan R, Zhai Y, Qi X, Lei J. Chest CT findings in patients with coronavirus disease 2019 (COVID-19): a comprehensive review. Diagn Interv Radiol 2021; 27:621-632. [PMID: 33135665 PMCID: PMC8480948 DOI: 10.5152/dir.2020.20212] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The objective of this review was to summarize the most pertinent CT imaging findings in patients with coronavirus disease 2019 (COVID-19). A literature search retrieved eligible studies in PubMed, EMBASE, Cochrane Library and Web of Science up to June 1, 2020. A comprehensive review of publications of the Chinese Medical Association about COVID-19 was also performed. A total of 84 articles with more than 5340 participants were included and reviewed. Chest CT comprised 92.61% of abnormal CT findings overall. Compared with real-time polymerase chain reaction result, CT findings has a sensitivity of 96.14% but a low specificity of 40.48% in diagnosing COVID-19. Ground glass opacity (GGO), pure (57.31%) or mixed with consolidation (41.51%) were the most common CT features with a majority of bilateral (80.32%) and peripheral (66.21%) lung involvement. The opacity might associate with other imaging features, including air bronchogram (41.07%), vascular enlargement (54.33%), bronchial wall thickening (19.12%), crazy-paving pattern (27.55%), interlobular septal thickening (42.48%), halo sign (25.48%), reverse halo sign (12.29%), bronchiectasis (32.44%), and pulmonary fibrosis (26.22%). Other accompanying signs including pleural effusion, lymphadenopathy and pericardial effusion were rare, but pleural thickening was common. The younger or early stage patients tended to have more GGOs, while extensive/multilobar involvement with consolidation was prevalent in the older or severe population. Children with COVID-19 showed significantly lower incidences of some ancillary findings than those of adults and showed a better performance on CT during follow up. Follow-up CT showed GGO lesions gradually decreased, and the consolidation lesions first increased and then remained relatively stable at 6-13 days, and then absorbed and fibrosis increased after 14 days. Chest CT imaging is an important component in the diagnosis, staging, disease progression and follow-up of patients with COVID-19.
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Affiliation(s)
- Jinkui Li
- Department of Radiology, the First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center, Accurate Image Collaborative Innovation International Science and Technology Cooperation, Lanzhou, China
| | - Ruifeng Yan
- Department of Radiology, the First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center, Accurate Image Collaborative Innovation International Science and Technology Cooperation, Lanzhou, China
| | - Yanan Zhai
- Department of Radiology, the First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center, Accurate Image Collaborative Innovation International Science and Technology Cooperation, Lanzhou, China
| | - Xiaolong Qi
- The first Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Junqiang Lei
- Department of Radiology, the First Hospital of Lanzhou University, Intelligent Imaging Medical Engineering Research Center, Accurate Image Collaborative Innovation International Science and Technology Cooperation, Lanzhou, China
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Tung-Chen Y, Martí de Gracia M, Parra-Gordo ML, Díez-Tascón A, Agudo-Fernández S, Ossaba-Vélez S. Usefulness of Lung Ultrasound Follow-up in Patients Who Have Recovered From Coronavirus Disease 2019. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2021; 40:1971-1974. [PMID: 33159704 DOI: 10.1002/jum.15556] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/24/2020] [Accepted: 10/16/2020] [Indexed: 06/11/2023]
Abstract
Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2 infection, which tends to be mild. Even in these cases, our understanding is still incomplete, particularly regarding its sequelae and long-term outcomes. We describe 3 recovered patients who had coronavirus disease 2019, with long-persisting symptoms after recovery, in whom chest computed tomographic and concurrent lung ultrasound examinations were performed. It is possible to correlate the findings from lung ultrasound with the symptoms and the fibrosis or residual abnormalities present on chest computed tomography. Lung ultrasound, which is easy to use, without side effects or radiation, helps monitor the disease resolution or assess early progression to lung fibrosis, as exemplified in the cases reported.
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Affiliation(s)
- Yale Tung-Chen
- Department of Internal Medicine, Hospital Universitario La Paz, Madrid, Spain
| | | | | | - Aurea Díez-Tascón
- Department of Emergency Radiology, Hospital Universitario La Paz, Madrid, Spain
| | | | - Silvia Ossaba-Vélez
- Department of Emergency Radiology, Hospital Universitario La Paz, Madrid, Spain
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Caruso D, Guido G, Zerunian M, Polidori T, Lucertini E, Pucciarelli F, Polici M, Rucci C, Bracci B, Nicolai M, Cremona A, De Dominicis C, Laghi A. Postacute Sequelae of COVID-19 Pneumonia: 6-month Chest CT Follow-up. Radiology 2021; 301:E396-E405. [PMID: 34313468 PMCID: PMC8335814 DOI: 10.1148/radiol.2021210834] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background The long-term post acute pulmonary sequelae of COVID-19 remain
unknown. Purpose To evaluate lung injury in patients affected by COVID-19 pneumonia at
six-month follow-up compared to baseline chest CT. Methods From March 19th,2020 to May 24th,2020, patients with moderate to severe
COVID-19 pneumonia and baseline Chest CT were prospectively enrolled at
six-months follow-up. CT qualitative findings, semi-quantitative Lungs
Severity Score (LSS) and well-aerated lung quantitative Chest CT (QCCT)
were analyzed. Baseline LSS and QCCT performances in predicting
fibrotic-like changes (reticular pattern and/or honeycombing) at
six-month follow-up Chest CT were tested with receiver operating
characteristic curves. Univariable and multivariable logistic regression
analysis were used to test clinical and radiological features predictive
of fibrotic-like changes. The multivariable analysis was performed with
clinical parameters alone (clinical model), radiological parameters
alone (radiological model) and the combination of clinical and
radiological parameters (combined model). Results One-hundred-eighteen patients, with both baseline and six-month follow-up
Chest CT, were included in the study (62 female, mean age 65±12
years). At follow-up Chest CT, 85/118 (72%) patients showed
fibrotic-like changes and 49/118 (42%) showed GGOs. Baseline LSS
(>14), QCCT (≤3.75L and ≤80%) showed an
excellent performance in predicting fibrotic-like changes at Chest CT
follow-up. In the multivariable analysis, AUC was .89 (95%CI
.77-.96) for the clinical model, .81 (95%CI .68-.9) for the
radiological model and .92 (95%CI .81-.98)for the combined
model. Conclusion At six-month follow-up Chest CT, 72% of patients showed late
sequelae, in particular fibrotic-like changes. Baseline LSS and QCCT of
well-aerated lung showed an excellent performance in predicting
fibrotic-like changes at six-month Chest CT (AUC>.88). Male sex,
cough, lymphocytosis and QCCT well-aerated lung were significant
predictors of fibrotic-like changes at six-month with an inverse
correlation (AUC .92). See also the editorial by Wells and Devaraj.
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Affiliation(s)
- Damiano Caruso
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Gisella Guido
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Marta Zerunian
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Tiziano Polidori
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Elena Lucertini
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Francesco Pucciarelli
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Michela Polici
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Carlotta Rucci
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Benedetta Bracci
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Matteo Nicolai
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Antonio Cremona
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Chiara De Dominicis
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Andrea Laghi
- Institution: Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
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Liu J, Wang T, Cai Q, Huang D, Sun L, He Q, Wang FS, Chen J. Acute Kidney Injury and Early Predictive Factors in COVID-19 Patients. Front Med (Lausanne) 2021; 8:604242. [PMID: 34322497 PMCID: PMC8311118 DOI: 10.3389/fmed.2021.604242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 06/11/2021] [Indexed: 01/14/2023] Open
Abstract
Objectives: Our objective was to explore the incidence and early predictive factors of acute kidney injury in coronavirus disease 2019 (COVID-19) patients. Method: We established a retrospective cohort of 408 patients who were admitted to Shenzhen Third People's Hospital in Shenzhen, China, between January 1 and March 31, 2020. Clinical outcomes and renal function were monitored until April 12, 2020, with a median follow-up duration of 21 days [interquartile range (IQR) = 14-33]. Results: When first admitted to hospital (baseline), 19.36% (79/408) presented renal dysfunction [estimated glomerular filtration rate (eGFR) <90 ml/min/1.73 m2]. During follow-up, 3.9% (16/408) developed acute kidney injury (AKI). Age ≥60 years [hazard ratio (HR) = 4.78, 95% CI = 1.10-20.69], PaO2/FiO2 ratio <300 (HR = 3.48, 95% CI = 1.04-11.62), and higher creatinine (HR = 1.04, 95% CI = 1.01-1.07) at baseline independently predicted the risk of AKI. Respectively, 25.0% (102/408), 3.9% (16/408), 0.5% (2/408), 1.0% (4/408), and 0.2% (1/408) experienced G2, G3a, G3b, G4, and G5 as their most severe category during hospitalization, while 69.4% (283/408) had normal eGFRs throughout the follow-up period. When finally discharged from hospital, there were 12.5% (51/408) of patients with abnormal eGFRs. Conclusions: COVID-19 patients can be at risk of AKI and continuous eGFR decline during hospitalization, which can be early predicted by baseline factors. Some individuals still had renal dysfunction when finally discharged from hospital.
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Affiliation(s)
- Jiaye Liu
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Tingyan Wang
- Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Qingxian Cai
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Deliang Huang
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Liqin Sun
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Qing He
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Fu-Sheng Wang
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
- Treatment and Research Center for Infectious Diseases, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Jun Chen
- National Clinical Research Center for Infectious Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
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Gündüz Y, Karabay O, Erdem AF, Arık E, Öztürk MH. Evaluation of initial chest computed tomography (CT) findings of COVID-19 pneumonia in 117 deceased patients: a retrospective study. Turk J Med Sci 2021; 51:929-938. [PMID: 33315351 PMCID: PMC8283471 DOI: 10.3906/sag-2009-183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 12/12/2020] [Indexed: 01/08/2023] Open
Abstract
Background/aim There is no study in the literature in which only chest computed tomography (CT) findings of deceased cases obtained at admission were examined, and the relationship between these findings and mortality was evaluated. Materials and methods In this retrospective study, a total of 117 deceased patients with COVID-19 infection confirmed by positive polymerase chain reaction and undergone chest CT were enrolled. We evaluated initial chest CT findings and their relationship, location, prevalence, and the frequency with mortality. Results The mean age of patients was 73 ±18 years; 71 of all patients were male and 46 were female. The predominant feature was pure ground-glass opacity (GGO) lesion (82.0%), and 59.8% of cases had pure consolidation. There was no cavitation or architectural distorsion. Pericardial effusion was found in 9.4% the patients, and pleural effusions were found in 15.3% of them. Mediastinal lymphadenopathy was only 11.9% in total. Conclusion In deceased patients, on admission CTs, pure consolidation, pleural and pericardial effusion, mediastinal LAP were more common than ordinary cases. It was these findings that should also raise the concern when they were seen on chest CT; therefore, these radiologic features have the potential to represent prognostic imaging markers in patients with COVID-19 pneumonia.
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Affiliation(s)
- Yasemin Gündüz
- Department of Radiology, Faculty of Medicine, Sakarya University, Sakarya, Turkey
| | - Oğuz Karabay
- Department of Infectious Diseases and Clinical Microbiology, Faculty of Medicine, Sakarya University, Sakarya, Turkey
| | - Ali Fuat Erdem
- Department of Anesthesiology and Reanimation, Faculty of Medicine, Sakarya University, Sakarya, Turkey
| | - Erbil Arık
- Department of Radiology, Faculty of Medicine, Sakarya University, Sakarya, Turkey
| | - Mehmet Halil Öztürk
- Department of Radiology, Faculty of Medicine, Sakarya University, Sakarya, Turkey
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Man MA, Rajnoveanu RM, Motoc NS, Bondor CI, Chis AF, Lesan A, Puiu R, Lucaciu SR, Dantes E, Gergely-Domokos B, Fira-Mladinescu O. Neutrophil-to-lymphocyte ratio, platelets-to-lymphocyte ratio, and eosinophils correlation with high-resolution computer tomography severity score in COVID-19 patients. PLoS One 2021; 16:e0252599. [PMID: 34181675 PMCID: PMC8238190 DOI: 10.1371/journal.pone.0252599] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 03/23/2021] [Indexed: 01/08/2023] Open
Abstract
Inflammation has an important role in the progression of various viral pneumonia, including COVID-19. Circulating biomarkers that can evaluate inflammation and immune status are potentially useful in diagnosing and prognosis of COVID-19 patients. Even more so when they are a part of the routine evaluation, chest CT could have even higher diagnostic accuracy than RT-PCT alone in a suggestive clinical context. This study aims to evaluate the correlation between inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocytes ratio (PLR), and eosinophils with the severity of CT lesions in patients with COVID-19. The second objective was to seek a statically significant cut-off value for NLR and PLR that could suggest COVID-19. Correlation of both NLR and PLR with already established inflammatory markers such as CRP, ESR, and those specific for COVID-19 (ferritin, D-dimers, and eosinophils) were also evaluated. One hundred forty-nine patients with confirmed COVID-19 disease and 149 age-matched control were evaluated through blood tests, and COVID-19 patients had thorax CT performed. Both NLR and PLR correlated positive chest CT scan severity. Both NLR and PLR correlated positive chest CT scan severity. When NLR value is below 5.04, CT score is lower than 3 with a probability of 94%, while when NLR is higher than 5.04, the probability of severe CT changes is only 50%. For eosinophils, a value of 0.35% corresponds to chest CT severity of 2 (Se = 0.88, Sp = 0.43, AUC = 0.661, 95% CI (0.544; 0.779), p = 0.021. NLR and PLR had significantly higher values in COVID-19 patients. In our study a NLR = 2.90 and PLR = 186 have a good specificity (0.89, p = 0.001, respectively 0.92, p<0.001). Higher levels in NLR, PLR should prompt the clinician to prescribe a thorax CT as it could reveal important lesions that could influence the patient’s future management.
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Affiliation(s)
- Milena Adina Man
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
| | - Ruxandra-Mioara Rajnoveanu
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
| | - Nicoleta Stefania Motoc
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
- * E-mail:
| | - Cosmina Ioana Bondor
- Department of Medical Biostatistics, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Romania
| | - Ana Florica Chis
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
| | - Andrei Lesan
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
| | - Ruxandra Puiu
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
| | - Sergiu-Remus Lucaciu
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
| | - Elena Dantes
- Faculty of Medicine, "Ovidius" University, Constanta, Romania
| | - Bianca Gergely-Domokos
- Department of Medical Sciences, Pulmonology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj Napoca, Cluj, Romania
- "Leon Daniello," Clinical Hospital of Pulmonology, Cluj Napoca, Cluj, Romania
| | - Ovidiu Fira-Mladinescu
- Center for Research and Innovation in Personalized Medicine of Respiratory Diseases, Department of Infectious Diseases, Pulmonology, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania
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Schiaffino S, Codari M, Cozzi A, Albano D, Alì M, Arioli R, Avola E, Bnà C, Cariati M, Carriero S, Cressoni M, Danna PSC, Della Pepa G, Di Leo G, Dolci F, Falaschi Z, Flor N, Foà RA, Gitto S, Leati G, Magni V, Malavazos AE, Mauri G, Messina C, Monfardini L, Paschè A, Pesapane F, Sconfienza LM, Secchi F, Segalini E, Spinazzola A, Tombini V, Tresoldi S, Vanzulli A, Vicentin I, Zagaria D, Fleischmann D, Sardanelli F. Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features. J Pers Med 2021; 11:501. [PMID: 34204911 PMCID: PMC8230339 DOI: 10.3390/jpm11060501] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 05/31/2021] [Accepted: 06/01/2021] [Indexed: 12/26/2022] Open
Abstract
Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann-Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p < 0.001) and higher median ascending aortic diameter (36.6 mm versus 34.0 mm, p < 0.001). SVM and MLP best models considered the same ten input features, yielding a 0.747 (precision 0.522, recall 0.800) and 0.844 (precision 0.680, recall 0.567) area under the curve, respectively. In this model integrating clinical and radiological data, pulmonary artery diameter was the third most important predictor after age and parenchymal involvement extent, contributing to reliable in-hospital mortality prediction, highlighting the value of vascular metrics in improving patient stratification.
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Affiliation(s)
- Simone Schiaffino
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy; (S.S.); (M.C.); (G.D.L.); (F.S.); (F.S.)
| | - Marina Codari
- Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, USA; (M.C.); (D.F.)
| | - Andrea Cozzi
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
| | - Domenico Albano
- IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milan, Italy; (D.A.); (C.M.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Via del Vespro 127, 90127 Palermo, Italy
| | - Marco Alì
- Department of Diagnostic Imaging and Stereotactic Radiosurgery, C.D.I. Centro Diagnostico Italiano S.p.A., Via Simone Saint Bon 20, 20147 Milan, Italy;
| | - Roberto Arioli
- Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Giuseppe Mazzini 18, 28100 Novara, Italy; (R.A.); (P.S.C.D.); (Z.F.); (A.P.); (D.Z.)
| | - Emanuele Avola
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy; (E.A.); (S.C.); (G.D.P.)
| | - Claudio Bnà
- Unit of Interventional Radiology, Unit of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Via Leonida Bissolati 57, 25124 Brescia, Italy; (C.B.); (L.M.)
| | - Maurizio Cariati
- Diagnostic and Interventional Radiology Service, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, 20142 Milan, Italy; (M.C.); (R.A.F.); (S.T.)
| | - Serena Carriero
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy; (E.A.); (S.C.); (G.D.P.)
| | - Massimo Cressoni
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy; (S.S.); (M.C.); (G.D.L.); (F.S.); (F.S.)
| | - Pietro S. C. Danna
- Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Giuseppe Mazzini 18, 28100 Novara, Italy; (R.A.); (P.S.C.D.); (Z.F.); (A.P.); (D.Z.)
| | - Gianmarco Della Pepa
- Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy; (E.A.); (S.C.); (G.D.P.)
| | - Giovanni Di Leo
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy; (S.S.); (M.C.); (G.D.L.); (F.S.); (F.S.)
| | - Francesco Dolci
- Emergency Department, ASST Crema—Ospedale Maggiore, Largo Ugo Dossena 2, 26013 Crema, Italy;
| | - Zeno Falaschi
- Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Giuseppe Mazzini 18, 28100 Novara, Italy; (R.A.); (P.S.C.D.); (Z.F.); (A.P.); (D.Z.)
| | - Nicola Flor
- Unit of Radiology, Ospedale Universitario Luigi Sacco—ASST Fatebenefratelli Sacco, Via Giovanni Battista Grassi 74, 20157 Milan, Italy;
| | - Riccardo A. Foà
- Diagnostic and Interventional Radiology Service, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, 20142 Milan, Italy; (M.C.); (R.A.F.); (S.T.)
- Unit of Interventional Radiology, Unit of Radiology, ASST Crema—Ospedale Maggiore, Largo Ugo Dossena 2, 26013 Crema, Italy; (G.L.); (A.S.)
| | - Salvatore Gitto
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
| | - Giovanni Leati
- Unit of Interventional Radiology, Unit of Radiology, ASST Crema—Ospedale Maggiore, Largo Ugo Dossena 2, 26013 Crema, Italy; (G.L.); (A.S.)
| | - Veronica Magni
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
| | - Alexis E. Malavazos
- High Speciality Center for Dietetics, Nutritional Education and Cardiometabolic Prevention, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy;
| | - Giovanni Mauri
- Department of Oncology and Hematology-Oncology, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy; (G.M.); (A.V.)
- Division of Interventional Radiology, IEO—Istituto Europeo di Oncologia IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy
| | - Carmelo Messina
- IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milan, Italy; (D.A.); (C.M.)
| | - Lorenzo Monfardini
- Unit of Interventional Radiology, Unit of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Via Leonida Bissolati 57, 25124 Brescia, Italy; (C.B.); (L.M.)
| | - Alessio Paschè
- Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Giuseppe Mazzini 18, 28100 Novara, Italy; (R.A.); (P.S.C.D.); (Z.F.); (A.P.); (D.Z.)
| | - Filippo Pesapane
- Division of Breast Radiology, IEO—Istituto Europeo di Oncologia IRCCS, Via Giuseppe Ripamonti 435, 20141 Milan, Italy;
| | - Luca M. Sconfienza
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
- IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milan, Italy; (D.A.); (C.M.)
| | - Francesco Secchi
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy; (S.S.); (M.C.); (G.D.L.); (F.S.); (F.S.)
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
| | - Edoardo Segalini
- Department of General and Emergency Surgery, ASST Crema—Ospedale Maggiore, Largo Ugo Dossena 2, 26013 Crema, Italy;
| | - Angelo Spinazzola
- Unit of Interventional Radiology, Unit of Radiology, ASST Crema—Ospedale Maggiore, Largo Ugo Dossena 2, 26013 Crema, Italy; (G.L.); (A.S.)
| | - Valeria Tombini
- ASST Grande Ospedale Metropolitano Niguarda, Piazza dell’Ospedale Maggiore 3, 20162 Milan, Italy; (V.T.); (I.V.)
| | - Silvia Tresoldi
- Diagnostic and Interventional Radiology Service, ASST Santi Paolo e Carlo, Via Antonio di Rudinì 8, 20142 Milan, Italy; (M.C.); (R.A.F.); (S.T.)
| | - Angelo Vanzulli
- Department of Oncology and Hematology-Oncology, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy; (G.M.); (A.V.)
- ASST Grande Ospedale Metropolitano Niguarda, Piazza dell’Ospedale Maggiore 3, 20162 Milan, Italy; (V.T.); (I.V.)
| | - Ilaria Vicentin
- ASST Grande Ospedale Metropolitano Niguarda, Piazza dell’Ospedale Maggiore 3, 20162 Milan, Italy; (V.T.); (I.V.)
| | - Domenico Zagaria
- Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Corso Giuseppe Mazzini 18, 28100 Novara, Italy; (R.A.); (P.S.C.D.); (Z.F.); (A.P.); (D.Z.)
| | - Dominik Fleischmann
- Department of Radiology, School of Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, USA; (M.C.); (D.F.)
- Cardiovascular Institute, 265 Campus Drive, Stanford University, Stanford, CA 94305, USA
| | - Francesco Sardanelli
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097 Milan, Italy; (S.S.); (M.C.); (G.D.L.); (F.S.); (F.S.)
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy; (S.G.); (V.M.); (L.M.S.)
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Ramos-Casals M, Brito-Zerón P, Mariette X. Systemic and organ-specific immune-related manifestations of COVID-19. Nat Rev Rheumatol 2021; 17:315-332. [PMID: 33903743 PMCID: PMC8072739 DOI: 10.1038/s41584-021-00608-z] [Citation(s) in RCA: 193] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2021] [Indexed: 01/08/2023]
Abstract
Immune-related manifestations are increasingly recognized conditions in patients with COVID-19, with around 3,000 cases reported worldwide comprising more than 70 different systemic and organ-specific disorders. Although the inflammation caused by SARS-CoV-2 infection is predominantly centred on the respiratory system, some patients can develop an abnormal inflammatory reaction involving extrapulmonary tissues. The signs and symptoms associated with this excessive immune response are very diverse and can resemble some autoimmune or inflammatory diseases, with the clinical phenotype that is seemingly influenced by epidemiological factors such as age, sex or ethnicity. The severity of the manifestations is also very varied, ranging from benign and self-limiting features to life-threatening systemic syndromes. Little is known about the pathogenesis of these manifestations, and some tend to emerge within the first 2 weeks of SARS-CoV-2 infection, whereas others tend to appear in a late post-infectious stage or even in asymptomatic patients. As the body of evidence comprises predominantly case series and uncontrolled studies, diagnostic and therapeutic decision-making is unsurprisingly often based on the scarcely reported experience and expert opinion. Additional studies are required to learn about the mechanisms involved in the development of these manifestations and apply that knowledge to achieve early diagnosis and the most suitable therapy.
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Affiliation(s)
- Manuel Ramos-Casals
- Department of Autoimmune Diseases, ICMiD, Hospital Clínic, Barcelona, Spain.
- Department of Medicine, University of Barcelona, Barcelona, Spain.
| | - Pilar Brito-Zerón
- Department of Internal Medicine, Hospital CIMA-Sanitas, Barcelona, Spain
| | - Xavier Mariette
- Department of Rheumatology, Center for Immunology of Viral Infections and Autoimmune Diseases, Université Paris-Saclay, INSERM, Assistance Publique - Hôpitaux de Paris, Hôpital Bicêtre, Le Kremlin-Bicêtre, Paris, France
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Role of Chest Computed Tomography versus Real Time Reverse Transcription Polymerase Chain Reaction for Diagnosis of COVID-19: A Systematic Review and Meta-Analysis. Interdiscip Perspect Infect Dis 2021; 2021:8798575. [PMID: 34194491 PMCID: PMC8184322 DOI: 10.1155/2021/8798575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 12/31/2020] [Accepted: 02/01/2021] [Indexed: 01/08/2023] Open
Abstract
Background The current global pandemic of COVID-19 is considered a public health emergency. The diagnosis of COVID-19 depends on detection of the viral nucleic acid by real time reverse transcription polymerase chain reaction (RT-PCR). However, false-negative RT-PCR tests are reported and could hinder the control of the pandemic. Chest computed tomography could achieve a more reliable diagnosis and represent a complementary diagnostic tool. Aim To perform a meta-analysis and systematic review to find out the role of chest computed tomography versus RT-PCR for precise diagnosis of COVID-19 infection. Methods We searched three electronic databases (PubMed, ScienceDirect, and Scopus) from April 1 to April 20, 2020, to find out articles including the accuracy of chest computed tomography scan versus RT-PCR for diagnosis of SARS-CoV-2 infection. Observational studies, case series, and case reports were included. Results A total of 238 articles were retrieved from the search strategy. Following screening, 39 articles were chosen for full text assessment and finally 35 articles were included for qualitative and quantitative analysis. Chest computed tomography showed a wide range of sensitivity varied from 12%–100%. Conclusion Chest computed tomography is playing a key role for diagnosis and detection of COVID-19 infection. Computed tomography image findings may precede the initially positive RT-PCR assay.
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Schmiady MO, Hofmann M, Sromicki J, Halbe M, van Tilburg K, Aser R, Mestres CA, Maisano F, Ferrari E. Initiation of an inter-hospital extracorporeal membrane oxygenation transfer programme for critically ill patients with coronavirus disease 2019: bringing extracorporeal membrane oxygenation support to peripheral hospitals. Interact Cardiovasc Thorac Surg 2021; 32:812-816. [PMID: 33647975 PMCID: PMC7989441 DOI: 10.1093/icvts/ivaa326] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/31/2020] [Accepted: 11/09/2020] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES Extracorporeal membrane oxygenation (ECMO) is a resource-intensive, highly specialized and expensive therapy that is often reserved for high-volume centres. In recent years, we established an inter-hospital ECMO transfer programme that enables ECMO implants in peripheral hospitals. During the pandemic, the programme was expanded to include ECMO support in selected critically ill patients with coronavirus disease 2019 (COVID-19). METHODS This retrospective single-centre study reports the technical details and challenges encountered during our initial experience with ECMO implants in peripheral hospitals for patients with COVID-19. RESULTS During March and April 2020, our team at the University Hospital of Zurich performed 3 out-of-centre ECMO implants at different peripheral hospitals. The implants were performed without any complications. The patients were transported by ambulance or helicopter. Good preparation and selection of the required supplies are the keys to success. The implant should be performed by a well-trained, seasoned ECMO team, because options are limited in most peripheral hospitals. CONCLUSIONS Out-of-centre ECMO implants in well-selected patients with COVID-19 is feasible and safe if a well-established organization is available and if the implantation is done by an experienced and regularly trained team.
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Affiliation(s)
- Martin O Schmiady
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Michael Hofmann
- Department of Vascular Surgery, University Hospital Zurich, Zurich, Switzerland
| | - Juri Sromicki
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Maximilian Halbe
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Koen van Tilburg
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Raed Aser
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Carlos A Mestres
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Francesco Maisano
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
| | - Enrico Ferrari
- Division of Cardiac Surgery, University Heart Center, University Hospital of Zurich, Zurich, Switzerland
- Cardiovascular Surgery Unit, Cardiocentro Ticino, Lugano, Switzerland
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Salamanna F, Veronesi F, Martini L, Landini MP, Fini M. Post-COVID-19 Syndrome: The Persistent Symptoms at the Post-viral Stage of the Disease. A Systematic Review of the Current Data. Front Med (Lausanne) 2021; 8:653516. [PMID: 34017846 PMCID: PMC8129035 DOI: 10.3389/fmed.2021.653516] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/10/2021] [Indexed: 01/08/2023] Open
Abstract
Whilst the entire world is battling the second wave of COVID-19, a substantial proportion of patients who have suffered from the condition in the past months are reporting symptoms that last for months after recovery, i. e., long-term COVID-19 symptoms. We aimed to assess the current evidence on the long-term symptoms in COVID-19 patients. We did a systematic review on PubMed, Web of Science, EMBASE, and Google Scholar from database inception to February 15, 2021, for studies on long-term COVID-19 symptoms. We included all type of papers that reported at least one long-term COVID-19 symptom. We screened studies using a standardized data collection form and pooled data from published studies. Cohort cross-sectional, case-report, cases-series, case-control studies, and review were graded using specific quality assessment tools. Of 11,361 publications found following our initial search we assessed 218 full-text articles, of which 145 met all selection criteria. We found that 20.70% of reports on long-term COVID-19 symptoms were on abnormal lung functions, 24.13% on neurologic complaints and olfactory dysfunctions, and 55.17% on specific widespread symptoms, mainly chronic fatigue, and pain. Despite the relatively high heterogeneity of the reviewed studies, our findings highlighted that a noteworthy proportion of patients who have suffered from SARS-CoV-2 infection present a "post-COVID syndrome." The multifaceted understanding of all aspects of the COVID-19 pandemic, including these long-term symptoms, will allow us to respond to all the global health challenges, thus paving the way to a stronger public health.
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Affiliation(s)
- Francesca Salamanna
- IRCCS Istituto Ortopedico Rizzoli, Complex Structure of Surgical Sciences and Technologies, Bologna, Italy
| | - Francesca Veronesi
- IRCCS Istituto Ortopedico Rizzoli, Complex Structure of Surgical Sciences and Technologies, Bologna, Italy
| | - Lucia Martini
- IRCCS Istituto Ortopedico Rizzoli, Complex Structure of Surgical Sciences and Technologies, Bologna, Italy
| | | | - Milena Fini
- IRCCS Istituto Ortopedico Rizzoli, Complex Structure of Surgical Sciences and Technologies, Bologna, Italy
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40
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Larici AR, Cicchetti G, Marano R, Bonomo L, Storto ML. COVID-19 pneumonia: current evidence of chest imaging features, evolution and prognosis. ACTA ACUST UNITED AC 2021; 4:229-240. [PMID: 33969266 PMCID: PMC8093598 DOI: 10.1007/s42058-021-00068-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 03/05/2021] [Accepted: 04/13/2021] [Indexed: 01/08/2023]
Abstract
COVID-19 pneumonia represents a global threatening disease, especially in severe cases. Chest imaging, with X-ray and high-resolution computed tomography (HRCT), plays an important role in the initial evaluation and follow-up of patients with COVID-19 pneumonia. Chest imaging can also help in assessing disease severity and in predicting patient’s outcome, either as an independent factor or in combination with clinical and laboratory features. This review highlights the current knowledge of imaging features of COVID-19 pneumonia and their temporal evolution over time, and provides recent evidences on the role of chest imaging in the prognostic assessment of the disease.
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Affiliation(s)
- Anna Rita Larici
- Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Rome, Italy.,Department of Diagnostic Imaging, Oncological Radiotherapy, and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy
| | - Giuseppe Cicchetti
- Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Rome, Italy.,Department of Diagnostic Imaging, Oncological Radiotherapy, and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy
| | - Riccardo Marano
- Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Rome, Italy.,Department of Diagnostic Imaging, Oncological Radiotherapy, and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy
| | - Lorenzo Bonomo
- Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Rome, Italy.,Department of Diagnostic Imaging, Oncological Radiotherapy, and Hematology, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy
| | - Maria Luigia Storto
- Bracco Diagnostics Inc., Global Medical and Regulatory Affairs, Monroe Twp, NJ USA
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Severe SARS-CoV-2 pneumonia: Clinical, functional and imaging outcomes at 4 months. Respir Med Res 2021; 80:100822. [PMID: 34242974 PMCID: PMC8080504 DOI: 10.1016/j.resmer.2021.100822] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/27/2021] [Accepted: 04/20/2021] [Indexed: 01/08/2023]
Abstract
Introduction Given the pathophysiology of coronavirus disease 19 (COVID-19), persistent pulmonary abnormalities are likely. Methods We conducted a prospective cohort study in severe COVID-19 patients who had oxygen saturation < 94% and were primarily admitted to hospital. We aimed to describe persistent gas exchange abnormalities at 4 months, defined as decreased diffusing capacity of the lungs for carbon monoxide (DLco) and/or desaturation on the 6-minute walk test (6MWT), along with associated mechanisms and risk factors. Results Of the 72 patients included, 76.1% required admission to an intensive care unit (ICU), while 68.5% required invasive mechanical ventilation (MV). A total of 39.1% developed venous thromboembolism (VTE). After 4 months, 61.4% were still symptomatic. Functionally, 39.1% had abnormal carbon monoxide test results and/or desaturation on 6MWT; high-flow oxygen, MV, and VTE during the acute phase were significantly associated. Restrictive lung disease was observed in 23.6% of cases, obstructive lung disease in 16.7%, and respiratory muscle dysfunction in 18.1%. A severe initial presentation with admission to ICU (P = 0.0181), and VTE occurrence during the acute phase (P = 0.0089) were associated with these abnormalities. 41% had interstitial lung disease in computed tomography (CT) of the chest. Four patients (5.5%) displayed residual defects on lung scintigraphy, only one of whom had developed VTE during the acute phase (5.5%). The main functional respiratory abnormality (31.9%) was reduced capillary volume (Vc < 70%). Conclusion Among patients with severe COVID-19 pneumonia who were admitted to hospital, 61% were still symptomatic, 39% of patients had persistent functional abnormalities and 41% radiological abnormalities after 4 months. Embolic sequelae were rare but the main functional respiratory abnormality was reduced capillary volume. A respiratory check-up after severe COVID-19 pneumonia may be relevant to improve future management of these patients.
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Lago VC, Prudente RA, Luzia DA, Franco ET, Cezare TJ, Peralta A, Ferreira EVM, Albuquerque ALP, Okoshi MP, Baldi BG, Tanni SE. Persistent interstitial lung abnormalities in post-COVID-19 patients: a case series. J Venom Anim Toxins Incl Trop Dis 2021; 27:e20200157. [PMID: 33907556 PMCID: PMC8047717 DOI: 10.1590/1678-9199-jvatitd-2020-0157] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 01/25/2021] [Indexed: 01/08/2023] Open
Abstract
A new concept of multisystem disease has emerged as a long-term condition following mild-severe COVID-19 infection. The main symptoms of this affection are breathlessness, chest pain, and fatigue. We present here the clinical case of four COVID-19 patients during hospitalization and 60 days after hospital discharge. Physiological impairment of all patients was assessed by spirometry, dyspnea score, arterial blood gas, and 6-minute walk test 60 days after hospital discharge, and computed tomographic scan 90 days after discharge. All patients had fatigue, which was not related to hypoxemia or impaired spirometry values, and interstitial lung alterations, which occurred in both mechanically ventilated and non-mechanically ventilated patients. In conclusion, identifying the prevalence and patterns of permanent lung damage is paramount in preventing and treating COVID-19-induced fibrotic lung disease. Additionally, and based on our preliminary results, it will be also relevant to establish long-term outpatient programs for these individuals.
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Affiliation(s)
- Vanessa Carvalho Lago
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Robson Aparecido Prudente
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Dayane Araujo Luzia
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Estefânia Thomé Franco
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Talita Jacon Cezare
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Amanda Peralta
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Eloara Vieira M. Ferreira
- Paulista School of Medicine (EPM), Federal University of São Paulo (Unifesp), São Paulo, SP, Brazil.Paulista School of MedicineFederal University of São PauloSão PauloSPBrazil
| | | | - Marina Politi Okoshi
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
| | - Bruno Guedes Baldi
- Heart Institute (InCor), University of São Paulo (USP), São Paulo, SP, Brazil.University of São PauloSão PauloSPBrazil
| | - Suzana Erico Tanni
- Department of Internal Medicine, Botucatu Medical School (FMB), São Paulo State University (UNESP), Botucatu, SP, Brazil.Department of Internal MedicineBotucatu Medical SchoolSão Paulo State UniversityBotucatuSPBrazil
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Xue M, Zhang T, Chen H, Zeng Y, Lin R, Zhen Y, Li N, Huang Z, Hu H, Zhou L, Wang H, Zhang XD, Sun B. Krebs Von den Lungen-6 as a predictive indicator for the risk of secondary pulmonary fibrosis and its reversibility in COVID-19 patients. Int J Biol Sci 2021; 17:1565-1573. [PMID: 33907520 PMCID: PMC8071769 DOI: 10.7150/ijbs.58825] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 03/14/2021] [Indexed: 12/17/2022] Open
Abstract
Dysregulated immune response and abnormal repairment could cause secondary pulmonary fibrosis of varying severity in COVID-19, especially for the elders. The Krebs Von den Lungen-6 (KL-6) as a sensitive marker reflects the degree of fibrosis and this study will focus on analyzing the evaluative efficacy and predictive role of KL-6 in COVID-19 secondary pulmonary fibrosis. The study lasted more than three months and included total 289 COVID-19 patients who were divided into moderate (n=226) and severe groups (n=63) according to the severity of illness. Clinical information such as inflammation indicators, radiological results and lung function tests were collected. The time points of nucleic acid test were also recorded. Furthermore, based on Chest radiology detection, it was identified that 80 (27.7%) patients developed reversible pulmonary fibrosis and 34 (11.8%) patients developed irreversible pulmonary fibrosis. Receiver operating characteristic (ROC) curve analysis shows that KL-6 could diagnose the severity of COVID-19 (AUC=0.862) and predict the occurrence of pulmonary fibrosis (AUC = 0.741) and irreversible pulmonary fibrosis (AUC=0.872). Importantly, the cross-correlation analysis demonstrates that KL-6 rises earlier than the development of lung radiology fibrosis, thus also illuminating the predictive function of KL-6. We set specific values (505U/mL and 674U/mL) for KL-6 in order to assess the risk of pulmonary fibrosis after SARS-CoV-2 infection. The survival curves for days in hospital show that the higher the KL-6 levels, the longer the hospital stay (P<0.0001). In conclusion, KL-6 could be used as an important predictor to evaluate the secondary pulmonary fibrosis degree for COVID-19.
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Affiliation(s)
- Mingshan Xue
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Teng Zhang
- Faculty of Health Sciences, University of Macau. Taipa, Macau, China
| | - Hao Chen
- Department of Allergy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yifeng Zeng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Runpei Lin
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Yingjie Zhen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Ning Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Zhifeng Huang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Haisheng Hu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Luqian Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
| | - Hui Wang
- Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
| | | | - Baoqing Sun
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China
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Li J, Long X, Zhang Q, Fang X, Li N, Fedorova B, Hu S, Li J, Xiong N, Lin Z. Tobacco smoking confers risk for severe COVID-19 unexplainable by pulmonary imaging. J Intern Med 2021; 289:574-583. [PMID: 33270312 PMCID: PMC7753648 DOI: 10.1111/joim.13190] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND COVID-19 is a new pneumonia. It has been hypothesized that tobacco smoking history may increase severity of this disease in the patients once infected by the underlying coronavirus SARS-CoV-2 because smoking and COVID-19 both cause lung damage. However, this hypothesis has not been tested. OBJECTIVE Current study was designed to focus on smoking history in patients with COVID-19 and test this hypothesis that tobacco smoking history increases risk for severe COVID-19 by damaging the lungs. METHODS AND RESULTS This was a single-site, retrospective case series study of clinical associations, between epidemiological findings and clinical manifestations, radiographical or laboratory results. In our well-characterized cohort of 954 patients including 56 with tobacco smoking history, smoking history increased the risk for severe COVID-19 with an odds ratio (OR) of 5.5 (95% CI: 3.1-9.9; P = 7.3 × 10-8 ). Meta-analysis of ten cohorts for 2891 patients together obtained an OR of 2.5 (95% CI: 1.9-3.3; P < 0.00001). Semi-quantitative analysis of lung images for each of five lobes revealed a significant difference in neither lung damage at first examination nor dynamics of the lung damage at different time-points of examinations between the smoking and nonsmoking groups. No significant differences were found either in laboratory results including D-dimer and C-reactive protein levels except different covariances for density of the immune cells lymphocyte (P = 3.8 × 10-64 ) and neutrophil (P = 3.9 × 10-46 ). CONCLUSION Tobacco smoking history increases the risk for great severity of COVID-19 but this risk is achieved unlikely by affecting the lungs.
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Affiliation(s)
- J. Li
- From theMedical Treatment Expert Group for COVID‐19Wuhan Red Cross HospitalWuhanHubeiChina
- Department of NeurologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina
| | - X. Long
- Department of RadiologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina
| | - Q. Zhang
- From theMedical Treatment Expert Group for COVID‐19Wuhan Red Cross HospitalWuhanHubeiChina
| | - X. Fang
- From theMedical Treatment Expert Group for COVID‐19Wuhan Red Cross HospitalWuhanHubeiChina
| | - N. Li
- From theMedical Treatment Expert Group for COVID‐19Wuhan Red Cross HospitalWuhanHubeiChina
| | - B. Fedorova
- Department of Emergency MedicineSana‐Klinikum OffenbachHessenGermany
| | - S. Hu
- Department of RadiologyWuhan Red Cross HospitalWuhanHubeiChina
| | - Jh. Li
- Department of MedicineUniversity of California San DiegoLa JollaCAUSA
| | - N. Xiong
- From theMedical Treatment Expert Group for COVID‐19Wuhan Red Cross HospitalWuhanHubeiChina
- Department of NeurologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubeiChina
| | - Z. Lin
- McLean HospitalHarvard Medical SchoolBelmontMAUSA
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45
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Agnello F, Rabiolo L, Grassedonio E, Toia P, Midiri F, Spatafora L, Matteini F, Tesè L, La Grutta L, Galia M. Imaging the COVID-19: a practical guide. Monaldi Arch Chest Dis 2021. [PMID: 33794596 DOI: 10.4081/monaldi.2021.1630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 01/17/2021] [Indexed: 01/08/2023] Open
Abstract
The Coronavirus Disease 2019 (COVID-19) represents the first medical catastrophe of the new millennium. Although imaging is not a screening test for COVID-19, it plays a crucial role in evaluation and follow-up of COVID-19 patients. In this paper, we will review typical and atypical imaging findings of COVID-19.
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Affiliation(s)
- Francesco Agnello
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | - Lidia Rabiolo
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | | | - Patrizia Toia
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | - Federico Midiri
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | | | - Francesco Matteini
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | - Lorenzo Tesè
- Department of Radiology, Azienda Ospedali Riuniti Villa Sofia-Cervello, Palermo.
| | - Ludovico La Grutta
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
| | - Massimo Galia
- Department of Radiology, Policlinico "Paolo Giaccone", University of Palermo.
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Gurumurthy B, Das SK, Hiremath R, Shetty S, Hiremath A, Gowda T. Spectrum of atypical pulmonary manifestations of COVID-19 on computed tomography. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [PMCID: PMC7930897 DOI: 10.1186/s43055-021-00448-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Background The typical CT manifestations of COVID-19 pneumonia include ground-glass opacity (GGO) with or without consolidation and superimposed interlobular septal thickening. These are often rounded in morphology and frequently bilateral, multilobar, posterior, peripheral, and basilar in distribution. The various atypical CT features of COVID-19 are seldom described in the literature. The study aims to enumerate the atypical pulmonary CT features in patients with COVID-19 pneumonia in correlation with the disease severity. Results A total of 298 confirmed cases of COVID-19 pneumonia with positive reverse transcription polymerase chain reaction (RT-PCR) who underwent chest CT scans were retrospectively evaluated. The cohort included 234 (78.5%) men and 64 (21.5%) women and the mean age was 53.48 ± 15.74 years. The most common presenting symptoms were fever [n = 197 (66.1%)] and cough [n = 139 (46.6%)]. Out of 298 cases of COVID-19 pneumonia, 218 cases (73.1%) showed typical CT features while 63 cases (21.1%) showed atypical CT features with concurrent classical findings and the remaining 17 cases (5.8%) were normal. Among the atypical CT features, the most common was pulmonary cysts [n = 27 (9%)]. The other features in the order of frequency included pleural effusion [n = 17 (5.7%)], nodules [n = 13 (4.3%)], bull’s eye/target sign[n = 4 (1.3%)], cavitation [n = 3 (1.0%)], spontaneous pneumothorax [n = 2 (0.6%)], hilar lymphadenopathy [n = 2 (0.6%)], spontaneous pneumo-mediastinum with subcutaneous emphysema [n = 1 (0.3%)], Halo sign [n = 1 (0.3%)], empyema [n = 1 (0.3%)] and necrotizing pneumonia with abscess [n = 1 (0.3%)]. Conclusion CT imaging features of COVID-19 pneumonia while in a vast majority of cases is classical, atypical diverse patterns are also encountered. A comprehensive knowledge of various atypical presentations on imaging plays an important role in the early diagnosis and management of COVID-19.
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Rafiee F, Keshavarz P, Katal S, Assadi M, Nejati SF, Ebrahimian Sadabad F, Gholamrezanezhad A. Coronavirus Disease 2019 (COVID-19) in Molecular Imaging: A Systematic Review of Incidental Detection of SARS-CoV-2 Pneumonia on PET Studies. Semin Nucl Med 2021; 51:178-191. [PMID: 33509374 PMCID: PMC7598766 DOI: 10.1053/j.semnuclmed.2020.10.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
There have been several reports of the incidental detection of severe acute respiratory syndrome coronavirus 2 pneumonia on positron emission tomography/computed tomography (PET/CT) studies, which represent the potential role of molecular imaging in the detection and management of coronavirus disease 2019. Here, we systematically review the value of PET/CT in this setting. We conducted a systematic search on June 23, 2020, for PET studies with findings suggestive of coronavirus disease 2019. Web of Science, PubMed, Scopus, EMBASE, and Google Scholar databases were used. Patients with at least one PET/CT imaging evaluation were included in the study. Fifty-two patients in 30 publications with a mean age of 60 ± 12.74 (age range; 27-87) were included in this study, of which 28 (53.8%) were male, and 19 (36.5%) were female. In 5 (9.7%) patients, gender was not reported. PET/CT was performed with 18F-fluorodeoxyglucose for 48 (92.3%), 18F-choline for 3 (5.8%), and 68Ga-PSMA for 1 (1.9%) patients. The mean SUV max of pulmonary lesions with 18F-fluorodeoxyglucose uptake was 4.9 ± 2.3. Moreover, 39 (75%) cases had an underlying malignancy, including 18 different type of primary cancers and 6 (11.5%) patients with metastatic disease. The most common pulmonary findings in PET/CT were bilateral hypermetabolic ground-glass opacities in 39 (75%), consolidation in 18 (34.6%), and interlobular thickening in 4 (7.6%). In addition, mediastinal 14 (27%) and hilar 10 (19.2%) lymph node involvement with increased metabolic activity was frequently identified. Early diagnosis of severe acute respiratory syndrome coronavirus 2 pneumonia is not only crucial for both appropriate patient management but also helps to ensure appropriate postexposure precautions are implemented for the department and hospital staff and those who have been in contact with the patient.
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Affiliation(s)
- Faranak Rafiee
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Pedram Keshavarz
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran; Department of Radiology, Tbilisi State Medical University (TSMU), Tbilisi, Georgia
| | - Sanaz Katal
- Department of Nuclear Medicine/PET-CT, Kowsar Hospital, Shiraz, Iran
| | - Majid Assadi
- Department of Molecular Imaging and Radionuclide Therapy (MIRT), The Persian Gulf Nuclear Medicine Research Center, Bushehr Medical University Hospital, School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Seyed Faraz Nejati
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Faranak Ebrahimian Sadabad
- Department of Radiology, Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Sothern California (USC), Los Angeles, CA.
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48
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Chattopadhyay S, Dey A, Singh PK, Geem ZW, Sarkar R. COVID-19 Detection by Optimizing Deep Residual Features with Improved Clustering-Based Golden Ratio Optimizer. Diagnostics (Basel) 2021; 11:diagnostics11020315. [PMID: 33671992 PMCID: PMC7919377 DOI: 10.3390/diagnostics11020315] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/28/2021] [Accepted: 02/09/2021] [Indexed: 12/11/2022] Open
Abstract
The COVID-19 virus is spreading across the world very rapidly. The World Health Organization (WHO) declared it a global pandemic on 11 March 2020. Early detection of this virus is necessary because of the unavailability of any specific drug. The researchers have developed different techniques for COVID-19 detection, but only a few of them have achieved satisfactory results. There are three ways for COVID-19 detection to date, those are real-time reverse transcription-polymerize chain reaction (RT-PCR), Computed Tomography (CT), and X-ray plays. In this work, we have proposed a less expensive computational model for automatic COVID-19 detection from Chest X-ray and CT-scan images. Our paper has a two-fold contribution. Initially, we have extracted deep features from the image dataset and then introduced a completely novel meta-heuristic feature selection approach, named Clustering-based Golden Ratio Optimizer (CGRO). The model has been implemented on three publicly available datasets, namely the COVID CT-dataset, SARS-Cov-2 dataset, and Chest X-Ray dataset, and attained state-of-the-art accuracies of 99.31%, 98.65%, and 99.44%, respectively.
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Affiliation(s)
- Soham Chattopadhyay
- Department of Electrical Engineering, Jadavpur University, Kolkata 700032, India;
| | - Arijit Dey
- Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Simhat, Haringhata, Nadia 741249, India;
| | - Pawan Kumar Singh
- Department of Information Technology, Jadavpur University, Kolkata 700106, India;
| | - Zong Woo Geem
- College of IT Convergence, Gachon University, 1342 Seongnam Daero, Seongnam 13120, Korea
- Correspondence:
| | - Ram Sarkar
- Department of Computer Science and Engineering, Jadavpur University, Kolkata 700032, India;
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49
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Incidence and clinical outcome of Coronavirus disease 2019 in a cohort of 11,560 Brazilian patients with multiple sclerosis. Mult Scler 2021:1352458520978354. [PMID: 33528295 DOI: 10.1177/1352458520978354] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Little information is available regarding the incidence and clinical outcome of the SARS-CoV2 infection in patients with multiple sclerosis (pwMS). OBJECTIVE To determine the incidence, clinical outcome, and impact of COVID-19 on pwMS. METHODS This observational study was prospectively performed on a cohort of pwMS (N = 11,560) followed up by 47 out of 51 Brazilian MS referral centers that registered pwMS with COVID-19 at the REDONE platform from 13 March to 4 June 2020. RESULTS The incidence of COVID-19 for pwMS patients was 27.7/10,000 patients and for the general population was 29.2/10,000 inhabitants. A total of 94 (77 women) pwMS patients, aged 40 ± 10.25 years, presenting 9.9 ± 8.6 years of MS disease duration, developed the COVID-19, most of them (87%) exhibited the mild form of the disease. Eighty (96%) patients maintained the use of MS disease-modifying treatment (DMT) during COVID-19 pandemic and 14 patients were not in use of DMTs. CONCLUSION Incidence of COVID-19 in Brazilian pwMS was not different from those observed for the general Brazilian population. Most pwMS exhibited mild COVID-19, despite the maintenance of the underlying MS treatment.
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50
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Rona G, Arifoğlu M, Voyvoda N, Batırel A. Should CT be used for the diagnosis of RT-PCR-negative suspected COVID-19 patients? CLINICAL RESPIRATORY JOURNAL 2021; 15:491-498. [PMID: 33484085 PMCID: PMC8014557 DOI: 10.1111/crj.13332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 01/19/2021] [Indexed: 01/08/2023]
Abstract
Introduction The diagnosis of patients with Coronavirus disease 2019 (COVID‐19) suspicion but negative reverse transcriptase‐polymerase chain reaction (RT‐PCR) test is challenging. Objective We aimed to investigate the diagnostic value of chest computed tomography (CT) in RT‐PCR‐negative patients with suspected COVID‐19. Materials and methods The study included patients who were admitted to our hospital with the suspicion of COVID‐19 between 1 April 2020 and 30 April 2020 and tested negative after RT‐PCR test, and underwent CT for further diagnosis. Initial CT findings were classified as typical, indeterminate, and atypical for COVID‐19, and negative for pneumonia. Incidental findings on CT were noted. Results Of the 338 patients with a mean age of 57 years (min 18 years–max 96 years), 168 (49.70%) were male and 170 (50.29%) were female. The most common symptoms were cough (58.87%), fever (40.82%), and dyspnea (39.34%). The CT findings were typical for COVID‐19 in 109 (32.24%) patients, indeterminate in 47 (13.90%) patients, and atypical in 77 (22.78%) patients. The CT findings of 105 (31.06%) patients were negative for pneumonia. Incidental lung nodules suspicious of malignancy were identified in seven patients. Seventy‐seven patients (22.78%) had extrapulmonary incidental findings Conclusion The diagnostic value of CT in RT‐PCR‐negative patients with suspected COVID‐19 is not very high. Based on clinical, laboratory, and chest x‐ray findings, it may be more appropriate to refer patients to CT after the first triage, when necessary.
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Affiliation(s)
- Günay Rona
- Department of Radiology, University of Health Sciences, Kartal Doktor Lütfi Kırdar Training and Research Hospital, İstanbul, Turkey
| | - Meral Arifoğlu
- Department of Radiology, University of Health Sciences, Kartal Doktor Lütfi Kırdar Training and Research Hospital, İstanbul, Turkey
| | - Nuray Voyvoda
- Department of Radiology, University of Health Sciences, Kartal Doktor Lütfi Kırdar Training and Research Hospital, İstanbul, Turkey
| | - Ayşe Batırel
- Department of Infectious Diseases, University of Health Sciences, Kartal Doktor Lütfi Kırdar Training and Research Hospital, İstanbul, Turkey
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