Lung damage in post-acute COVID-19 is a common clinical finding. Lung water density (LWD) imaging using ultrashort echo time (UTE) MRI with proton-density weighting is sensitive to edema and fibrosis.

To characterize LWD in COVID-19 survivors, compared with a healthy cohort.

Retrospective cohort.

185 COVID-19 survivors (63 male; age [median (interquartile range, IQR)]: 51 (25-83) years; 160 (66-363) days from COVID-19 infection to MRI) and 109 healthy controls (64 male; age: 52 (27-76) years) with no history of COVID-19 infection.

2.89T; Yarnball UTE pulse sequence.

Free-breathing three-dimensional LWD images were acquired in both cohorts. Clinical demographics (age, sex, body mass index [BMI]), presence of comorbidities (hypertension, dyslipidemia, diabetes, obesity), COVID-19 hospitalization, pulmonary function, six-minute walking distance, and plasma biomarkers were recorded.

Student's t-tests or Mann-Whitney U tests were used to compare lung water metrics between cohorts. The effect of comorbidities was assessed using Kruskal-Wallis tests followed by pairwise Wilcoxon tests with Bonferroni correction. Categorical variables were compared using chi-squared tests. p < 0.05 was considered significant.

LWD (median (IQR)), was significantly greater in the post-COVID-19 cohort than in the healthy cohort, 31.3 (6.6)% versus 27.9 (6.5)% in men and 30.3 (7.4)% versus 27.5 (4.9)% in women. 37% of men and 24% of women in the post-COVID-19 cohort had LWD above the healthy cohort 95% confidence limit. Participants with elevated LWD had significantly higher BMI (kg/m2) (32 (5) versus 26 (4) in men, 33 (9) versus 26 (7) in women), incidence of comorbidities (78% vs. 50% in men, 72% vs. 38% in women), rates of COVID-19 hospitalization (52% vs. 23% in men, 38% vs. 18% in women), and elevated CRP (mg/L) (2.2 (3.4) vs. 1.1 (1.4) in men, 1.8 (4.2) vs. 1.2 (2.1) in women).

MRI-derived LWD is elevated in COVID-19 survivors and is related to high BMI, COVID-19 hospitalization, inflammatory plasma biomarkers, and the presence of comorbidities.

2.

Stage 3.

Coronavirus disease 2019 (COVID-19) have posed a great threat to human health. We carried out this systematic review and meta-analysis for two objectives. First, to evaluate the differences in lung infection between the Omicron variants and the non-Omicron strains by chest computed tomography (CT); second, to evaluate the differences in chest CT features between COVID-19 patients with the Omicron variants and those with non-Omicron strains in CT-positive cases.

We searched PubMed, Embase, Web of Science and China National Knowledge Infrastructure for articles and performed a meta-analysis using Stata 14.0 with a random effects model.

Our study included a total of 8126 patients with COVID-19, 4113 with the Omicron variants, and 4013 with non-Omicron strains. Patients with the Omicron variants were less likely to be CT-positive (OR = 0.14, 95% CI: 0.08-0.25), and further analysis among CT-positive patients was performed. Compared with the CT images of patients with non-Omicron strains, those of patients with the Omicron variants showed atypical pulmonary features (OR = 4.02, 95% CI: 2.31-6.98). Moreover, patients with the Omicron variants typically had lesions that were mainly located in the center of the lung (OR = 4.51, 95% CI: 1.38-14.76) and in a single lobe (OR = 1.72, 95% CI: 1.10-2.70). The patients with the Omicron variants were less likely to have lesions in both lungs (OR = 0.33, 95% CI: 0.15-0.69), more likely to have bronchial wall thickening (OR = 1.99, 95% CI: 1.05-3.77) and less likely to have the crazy-paving pattern (OR = 0.51, 95% CI: 0.33-0.81), linear opacity (OR = 0.26, 95% CI: 0.12-0.60), and vascular enlargement (OR = 0.54, 95% CI: 0.35-0.84).

Through meta-analysis, which yields the highest level of evidence for evidence-based medicine, we further confirmed that there were significant differences in the distribution and manifestations of lesions between patients with non-Omicron strains and those with the Omicron variants on chest CT. The variation in SARS-CoV-2 has never stopped. Our findings are useful for the diagnosis and treatment of new SARS-CoV-2 variants that may appear in the future and provide a basis for public health decision-making.

CRD42024581869.

Early in the COVID-19 pandemic, CT was demonstrated as a sensitive tool for diagnosing COVID-19. We undertook a detailed study of CT scans in COVID-19 patients to characterise disease distribution within lung parenchyma, respiratory airways, and pulmonary vasculature, aiming to delineate underlying disease processes.

We characterised acute phase chest CT of 40 participants with COVID-19 from the REACT study, 31 with CT pulmonary angiography (CTPA), 4 with intravenous contrast enhanced CT and 5 with non-intravenous contrast enhanced CT. Participants had neither been vaccinated nor received systemic steroids. We further correlated the distribution of lung parenchymal damage on CT with contemporaneous chest radiographs.

Parenchymal lung damage was found in all subjects. However, airways inflammation was present in only 23% (9) and limited to small areas. Notably, vascular abnormalities were dominant and characterised by dilated peripheral pulmonary vessels supplying areas of lung damage in a gravity-dependent distribution bilaterally in 95% (38), basally in 90% (36), peripherally in 92.5% (37), and posteriorly in 90% (36). Macrothrombosis was demonstrated in 23% (7) of CTPAs. Wedge-shaped peripheral lung damage, resembling areas of pulmonary vascular congestion, were distinct in 53% (21) with or without visible macrothrombosis. Pleural effusions were seen in 28% (11). Notably, lung opacification distribution in 98% of the plain radiographs matched distribution on CT (39).

Our study frames COVID-19 as a pulmonary vasculopathy rather than a more conventional pneumonia which may be important not only for guiding mechanistic study design but also for the development of novel targeted therapeutics.

Long coronavirus disease 2019 (COVID-19)-a postacute consequence of severe acute respiratory syndrome coronavirus 2 infection-manifests with a broad spectrum of relapsing and remitting or persistent symptoms as well as varied levels of organ damage, which may be asymptomatic or present as acute events such as heart attacks or strokes and recurrent infections, hinting at complex underlying pathogenic mechanisms. Central to these symptoms is vascular dysfunction rooted in thrombotic endothelialitis. We review the scientific evidence that widespread endothelial dysfunction (ED) leads to chronic symptomatology. We briefly examine the molecular pathways contributing to endothelial pathology and provide a detailed analysis of how these cellular processes underpin the clinical picture. Noninvasive diagnostic techniques, such as flow-mediated dilation and peripheral arterial tonometry, are evaluated for their utility in identifying ED. We then explore mechanistic, cellular-targeted therapeutic interventions for their potential in treating ED. Overall, we emphasize the critical role of cellular health in managing Long COVID and highlight the need for early intervention to prevent long-term vascular and cellular dysfunction.

Computed tomography (CT) is a critical tool for the diagnosis of pneumonia caused by SARS-CoV-2. The Delta and Omicron variants show distinct clinical features, but the radiological differences between pneumonia caused by these variants have not been extensively studied in patients with oxygen-dependent pneumonia.

To compare the radiological and clinical features of pneumonia in patients hospitalized with oxygen-dependent SARS-CoV-2 infection caused by the Delta and Omicron variants.

We performed a retrospective single-center study, including patients hospitalized with oxygen-dependent SARS-CoV-2 pneumonia between October 2021 and February 2022. Clinical and radiological data were collected and compared between patients infected with the Delta variant and those with the Omicron variant. CT scans were reviewed by a radiologist and a pulmonologist blinded to clinical and variant information.

A total of 135 patients with the Delta variant and 48 with the Omicron variant were included. Patients infected with Omicron were older (median age 75 years [68-83.2] vs 69 years [62-77.5], p = 0.004), more immunocompromised (52 % vs. 25 %, p < 0.001), and had higher vaccination rates (73 % vs. 51 %, p = 0.009). Radiologically, ground-glass opacities were present in 95 % of patients. There were no significant differences in the degree of lung involvement, type of lesions and their predominance. Unilateral lung involvement was more common in Omicron-infected patients (8.3 % vs 0.74 %, p = 0.02).

While Omicron oxygen-dependent pneumonia occurred in older and more comorbid patients, its clinical and radiological features were largely indistinguishable from those caused by the Delta variant, except for a higher rate of unilateral lung involvement.

One of the primary concerns regarding COVID-19 vaccination programs is the emergence of new virus variants and the effectiveness of the currently available vaccines against these variants. The main objective of this study was to evaluate the effectiveness of the system of vaccination of COVID-19 in Iran in preventing hospitalization, severe illness, critical illness, and death in relation to the Omicron BA.2 variant of SARS-CoV-2. The study focused on assessing vaccine effectiveness regardless of the specific vaccine administered in the community and also investigated the potential improvement in effectiveness after receiving the second dose or subsequent doses of the vaccine. The study specifically examined two age groups including individuals aged 65 years and older and individuals younger than 65 years. This study was performed using case-population method provided by World Health Organization (WHO). To conduct the study, data on vaccination coverage and vaccination status within the community were obtained from the data center of the Public Health Service in the Tehran province, Iran. Additionally, data on hospitalization, critical illness, and death related to COVID-19 were collected from hospitals in Tehran during the period when the Omicron Ba.2 variant was dominant in Iran. The results of the study indicated that vaccination with the available vaccines was effective in preventing severe illness, critical illness, and death resulting from infection with the Omicron variant in both age groups. This study found that completing the vaccination regimen was more effective in preventing adverse outcomes associated with the Omicron variant in elderly individuals compared to younger individuals.

Coronavirus disease 2019 (COVID-19) pneumonia has had catastrophic effects worldwide. Radiology, in particular computed tomography (CT) imaging, has proven to be valuable in the diagnosis, prognostication, and longitudinal assessment of those diagnosed with COVID-19 pneumonia. This article will review acute and chronic pulmonary radiologic manifestations of COVID-19 pneumonia with an emphasis on CT and also highlighting histopathology, relevant clinical details, and some notable challenges when interpreting the literature.

Introduction This study aimed to determine the characteristics of coronavirus disease 2019 (COVID-19) pneumonia caused by the wild type and the alpha variant in patients. This study included patients with COVID-19 admitted to Fukui General Hospital between October 31, 2020, and April 30, 2021. Methods Pneumonia occurrence rate, chest X-ray, and computed tomography (CT) findings were evaluated by two radiologists. The time since the onset and presence of pneumonia were also investigated. Results Out of 128 patients, 43 had pneumonia. The pneumonia detection rates using chest radiography were 15.6% (20/128) and 33.6% (43/128) using CT (p = 0.0008). Of the pneumonia cases detected by CT, 32.0% (8/25) of the wild type and 66.7% (12/18) of the alpha variant were detected by X-rays (p = 0.0246). The main finding of pneumonia was a higher percentage of ground-glass opacities than consolidation in both the wild type and alpha variant. In the alpha variant, multiple signs of air bubbles were observed in four patients on chest CT; however, these were not observed in the wild type (p = 0.014). Conclusion The imaging features of pneumonia may be different in variants of COVID-19 compared to those in the wild type. CT helps to detect pneumonia and identify features in patients with COVID-19 because it is difficult to detect COVID-19 pneumonia using plain chest radiographs.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, fast-spreading, and insidious. Most patients present with normal findings on lung computed tomography (CT). The current study aimed to develop and validate a tracheal CT radiomics model to predict Omicron variant infection.

In this retrospective study, a radiomics model was developed based on a training set consisting of 157 patients with an Omicron variant infection and 239 healthy controls between 1 January and 30 April 2022. A set of morphological expansions, with dilations of 1, 3, 5, 7, and 9 voxels, was applied to the trachea, and radiomic features were extracted from different dilation voxels of the trachea. Logistic regression (LR), support vector machines (SVM), and random forests (RF) were developed and evaluated; the models were validated on 67 patients with the Omicron variant and on 103 healthy controls between 1 May and 30 July 2022.

Logistic regression with 12 radiomic features extracted from the tracheal wall with dilation of 5 voxels achieved the highest classification performance compared with the other models. The LR model achieved an area under the curve of 0.993 (95% confidence interval [CI]: 0.987-0.998) in the training set and 0.989 (95% CI: 0.979-0.999) in the validation set. Sensitivity, specificity, and accuracy of the model for the training set were 0.994, 0.946, and 0.965, respectively, whereas those for the validation set were 0.970, 0.952, and 0.959, respectively.

The tracheal CT radiomics model reliably identified the Omicron variant of SARS-CoV‑2, and may help in clinical decision-making in future, especially in cases of normal lung CT findings.

Background The post-pandemic phase of the coronavirus infectious disease that emerged in 2019 (COVID-19) has necessitated updates in radiology, with emerging evidence suggesting tracheobronchial wall thickness as a potential new diagnostic marker. Purpose To evaluate the accuracy of chest computed tomography (CT) scans in identifying COVID-19 by assessing tracheobronchial wall thickness in mid-2023. Material and methods A retrospective review was conducted on 60 patients who underwent thoracoabdominal CT and the severe acute respiratory syndrome coronavirus (SARS-CoV-2) antigen tests during emergency visits between June and August 2023. Tracheobronchial wall thickness was measured using a 4-point scale (1=no thickening, 2=mild, 3=moderate, 4=significant). Lung assessment employed the COVID-19 Reporting and Data System (CO-RADS). Patients were classified based on antigen test results. The Mann-Whitney U test and Fisher's exact test compared characteristics and CT findings. Diagnostic performance was evaluated using the area under the receiver operating characteristic curves (AUC). Results The SARS-CoV-2-positive group showed significantly thicker tracheobronchial walls (median 1.5 mm vs. 1.2 mm, P < 0.001), especially in the trachea's membranous wall (median 1.2 mm vs. 0.9 mm, P < 0.001) and higher scores (median 3 vs. 2, P < 0.001). CO-RADS scores showed no significant difference. Quantitative and qualitative wall thickness assessments demonstrated high diagnostic value, with AUCs of 0.90 and 0.94, and accuracies of 85% and 87%, respectively. Conclusion Tracheobronchial wall thickness on chest CT exhibited high diagnostic accuracy, establishing it as a reliable marker for COVID-19 detection in mid-2023.

To explore the relationship between the timing of non-emergency surgery in mild or asymptomatic SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infected individuals and the quality of postoperative recovery from the time of confirmed infection to the day of surgery.

We retrospectively reviewed the medical records of 300 cases of mild or asymptomatic SARS-CoV-2 infected patients undergoing elective general anaesthesia surgery at Yijishan Hospital between January 9, 2023, and February 17, 2023. Based on the time from confirmed SARS-CoV-2 infection to the day of surgery, patients were divided into four groups: ≤2 weeks (Group A), 2-4 weeks (Group B), 4-6 weeks (Group C), and 6-8 weeks (Group D). The primary outcome measures included the Quality of Recovery-15 (QoR-15) scale scores at 3 days, 3 months, and 6 months postoperatively. Secondary outcome measures included postoperative mortality, ICU admission, pulmonary complications, postoperative length of hospital stay, extubation time, and time to leave the PACU.

Concerning the primary outcome measures, the QoR-15 scores at 3 days postoperatively in Group A were significantly lower compared to the other three groups (P < 0.05), while there were no statistically significant differences among the other three groups (P > 0.05). The QoR-15 scores at 3 and 6 months postoperatively showed no statistically significant differences among the four groups (P > 0.05). In terms of secondary outcome measures, Group A had a significantly prolonged hospital stay compared to the other three groups (P < 0.05), while other outcome measures showed no statistically significant differences (P > 0.05).

The timing of surgery in mild or asymptomatic SARS-CoV-2 infected patients does not affect long-term recovery quality but does impact short-term recovery quality, especially for elective general anaesthesia surgeries within 2 weeks of confirmed infection. Therefore, it is recommended to wait for a surgical timing of at least greater than 2 weeks to improve short-term recovery quality and enhance patient prognosis.

To identify clinical characteristics and risk factors for pulmonary involvements in asymptomatic and mildly symptomatic patients infected with SARS-CoV-2 Omicron variant by chest imaging analysis.

Detailed data and chest computed tomography (CT) imaging features were retrospectively analyzed from asymptomatic and mildly symptomatic patients infected with Omicron between 24 April and 10 May 2022. We scored chest CT imaging features and categorized the patients into obvious pulmonary involvements (OPI) (score > 2) and not obvious pulmonary involvements (NOPI) (score ≤ 2) groups based on the median score. The risk factors for OPI were identified with analysis results visualized by nomogram.

In total, 339 patients were included (145 were male and 194 were female), and the most frequent clinical symptoms were cough (75.5%); chest CT imaging features were mostly linear opacities (42.8%). Pulmonary involvements were more likely to be found in the left lower lung lobe, with a significant difference in the lung total severity score of the individual lung lobes (p < 0.001). Logistic regression analysis revealed age stratification [odds ratio (OR) = 1.92, 95% confidence interval (CI) (1.548-2.383); p < 0.001], prolonged nucleic acid negative conversion time (NCT) (NCT > 8d) [OR = 1.842, 95% CI (1.104-3.073); p = 0.019], and pulmonary diseases [OR = 4.698, 95% CI (1.159-19.048); p = 0.03] as independent OPI risk factors.

Asymptomatic and mildly symptomatic patients infected with Omicron had pulmonary involvements which were not uncommon. Potential risk factors for age stratification, prolonged NCT, and pulmonary diseases can help clinicians to identify OPI in asymptomatic and mildly symptomatic patients infected with Omicron.

Coronavirus disease 2019 (COVID-19) pneumonia has had catastrophic effects worldwide. Radiology, in particular computed tomography (CT) imaging, has proven to be valuable in the diagnosis, prognostication, and longitudinal assessment of those diagnosed with COVID-19 pneumonia. This article will review acute and chronic pulmonary radiologic manifestations of COVID-19 pneumonia with an emphasis on CT and also highlighting histopathology, relevant clinical details, and some notable challenges when interpreting the literature.

Understanding COVID-19 outcomes remains a challenge. While numerous biomarkers have been proposed for severity at admission, limited exploration exists for markers during the infection course, especially for the requirement of oxygen therapy. This study investigates the potential of eosinophil count normalization as a predictor for oxygen weaning during the initial wave of the pandemic.

A retrospective study was conducted between March and April 2020 (first wave) among adults admitted directly to a medicine ward. Biological abnormalities, including lymphocyte count, eosinophil count, and C-reactive protein (CRP), were gathered daily during the first week of admission according to oxygen level. In case of worsening, oxygen level was censored at 15 L/min. The primary aim was to assess whether eosinophil count normalization predicts a subsequent decrease in oxygen requirements.

Overall, 132 patients were admitted, with a mean age of 59.0 ± 16.3 years. Of the patients, 72% required oxygen, and 20.5% were admitted to the intensive care unit after a median delay of 48 hours. The median CRP at admission was 79 (26-130) mg/L, whereas the eosinophil count was 10 (0-60)/mm3. Eosinophil count normalization (≥100/mm3) by day 2 correlated significantly with decreased oxygen needs (<2 L) with hazard ratio (HR) = 3.7 [1.1-12.9] (p = 0.04). Likewise, CRP < 80 mg/L was associated with reduced oxygen requirements (p < 0.001). Predictors, including underlying chronic respiratory disease, exhibited a trend toward a negative association (p = 0.06).

The study highlights the relationship between eosinophil count and CRP, with implications for predicting oxygen weaning during COVID-19. Further research is warranted to explore the relevance of these biomarkers in other respiratory infections.

Background/Objectives: Coronavirus disease 2019 (COVID-19) course may differ among individuals-in particular, those with comorbidities may have severe pneumonia, requiring oxygen supplementation or mechanical ventilation. Post-COVID-19 long-term structural changes in imaging studies can contribute to persistent respiratory disturbance. This study aimed to investigate COVID-19 sequels affecting the possibility of persistent structural lung tissue abnormalities and their influence on the respiratory function of peripheral airways and gas transfer. Methods: Patients were divided into two groups according to severity grades described by the World Health Organization. Among the 176 hospitalized patients were 154 patients with mask oxygen supplementation and 22 patients with high-flow nasal cannula (HFNC) or mechanical ventilation. All tests were performed at 3, 6, and 9 months post-hospitalization. Results: Patients in the severe/critical group had lower lung volumes in FVC, FVC%, FEV1, FEV1%, LC, TLC%, and DLCO% at three months post-hospitalization. At 6 and 9 months, neither group had significant FVC and FEV1 value improvements. The MEF 25-75 values were not significantly higher in the mild/moderate group than in the severe/critical group at three months. There were weak significant correlations between FVC and FEV1, MEF50, MEF 75, plethysmography TLC, disturbances in DLCO, and total CT abnormalities in the severe/critical group at three months. In a mild/moderate group, there was a significant negative correlation between the spirometry, plethysmography parameters, and CT lesions in all periods. Conclusions: Persistent respiratory symptoms post-COVID-19 can result from fibrotic lung parenchyma and post-infectious stenotic small airway changes not visible in CT, probably due to persistent inflammation.

To investigate changes in chest CT between 3 and 12 months and associations with disease severity in patients hospitalized for COVID-19 during the first wave in 2020.

Longitudinal cohort study of patients hospitalized for COVID-19 in 2020. Chest CT was performed 3 and 12 months after admission. CT images were evaluated using a CT severity score (CSS) (0-12 scale) and recoded to an abbreviated version (0-3 scale). We analyzed determinants of the abbreviated CSS with multivariable mixed effects ordinal regression.

242 patients completed CT at 3 months, and 124 (mean age 62.3±13.3, 78 men) also at 12 months. Between 3 and 12 months (n = 124) CSS (0-12 scale) for ground-glass opacities (GGO) decreased from median 3 (25th-75th percentile: 0-12) at 3 months to 0.5 (0-12) at 12 months (p<0.001), but increased for parenchymal bands (p<0.001). In multivariable analysis of GGO, the odds ratio for more severe abbreviated CSS (0-3 scale) at 12 months was 0.11 (95%CI 0.11 0.05 to 0.21, p<0.001) compared to 3 months, for WHO severity category 5-7 (high-flow oxygen/non-invasive ventilation/ventilator) versus 3 (non-oxygen use) 37.16 (1.18 to 43.47, p = 0.032), and for age ≥60 compared to <60 years 4.8 (1.33 to 17.6, p = 0.016). Mosaicism was reduced at 12 compared to 3 months, OR 0.33 (95%CI 0.16 to 0.66, p = 0.002).

GGO and mosaicism decreased, while parenchymal bands increased from 3 to 12 months. Persistent GGO were associated with initial COVID-19 severity and age ≥60 years.

The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors.

This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination.

A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed.

The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

As the long-term consequences of coronavirus disease 2019 (COVID-19) have not been defined, it is necessary to explore persistent symptoms, long-term respiratory impairment, and impact on quality of life over time in COVID-19 survivors. In this prospective cohort study, convalescent individuals diagnosed with COVID-19 were followed-up 2 and 3 years after discharge from hospital. Participants completed an in-person interview to assess persistent symptoms and underwent blood tests, pulmonary function tests, chest high-resolution computed tomography, and the 6-min walking test. There were 762 patients at the 2-year follow-up and 613 patients at the 3-year follow-up. The mean age was 60 years and 415 (54.5%) were men. At 3 years, 39.80% of the participants had at least one symptom; most frequently, fatigue, difficulty sleeping, joint pain, shortness of breath, muscle aches, and cough. The participants experienced different degrees of pulmonary function impairment, with decreased carbon monoxide diffusion capacity being the main feature; results remained relatively stable over the 2-3 years. Multiple logistic regression analysis demonstrated that female sex and smoking were independently associated with impaired diffusion capacity. A subgroup analysis based on disease severity was performed, indicating that there was no difference in other parameters of lung function except forced vital capacity at 3-year follow-up. Persistent radiographic abnormalities, most commonly fibrotic-like changes, were observed at both timepoints. At 3 years, patients had a significantly improved Mental Component Score compared with that at 2 years, with a lower percentage with anxiety. Our study indicated that symptoms and pulmonary abnormalities persisted in COVID-19 survivors at 3 years. Further studies are warranted to explore the long-term effects of COVID-19 and develop appropriate rehabilitation strategies.

To investigate potential differences in clinical and computed tomography (CT) features between patients with the SARS-CoV-2 Omicron variant and the original strain.

This retrospective study included 69 hospitalized patients infected with Omicron variant from November to December 2022, and 96 hospitalized patients infected with the original strain from February to March 2020 in Chongqing, China. The clinical features, CT manifestations, degrees of lung involvement in different stages on CT, and imaging changes after the reverse-transcription polymerase chain reaction (RT-PCR) results turned negative were compared between the two groups.

For clinical features, patients with Omicron were predominantly old people and females, without manifestation of any clinical symptoms, who had low serum levels of C-reactive protein and procalcitonin. Shorter interval from symptoms onset to initial CT scan was observed in Omicron patients compared to patients with the original strain (all P < 0.05). For CT features, patients with Omicron were more likely to present with round-like opacities and tree-in-bud pattern (all P < 0.05), but less likely to exhibit a diffuse distribution, patchy and linear opacities, as well as vascular enlargement pattern (all P < 0.05). The Omicron group was more susceptible to exhibiting lower CT involvement scores in each stage (all P < 0.05) and imaging progression after the RT-PCR results turned negative (P < 0.001).

Patients infected with the Omicron variant exhibited less severe changes on chest CT compared to those infected with the original strain. Furthermore, imaging progression under low viral load conditions was more common in patients with Omicron than in those with the original strain.

This study aimed to assess pulmonary changes at 6-month follow-up CT and predictors of pulmonary residual abnormalities and fibrotic-like changes in COVID-19 pneumonia patients in China following relaxation of COVID restrictions in 2022. A total of 271 hospitalized patients with COVID-19 pneumonia admitted between November 29, 2022 and February 10, 2023 were prospectively evaluated at 6 months. CT characteristics and Chest CT scores of pulmonary abnormalities were compared between the initial and the 6-month CT. The association of demographic and clinical factors with CT residual abnormalities or fibrotic-like changes were assessed using logistic regression. Follow-up CT scans were obtained at a median of 177 days (IQR, 170-185 days) after hospital admission. Pulmonary residual abnormalities and fibrotic-like changes were found in 98 (36.2%) and 39 (14.4%) participants. In multivariable analysis of pulmonary residual abnormalities and fibrotic-like changes, the top three predictive factors were invasive ventilation (OR 13.6; 95% CI 1.9, 45; P < .001), age > 60 years (OR 9.1; 95% CI 2.3, 39; P = .01), paxlovid (OR 0.11; 95% CI 0.04, 0.48; P = .01) and invasive ventilation (OR 10.3; 95% CI 2.9, 33; P = .002), paxlovid (OR 0.1; 95% CI 0.03, 0.48; P = .01), smoker (OR 9.9; 95% CI 2.4, 31; P = .01), respectively. The 6-month follow-up CT of recent COVID-19 pneumonia cases in China showed a considerable proportion of the patients with pulmonary residual abnormalities and fibrotic-like changes. Antivirals against SARS-CoV-2 like paxlovid may be beneficial for long-term regression of COVID-19 pneumonia.

Global and national surveillance efforts have tracked COVID-19 incidence and clinical outcomes, but few studies have compared comorbid conditions and clinical outcomes across each wave of the pandemic. We analyzed data from the COVID-19 registry of a large urban healthcare system to determine the associations between presenting comorbidities and clinical outcomes during the pandemic.

We analyzed registry data for all inpatients and outpatients with COVID-19 from March 2020 through September 2022 (N = 44,499). Clinical outcomes were death, hospitalization, and intensive care unit (ICU) admission. Demographic and clinical outcomes data were analyzed overall and for each wave. Unadjusted and multivariable logistic regressions were performed to explore the associations between age, sex, race, ethnicity, comorbidities, and mortality.

Waves 2 and 3 (Alpha and Delta variants) were associated with greater hospitalizations, ICU admissions, and mortality than other variants. Chronic pulmonary disease was the most common comorbid condition across all age groups and waves. Mortality rates were higher in older patients but decreased across all age groups in later waves. In every wave, mortality was associated with renal disease, congestive heart failure, cerebrovascular disease, diabetes, and chronic pulmonary disease. Multivariable analysis found that liver disease and renal disease were significantly associated with mortality, hospitalization, and ICU admission, and diabetes was significantly associated with hospitalization and ICU admission.

The COVID-19 registry is a valuable resource to identify risk factors for clinical outcomes. Our findings may inform risk stratification and care planning for patients with COVID-19 based on age and comorbid conditions.

The H5N1 influenza virus is a cause of severe pneumonia. Co-infection of influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may lead to poor prognosis of patients during the COVID-19 epidemic. However, reports on patients co-infected with avian influenza virus and SARS-CoV-2 are scarce.

A 52-year-old woman presented with a fever, which has persisted for the past eight days, along with worsening shortness of breath and decreased blood pressure. Computed tomography (CT) revealed an air bronchogram, lung consolidation, and bilateral pleural effusion. The subsequent polymerase chain reaction (PCR) of the bronchoalveolar lavage fluid (BALF) revealed positivity for H5N1 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The H5N1 influenza virus is a cause of severe pneumonia. The clinical presentation of the patient had a predomination of H5N1 influenza rather than COVID-19. A PCR analysis for the identification of the virus is necessary to reveal the pathogen causing the severe pneumonia. The patient exhibited an excellent prognosis upon the use of the appropriate antiviral medicine.

Background The impact of waning vaccine effectiveness on the severity of COVID-19-related findings discovered with radiologic examinations remains underexplored. Purpose To evaluate the effectiveness of vaccines over time against severe clinical and radiologic outcomes related to SARS-CoV-2 infections. Materials and Methods This multicenter retrospective study included patients in the Korean Imaging Cohort of COVID-19 database who were hospitalized for COVID-19 between June 2021 and December 2022. Patients who had received at least one dose of a SARS-CoV-2 vaccine were categorized based on the time elapsed between diagnosis and their last vaccination. Adjusted multivariable logistic regression analysis was used to estimate vaccine effectiveness against a composite of severe clinical outcomes (invasive ventilation, extracorporeal membrane oxygenation, or in-hospital death) and severe radiologic pneumonia (≥25% of lung involvement), and odds ratios (ORs) were compared between patients vaccinated within 90 days of diagnosis and those vaccinated more than 90 days before diagnosis. Results Of 4196 patients with COVID-19 (mean age, 66 years ± 17 [SD]; 2132 [51%] women, 2064 [49%] men), the ratio of severe pneumonia since their most recent vaccination was as follows: 90 days or less, 18% (277 of 1527); between 91 and 120 days, 22% (172 of 783); between 121 and 180 days, 27% (274 of 1032); between 181 and 240 days, 32% (159 of 496); and more than 240 days, 31% (110 of 358). Patients vaccinated more than 240 days before diagnosis showed increased odds of severe clinical outcomes compared with patients vaccinated within 90 days (OR = 1.94 [95% CI: 1.16, 3.24]; P = .01). Similarly, patients vaccinated more than 240 days before diagnosis showed increased odds of severe pneumonia on chest radiographs compared with patients vaccinated within 90 days (OR = 1.65 [95% CI: 1.13, 2.40]; P = .009). No difference in odds of severe clinical outcomes (P = .13 to P = .68) or severe pneumonia (P = .15 to P = .86) were observed between patients vaccinated 91-240 days before diagnosis and those vaccinated within 90 days of diagnosis. Conclusion Vaccine effectiveness against severe clinical outcomes and severe pneumonia related to SARS-CoV-2 infection gradually declined, with increased odds of both observed in patients vaccinated more than 240 days before diagnosis. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Wells in this issue.

Significant changes were observed in the lung imaging of hospitalised COVID-19 patients from 2020 to 2023, with the emergence of more signs of co-infection https://bit.ly/3TaQlJ2.

With the COVID-19 pandemic having lasted more than 3 years, concerns are growing about prolonged symptoms and respiratory complications in COVID-19 survivors, collectively termed post-COVID-19 condition (PCC). Up to 50% of patients have residual symptoms and physiologic impairment, particularly dyspnea and reduced diffusion capacity. Studies have also shown that 24%-54% of patients hospitalized during the 1st year of the pandemic exhibit radiologic abnormalities, such as ground-glass opacity, reticular opacity, bronchial dilatation, and air trapping, when imaged more than 1 year after infection. In patients with persistent respiratory symptoms but normal results at chest CT, dual-energy contrast-enhanced CT, xenon 129 MRI, and low-field-strength MRI were reported to show abnormal ventilation and/or perfusion, suggesting that some lung injury may not be detectable with standard CT. Histologic patterns in post-COVID-19 lung disease include fibrosis, organizing pneumonia, and vascular abnormality, indicating that different pathologic mechanisms may contribute to PCC. Therefore, a comprehensive imaging approach is necessary to evaluate and diagnose patients with persistent post-COVID-19 symptoms. This review will focus on the long-term findings of clinical and radiologic abnormalities and describe histopathologic perspectives. It also addresses advanced imaging techniques and deep learning approaches that can be applied to COVID-19 survivors. This field remains an active area of research, and further follow-up studies are warranted for a better understanding of the chronic stage of the disease and developing a multidisciplinary approach for patient management.

The Omicron variant of COVID-19 is less severe than the ancestral strain, leading to the potential for deaths in patients infected with the virus but who die of other causes. This study evaluated the difference in rates of pneumonia among patients who died with SARS-CoV-2 infection in the ancestral vs Omicron eras.

We identified patients who died within 30days of a positive SARS-CoV-2 test, from March 2020 through December 2022; variants were assigned based on the prevalent variant in the US at that time. We also obtained a control group from patients who died within 30days of a negative SARS-CoV-2 test in January 2022. The first CT after the test was reviewed in a blinded fashion and assigned a category from the RSNA Consensus Reporting Guidelines. The primary outcome was the difference in rates of positive (typical or indeterminate) COVID-19 findings in the ancestral vs Omicron eras.

A total of 598 patients died during the ancestral era and 400 during the Omicron era, and 347 decedents comprised the control group. The rate of positive COVID-19 findings was 67/81 (83%) in the ancestral era and 43/81 (53%) in the Omicron era (P < .001), an absolute difference of 30% (95% CI 16%-43%). The rate of positive findings in the control group was 23/76 (30%).

During the Omicron era, 30% fewer SARS-CoV-2-associated deaths were associated with COVID-19 pneumonia and were caused either by nonpulmonary effects of the infection or were unrelated to the infection.

Little information is available regarding incidence and severity of pulmonary embolism (PE) across the periods of ancestral strain, Alpha, Delta, and Omicron variants. The aim of this study is to investigate the incidence and severity of PE over the dominant periods of ancestral strain and Alpha, Delta, and Omicron variants. We hypothesized that the incidence and the severity by proximity of PE in patients with the newer variants and vaccination would be decreased compared with those in ancestral and earlier variants. Patients with COVID-19 diagnosis between March 2020 and February 2022 and computed tomography pulmonary angiogram performed within a 6-week window around the diagnosis (-2 to +4 weeks) were studied retrospectively. The primary endpoints were the associations of the incidence and location of PE with the ancestral strain and each variant. Of the 720 coronavirus disease 2019 patients with computed tomography pulmonary angiogram (58.6 ± 17.2 years; 374 females), PE was diagnosed among 42/358 (12%) during the ancestral strain period, 5/60 (8%) during the Alpha variant period, 16/152 (11%) during the Delta variant period, and 13/150 (9%) during the Omicron variant period. The most proximal PE (ancestral strain vs variants) was located in the main/lobar arteries (31% vs 6%-40%), in the segmental arteries (52% vs 60%-75%), and in the subsegmental arteries (17% vs 0%-19%). There was no significant difference in both the incidence and location of PE across the periods, confirmed by multivariable logistic regression models. In summary, the incidence and severity of PE did not significantly differ across the periods of ancestral strain and Alpha, Delta, and Omicron variants.

To investigate the frequency of pneumonia and chest computed tomography (CT) findings in patients with coronavirus disease 2019 (COVID-19) during the fifth Delta variant-predominant and sixth Omicron variant-predominant waves of the COVID-19 pandemic in Okinawa, Japan. A survey on chest CT examinations for patients with COVID-19 was conducted byhospitals with board-certified radiologists who provided treatment for COVID-19 pneumonia in Okinawa Prefecture. Data from 11 facilities were investigated. Indications for chest CT; number of COVID-19 patients undergoing chest CT; number of patients with late-onset pneumonia, tracheal intubation, and number of deaths; and COVID-19 Reporting and Data System classifications of initial chest CT scans were compared by the chi-squared test between the two pandemic waves (Delta vs. Omicron variants). A total of 1944 CT scans were performed during the fifth wave, and 1178 were performed during the sixth wave. CT implementation rates, which were the number of patients with COVID-19 undergoing CT examinations divided by the total number of COVID-19 cases in Okinawa Prefecture during the waves, were 7.1% for the fifth wave and 2.1% for the sixth wave. The rates of tracheal intubation and mortality were higher in the fifth wave. Differences between the distributions of the CO-RADS classifications were statistically significant for the fifth and sixth waves (p < 0.0001). In the fifth wave, CO-RADS 5 (typical of COVID-19) was most common (65%); in the sixth wave, CO-RADS 1 (no findings of pneumonia) was most common (50%). The finding of "typical for other infection but not COVID-19" was more frequent in the sixth than in the fifth wave (13.6% vs. 1.9%, respectively). The frequencies of pneumonia and typical CT findings were higher in the fifth Delta variant-predominant wave, and nontypical CT findings were more frequent in the sixth Omicron variant-predominant wave of the COVID-19 pandemic in Okinawa, Japan.

Background and objective It is crucial to make early differentiation between coronavirus disease 2019 (COVID-19) and seasonal influenza infections at the time of a patient's presentation to the emergency department (ED). In light of this, this study aimed to identify key epidemiological, initial laboratory, and radiological differences that would enable early recognition during co-circulation. Methods This was a retrospective, observational cohort study. All adult patients presenting to our ED at the Watford General Hospital, UK, with a laboratory-confirmed diagnosis of COVID-19 (2019/20) or influenza (2018/19) infection were included in this study. Demographic, laboratory, and radiological data were collected. Binary logistic regression was employed to determine features associated with COVID-19 infection rather than influenza. Results Chest radiographs suggestive of viral pneumonitis and older age (≥80 years) were associated with increased odds of having COVID-19 [odds ratio (OR): 47.00, 95% confidence interval (CI): 21.63-102.13 and OR: 64.85, 95% CI: 19.96-210.69 respectively]. Low eosinophils (<0.02 x 109/L) were found to increase the odds of COVID-19 (OR: 2.12, 95% CI: 1.44-3.10, p<0.001). Conclusions Gaining awareness about the epidemiological, biological, and radiologic presentation of influenza-like illness can be useful for clinicians in ED to differentiate between COVID-19 and influenza. This study showed that older age, eosinopenia, and radiographic evidence of viral pneumonitis significantly increase the odds of having COVID-19 compared to influenza. Further research is needed to determine if these findings are affected by acquired or natural immunity.

We investigated different computed tomography (CT) features between Omicron-variant and original-strain SARS-CoV‑2 pneumonia to facilitate the clinical management.

Medical records were retrospectively reviewed to select patients with original-strain SARS-CoV‑2 pneumonia from February 22 to April 22, 2020, or Omicron-variant SARS-CoV‑2 pneumonia from March 26 to May 31, 2022. Data on the demographics, comorbidities, symptoms, clinical types, and CT features were compared between the two groups.

There were 62 and 78 patients with original-strain or Omicron-variant SARS-CoV‑2 pneumonia, respectively. There were no differences between the two groups in terms of age, sex, clinical types, symptoms, and comorbidities. The main CT features differed between the two groups (p = 0.003). There were 37 (59.7%) and 20 (25.6%) patients with ground-glass opacities (GGO) in the original-strain and Omicron-variant pneumonia, respectively. A consolidation pattern was more frequently observed in the Omicron-variant than original-strain pneumonia (62.8% vs. 24.2%). There was no difference in crazy-paving pattern between the original-strain and Omicron-variant pneumonia (16.1% vs. 11.6%). Pleural effusion was observed more often in Omicron-variant pneumonia, while subpleural lesions were more common in the original-strain pneumonia. The CT score in the Omicron-variant group was higher than that in the original-strain group for critical-type (17.00, 16.00-18.00 vs. 16.00, 14.00-17.00, p = 0.031) and for severe-type (13.00, 12.00-14.00 vs 12.00, 10.75-13.00, p = 0.027) pneumonia.

The main CT finding of the Omicron-variant SARS-CoV‑2 pneumonia included consolidations and pleural effusion. By contrast, CT findings of original-strain SARS-CoV‑2 pneumonia showed frequent GGO and subpleural lesions, but without pleural effusion. The CT scores were also higher in the critical and severe types of Omicron-variant than original-strain pneumonia.

To investigate the computed tomography (CT) findings of SARs-CoV-2 Omicron variant in relation to respiratory viral loads determined by cycle threshold values in reverse-transcription polymerase chain reaction (RT-PCR).

From October 2022 to November 2022, 74 hospitalized patients with Omicron were included in this retrospective study. The radiological features, CT involvement scores in relation to the respiratory viral load, and factors associated with imaging progression (IP) after the RT-PCR results turned negative were analyzed.

The most common CT patterns of Omicron were multiple round-like or patchy ground-glass opacity (GGO) or mixed GGO in the peripheral or diffuse areas. The grading of CT involvement scores exhibited an inverse pattern compared to viral loads from day 1 to day 8 and from day 13 to day 20 after diagnosis. Among the 65 patients with complete imaging data, 45 (69.23%) showed IP with clinical warning indicators of disease exacerbation negative in 34 and positive in 11. Patients with IP were older than those with non-IP (NIP); the erythrocyte sedimentation rates, procalcitonin levels, and D-dimer levels on admission of patients with IP were significantly higher than those of patients with NIP, whereas the immunoglobulin (Ig) G antibody level on admission and CT involvement score on initial CT of patients with IP were significantly lower than those of patients with NIP (all P < 0.05).

For patients with Omicron, the IP of lung abnormalities is common when the viral load decreases. Under these circumstances, paying attention to clinical warming indicators of disease progression may contribute to better patient management and the mitigation of severe pneumonia.

The COVID-19 pandemic is considered one of the most devastating situations globally, the worst affected were the senior citizens. A number of initiatives were carried out to control the COVID-19 pandemic; one such important measure is the development of COVID-19 vaccines to prevent the disease. But the continuous emergence of new SARS-COV2 variants (antigenic drift) and its demographic variation in virulence makes the vaccine's efficacy questionable. This study is intended to evaluate the association between the degree of lung involvement and the effectiveness of vaccination against the disease in cases admitted to a designated hospital in Tamil Nadu.

A hospital records-based-retrospective research was conducted among COVID-19 patients admitted from the 1st of April 2021 to the 31st of May 2021, and information was gathered regarding their vaccination status, comorbid conditions, and CT severity score (CTSS) in the HRCT lung report. A consecutive sampling technique was used to choose the study participants; about 120 participants were included in the study. The Chi-square test and Fisher's extract test were used to evaluate the hypothesis. The relationship between a dependent variable and independent factors was estimated using multiple linear regression.

Among 120 participants, about 60.2% were males and 39.8% were females. Vaccination status and comorbid conditions had a significant association with severe lung involvement in COVID-19 patients.

Non-vaccinated patients had severe lung involvement based on the HRCT lung scan findings than the vaccinated patients. To reduce mortality, it is essential to ensure universal coverage of COVID-19 vaccination.

Survivors of SARS-CoV-2 pneumonia often develop persistent respiratory symptom and interstitial lung abnormalities (ILAs) after infection. Risk factors for ILA development and duration of ILA persistence after SARS-CoV-2 infection are not well described in immunocompromised hosts, such as cancer patients.

We conducted a prospective cohort study of 95 patients at a major cancer center and 45 patients at a tertiary referral center. We collected clinical and radiographic data during the index hospitalization for COVID-19 pneumonia and measured pneumonia severity using a semi-quantitative radiographic score, the Radiologic Severity Index (RSI). Patients were evaluated in post-COVID-19 clinics at 3 and 6 months after discharge and underwent comprehensive pulmonary evaluations (symptom assessment, chest computed tomography, pulmonary function tests, 6-min walk test). The association of clinical and radiological factors with ILAs at 3 and 6 months post-discharge was measured using univariable and multivariable logistic regression.

Sixty-six (70%) patients of cancer cohort had ILAs at 3 months, of whom 39 had persistent respiratory symptoms. Twenty-four (26%) patients had persistent ILA at 6 months after hospital discharge. In adjusted models, higher peak RSI at admission was associated with ILAs at 3 (OR 1.5 per 5-point increase, 95% CI 1.1-1.9) and 6 months (OR 1.3 per 5-point increase, 95% CI 1.1-1.6) post-discharge. Fibrotic ILAs (reticulation, traction bronchiectasis, and architectural distortion) were more common at 6 months post-discharge.

Post-COVID-19 ILAs are common in cancer patients 3 months after hospital discharge, and peak RSI and older age are strong predictors of persistent ILAs.

This study aimed to compare the clinical picture of COVID-19 in the initial and later period of Omicron dominance and to identify populations still at risk. A retrospective comparison of the clinical data of 965 patients hospitalized during the early period of Omicron's dominance (EO, January-June 2022) with 897 patients from a later period (LO, July 2022-April 2023) from the SARSTer database was performed. Patients hospitalized during LO, compared to EO, were older, had a better clinical condition on admission, had a lower need for oxygen and mechanical ventilation, had less frequent lung involvement in imaging, and showed much faster clinical improvement. Moreover, the overall mortality during EO was 14%, higher than that in LO-9%. Despite the milder course of the disease, mortality exceeding 15% was similar in both groups among patients with lung involvement. The accumulation of risk factors such as an age of 60+, comorbidities, lung involvement, and oxygen saturation <90% resulted in a constant need for oxygen in 98% of patients, an 8% risk of mechanical ventilation, and a 30% mortality rate in the LO period. Multiple logistic regression revealed lower odds of death during the LO phase. Despite the milder course of infections caused by the currently dominant subvariants, COVID-19 prophylaxis is necessary in people over 60 years of age, especially those with comorbidities, and in the case of pneumonia and respiratory failure.

Understanding the changing epidemiology of adults hospitalized with coronavirus disease 2019 (COVID-19) informs research priorities and public health policies.

Among adults (≥18 years) hospitalized with laboratory-confirmed, acute COVID-19 between 11 March 2021, and 31 August 2022 at 21 hospitals in 18 states, those hospitalized during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron-predominant period (BA.1, BA.2, BA.4/BA.5) were compared to those from earlier Alpha- and Delta-predominant periods. Demographic characteristics, biomarkers within 24 hours of admission, and outcomes, including oxygen support and death, were assessed.

Among 9825 patients, median (interquartile range [IQR]) age was 60 years (47-72), 47% were women, and 21% non-Hispanic Black. From the Alpha-predominant period (Mar-Jul 2021; N = 1312) to the Omicron BA.4/BA.5 sublineage-predominant period (Jun-Aug 2022; N = 1307): the percentage of patients who had ≥4 categories of underlying medical conditions increased from 11% to 21%; those vaccinated with at least a primary COVID-19 vaccine series increased from 7% to 67%; those ≥75 years old increased from 11% to 33%; those who did not receive any supplemental oxygen increased from 18% to 42%. Median (IQR) highest C-reactive protein and D-dimer concentration decreased from 42.0 mg/L (9.9-122.0) to 11.5 mg/L (2.7-42.8) and 3.1 mcg/mL (0.8-640.0) to 1.0 mcg/mL (0.5-2.2), respectively. In-hospital death peaked at 12% in the Delta-predominant period and declined to 4% during the BA.4/BA.5-predominant period.

Compared to adults hospitalized during early COVID-19 variant periods, those hospitalized during Omicron-variant COVID-19 were older, had multiple co-morbidities, were more likely to be vaccinated, and less likely to experience severe respiratory disease, systemic inflammation, coagulopathy, and death.