The Spanish Society of Pulmonology and Thoracic Surgery created a registry for hospitalised patients with COVID-19 and the different types of respiratory support used (RECOVID). Objectives. To describe the profile of hospitalised patients with COVID-19, comorbidities, respiratory support treatments and setting. In addition, we aimed to identify varying profiles of patients according to outcomes and the complexity of respiratory support needed.

Multicentre, observational study in 49 Spanish hospitals. A protocol collected demographic data, comorbidities, respiratory support, treatment setting and 1-year follow-up. Patients were described using either frequency and percentages or median and interquartile range, as appropriate. A cluster analysis made it possible to identify different types of profile among the patients.

In total, 2148 of 2454 hospitalised patients (87.5%) received care in the conventional ward, whilst 126 in IRCU and 180 in ICU. In IRCU, 30% required high-flow nasal oxygen whilst 25%, non-invasive mechanical ventilation and 17%, mechanical ventilation. Four clusters of patients were identified. Two clusters were more likely to require IRCU/ICU admission, although primarily Cluster 2: Cluster (C) 1 consisted of patients without comorbidities and C2, those with comorbidities. Both presented higher inflammatory levels and lower lymphocyte count and SpO2/FiO2; however, C2 showed worse values. Two different clusters identified patients requiring less complex respiratory support. C3 presented higher comorbidities and elevated lymphocyte count, SpO2/FiO2 and low C-reactive protein (CRP). C4 included those without comorbidities except for arterial hypertension, lymphopenia and an intermediate CRP. In-hospital mortality and subsequent 1-year mortality were greater for C2 (28.6% and 7.1%) and C1 (11.1%, 8.3%) than for C4 (3.3%, 1.8%) and C3 (0%, 0%).

The cluster analysis identified four clinical phenotypes requiring distinct types of respiratory support, with great differences present per characteristics and outcomes.

This study investigated the role of protein disulphide isomerase A4 (PDIA4) in the pathogenesis of coronavirus disease 2019 (COVID-19), focusing on its relationship with disease severity and potential as a biomarker. We analysed a cohort of adult COVID-19 patients with varying disease severity, grouped by vaccination status. Serum levels of PDIA4 and cytokines (interleukin [IL]-6, interferon gamma inducible protein-10 [IP-10], IL-16, monocyte chemoattractant protein-1 [MCP-1], and platelet-derived growth factor-BB [PDGF-BB]) were measured using enzyme-linked immunosorbent assay and compared among patients with different disease severities. Statistical analyses were performed to assess the correlation between PDIA4 levels, disease severity, and inflammatory markers. Unvaccinated COVID-19 patients with pneumonia had significantly higher PDIA4 levels than those without pneumonia (517.94 ± 264 vs. 284.86 ± 2.24; p = 0.0022). Although unvaccinated patients requiring oxygen support exhibited higher PDIA4 levels than those not requiring oxygen (519.30 ± 269.67 vs. 420.89 ± 240.49; p = 0.4825), the difference was not statistically significant. No significant difference was observed in the PDIA4 levels between unvaccinated patients with and without respiratory failure. Levels of PDIA4 were positively correlated with the levels of IL-16, MCP-1, IP-10, and IL-6 (correlation coefficients: 0.28-0.62), although this correlation was weaker or absent in vaccinated patients. Our findings suggest that PDIA4 is associated with COVID-19 severity and may serve as a potential biomarker of disease progression. Further studies are needed to elucidate the mechanisms by which PDIA4 influences the immune response and assess its potential for therapeutic exploration in COVID-19.

Persistent respiratory symptoms and impaired gas exchange are common in patients recovering from COVID-19 pneumonia. The Lung Diffusing Capacity for Carbon Monoxide (DLCO) and Carbon Monoxide Transfer Coefficient (KCO) do not adequately distinguish alveolar membrane dysfunction from vascular abnormalities. This study aimed to characterize persistent diffusion impairment in post-ICU patients with prior SARS-CoV-2 pneumonia and reduced DLCO.

After hospital discharge, patients underwent spirometry, DLCO measurement, and a 6-minute walking test every six months. If DLCO remained impaired at 18-24 months, a combined Lung Diffusing Capacity for Nitric Oxide (DLNO) and DLCO assessment was performed to differentiate alveolar-capillary membrane (DmCO) and pulmonary capillary blood volume (Vc) alterations.

Among 20 patients with persistent DLCO reduction, 3 had an obstructive ventilatory pattern, 6 had restriction, and 12 had low KCO. In restrictive cases, KCO was reduced but remained within normal limits without compensation. The DLNO/DLCO ratio exceeded 113.5% predicted in all patients. DmCO was impaired in 7 patients, while Vc was reduced in 16.

Both DLCO determinants were affected, with vascular impairment predominating. Vc reduction was present in most patients, with mean values below the lower limit of normality, whereas DmCO was less affected and often normal. The elevated DLNO/DLCO ratio suggests that persistent DLCO reduction is primarily driven by prolonged pulmonary capillary circulation dysfunction rather than alveolar membrane alterations, highlighting the vascular component as the primary site of long-term impairment.

The impact of COVID-19 on lung function and sleep in otherwise healthy individuals has been subject to a limited number of studies. The aim of this study was to investigate the effect of COVID-19 on pulmonary function and sleep in adults. Participants, 50-85 years old, who had recovered from COVID-19 (COVID-19 group: n = 48) and those without history of COVID-19 (control group: n = 28) underwent pulmonary function assessment (Forced Vital Capacity, FVC, and Slow Vital Capacity, SVC) using spirometry. Sleep and circadian variables were measured objectively with wrist-worn actigraphy for seven days. Subjective sleep of participants was assessed using the Pittsburgh Sleep Quality Index (PSQI). There were no significant differences in age (60 ± 6 vs 62 ± 6 years), BMI (26.30 ± 4.25 vs 26.48 ± 3.60 kg/m2), or pulmonary function (FVC, 4.02 ± 1.04 vs 3.80 ± 0.98 L, p = 0.36; and SVC, 3.82 ± 1.09 vs 3.89 ± 0.92 L, p = 0.76) between COVID-19 and control groups. The COVID-19 group had significantly reduced sleep efficiency (0.87 ± 0.04 vs 0.91 ± 0.04, p < 0.01), increased sleep disturbance (awakenings, 1.70 ± 1.02 vs 1.15 ± 1.15, p < 0.01; and wakefulness after sleep onset, 35:05 ± 25:37 vs 20:02 ± 12:48 min, p = 0.01) and PSQI score (5.19 ± 2.88 vs 3.93 ± 2.89, p = 0.01), compared to the control group. Individuals with history of COVID-19 demonstrate reduced sleep quality compared to a non-COVID-19 control group.

COVID-19 is no longer a global health emergency, but it remains challenging to predict its prognosis.

To develop and validate an instrument to predict COVID-19 progression for critically ill hospitalized patients in a Brazilian population.

Observational study with retrospective follow-up. Participants were consecutively enrolled for treatment in non-critical units between January 1, 2021, to February 28, 2022. They were included if they were adults, with a positive RT-PCR result, history of exposure, or clinical or radiological image findings compatible with COVID-19. The outcome was characterized as either transfer to critical care or death. Predictors such as demographic, clinical, comorbidities, laboratory, and imaging data were collected at hospitalization. A logistic model with lasso or elastic net regularization, a random forest classification model, and a random forest regression model were developed and validated to estimate the risk of disease progression.

Out of 301 individuals, the outcome was 41.8 %. The majority of the patients in the study lacked a COVID-19 vaccination. Diabetes mellitus and systemic arterial hypertension were the most common comorbidities. After model development and cross-validation, the Random Forest regression was considered the best approach, and the following eight predictors were retained: D-dimer, Urea, Charlson comorbidity index, pulse oximetry, respiratory frequency, Lactic Dehydrogenase, RDW, and Radiologic RALE score. The model's bias-corrected intercept and slope were - 0.0004 and 1.079 respectively, the average prediction error was 0.028. The ROC AUC curve was 0.795, and the variance explained was 0.289.

The prognostic model was considered good enough to be recommended for clinical use in patients during hospitalization (https://pedrobrasil.shinyapps.io/INDWELL/). The clinical benefit and the performance in different scenarios are yet to be known.

Bronchial asthma, a widely prevalent respiratory disease influencing individuals of all age groups worldwide, has been increasingly recognized as a global concern. While there exists a potentially heightened risk of severe coronavirus disease 2019 (COVID-19) in asthmatic patients, particularly those with non-allergic asthma, it is uncertain whether COVID-19 infection-induced bronchial asthma has its own unique clinical characteristics. The present study aimed to compare and analyze the pulmonary function and eosinophilic inflammation indices of patients with COVID-19 infection-induced bronchial asthma and those with typical bronchial asthma, and further deepen the understanding of COVID-19 infection-induced bronchial asthma. A retrospective analysis was conducted on the pulmonary function and inflammatory characteristics of 116 patients diagnosed with COVID-19 infection-induced bronchial asthma and treated in outpatient clinics after March 2023, as well as 113 patients with typical bronchial asthma diagnosed and treated from January 2022 to November 2022. The main clinical characteristics were cough, sputum, chest tightness, dyspnea and wheezing. There was no significant difference in clinical characteristics between the two groups. The results indicated that there was no significant difference in the total IgE, the absolute value and percentage of eosinophil, transoral FeNO, and trans-nasal FeNO in the peripheral blood samples of patients in the COVID-19 infection-induced bronchial asthma group compared with the typical bronchial asthma group. Although there was no significant difference between the two groups in the rates of impairment in ventilation function, reserve function, and small airway function, significant differences were identified in various indicators, including forced expiratory volume in 1 sec as a percentage of the predicted value (FEV1%), residual volume/total lung capacity (RV/TLC), peak expiratory flow (PEF), maximal expiratory flow rate at 75% (MEF75), maximal voluntary ventilation (MVV), FEV * 30, and residual volume (RV) between the two groups. The findings indicated that patients with COVID-19 infection-induced bronchial asthma exhibited a comparatively inferior pulmonary function versus those with typical bronchial asthma. However, it is important to note that the clinical impact of this disparity was not statistically significant.

Nirmatrelvir-Ritonavir (NR) has proven effective for mild to moderate COVID-19 patients at risk of disease progression. Following its emergency use authorization in Taiwan in January 2022, this study aims to evaluate its impact on severe COVID-19 outcomes across different patient demographics in Taiwan.

We performed a retrospective analysis of a database that includes data from three hospitals in Northern Taiwan. Patients with COVID-19 in 2022 were paired by propensity score matching based on NR prescription. Cox proportional hazard regression analysis calculated hazard ratios (HR), adjusting for confounding factors. Subgroup analysis determined HRs across patient characteristics.

Among 95,096 patients, 3329 were in the NR group, and 12,807 in the non-NR group. NR users demonstrated significantly better prevention of severe outcomes: intubation (HR=0.296 [95 % CI: 0.187-0.469], p = 0.0482); ICU admission (HR=0.327[0.108-0.991], p < 0.001); mortality (HR=0.195 [0.101-0.378], p < 0.001). Subgroup analysis revealed significantly lower intubation risks for NR users among both sexes, aged 18-65 or ≥ 65 years, BMI < 30, and patients with diabetes mellitus (DM), cardiovascular disease (CVD), or chronic obstructive pulmonary disease (COPD). ICU admission risk was lower for NR users among males, aged ≥ 65 years, and BMI < 30. Mortality risk was lower for NR users among both sexes, aged ≥ 65 years, BMI < 30, and patients with DM, CVD, or COPD.

NR significantly reduces the risk of severe COVID-19, particularly among older adults and those with pre-existing conditions, supporting NR as an essential treatment for high-risk COVID-19 patients.

As new SARS-CoV-2 variants emerge and as treatment of COVID-19 ARDS remains exclusively supportive, there is an unmet need to better characterize its different phenotypes to tailor personalized treatments. Clinical, biological, spirometric and CT data hardly allow deciphering of Heavy (H), Intermediate (I) and Light (L) phenotypes of COVID-19 ARDS and the implementation of tailored specific strategies (prone positioning, PEEP settings, recruitment maneuvers). We hypothesized that the ratio of two pivotal COVID-19 biomarkers (interleukin 6 [IL-6] and Krebs von den Lungen 6 [KL-6], related to inflammation and pneumocyte repair, respectively) would provide a biologic insight into the disease timeline allowing 1) to differentiate H, I and L phenotypes, 2) to predict outcome and 3) to reflect some of CT findings.

This was a retrospective analysis of prospectively acquired data (COVID HUS cohort). Inclusion concerned any patient with severe COVID-19 pneumonia admitted to two intensive care units between March 1st and May 1st, 2020, in a high-density cluster of the first epidemic wave (Strasbourg University Hospital, France). Demographic, clinical, biological (standard, IL-6 [new generation ELISA], KL-6 [CLEIA technique]), spirometric (driving pressure, respiratory system compliance) and CT data were collected longitudinally. CT analysis included semi-automatic and automatic lung measurements and allowed segmentation of lung volumes into 4 (poorly aerated, non-aerated, overinflated and normally aerated) and 3 (ground-glass, restricted normally aerated, and overinflated) zones, respectively. The primary outcome was to challenge the IL-6/KL-6 ratio capacity to decipher the three COVID-19 ARDS phenotypes (H, I and L) defined on clinical, spirometric and radiologic grounds. Secondary outcomes were the analysis of the prognostic value of the IL-6/KL-6 ratio and its correlates with CT-acquired data. Multivariate analysis was based on principal component analysis. One hundred and forty-eight ventilated COVID-19 ICU patients from the COVID HUS cohort were assessed for eligibility and 77 were included in the full analysis. Most were male, all were under invasive mechanical ventilation and vasopressor therapy and displayed high severity scores (SAPSII: 48 [42-56]; SOFA: 8 [7-10]). The L, I and H COVID ARDS phenotypes were identified in 11, 15 and 48 patients, respectively. In three patients, the phenotype could not be defined precisely. Thirty patients (39%) died in the ICU and the number of ventilator-free days was 2 [0-2] days. The IL-6/KL-6 ratio was not significantly different between the L, I and H phenotypes and evolved according to similar patterns over time. Surviving and deceased patients displayed an inverse kinetic of KL-6. IL-6 and the IL-6/KL-6 ratio were linearly associated with ground-glass volume on semi-automatic and automatic CT lung measurements.

In our population of severe ventilated COVID ARDS patients, the IL-6/KL-6 ratio was not clue to differentiate the H, I and L phenotypes and tailor a personalized ventilatory approach. There was an interesting correlation between IL-6/KL-6 ratio and ground-glass volume as determined by automated lung CT analysis. Such correlation deserves more in-depth pathophysiological study, at best gathered from a prospective cohort with a larger sample size and histological analysis.

COVID HUS Trial registration number: NCT04405726.

Emergency medical technicians (EMTs), positioned at the forefront of medical services, are at greater risk of contracting COVID-19 and passing it on to their families and communities than others. Recognizing the risks associated with this disease can play a crucial role in the care and prevention process. Consequently, this study evaluated the level of risk perception (RP) regarding COVID-19 among EMTs and compared it between those who have contracted the disease and those who have not.

This was a cross-sectional descriptive-analytical study conducted in 2021. This study employed simple random sampling to select 200 EMTs affiliated with Birjand University of Medical Sciences. The sample included 100 EMTs who had contracted COVID-19 and 100 who had not. Data were collected through a researcher-designed questionnaire, distributed online via WhatsApp and Telegram groups among the participants. The data were analyzed using SPSS version 16, utilizing descriptive statistical methods (frequency, mean, and standard deviation) along with inferential statistical tests such as independent t-tests, chi-square, and two-way analysis of variance (ANOVA).

The infected EMTs exhibited a moderate perception of the risk of COVID-19, while the non-infected EMTs reported a high level of RP. The independent t-test confirmed that the mean total score for COVID-19 RP was significantly lower in the infected EMTs compared to the non-infected group (mean RP score: infected 150.82 ± 32.24 vs. non-infected 161.54 ± 22.50, P = 0.007). Additionally, ANOVA revealed that none of the demographic variables individually had a significant impact on the level of COVID-19 RP (P > 0.05). Furthermore, the interaction effect between the demographic variables and the groups was also insignificant (P > 0.05).

EMTs who contracted COVID-19 had a significantly lower RP compared to their non-infected counterparts. This reduced awareness of COVID-19 risks likely contributed to their infection, highlighting the critical role of RP in disease prevention. Targeted educational programs to enhance RP among EMTs could foster stronger adherence to preventive measures, ultimately reducing infection rates during future biological disasters. Therefore, this study not only contributes to expanding existing knowledge in this field but also assists policymakers and health administrators in improving decision-making to strengthen epidemic preparedness.

Severe COVID-19 presents with a distinct immunological profile, characterized by elevated neutrophil and reduced lymphocyte counts, seen commonly in fungal and bacterial infections. This study demonstrates that patients hospitalized with COVID-19 show evidence of neutrophil degranulation and have increased expression of neutrophil surface lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), a marker of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). Both early LOX-1 and programmed death-ligand 1 (PD-L1) expression on neutrophils were associated with development of severe disease. To determine whether tissue damage or inflammation is required to induce PMN-MDSCs or whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) directly activates neutrophils to become PMN-MDSCs, we incubated healthy human neutrophils with SARS-CoV-2. SARS-CoV-2 rapidly induced LOX-1 surface expression in healthy neutrophils independent of productive infection. LOX-1 induction was dependent on granule exocytosis and promoted up-regulation of reactive oxygen species, CD63, and PD-L1, enabling LOX-1+ neutrophils to suppress autologous T cell proliferation in vitro. These results support a role for PMN-MDSCs in mediating severe COVID-19, and inhibition of PD-L1 represents a potential therapeutic strategy for enhancing the immune response in acute SARS-CoV-2 infection.

to evaluate the performance of qSOFA in identifying deterioration in patients with COVID-19.

retrospective cohort study conducted between February and August 2020 in the Emergency Department of a private hospital, involving 813 adults. The variables studied included sociodemographic data, clinical characteristics, deterioration, qSOFA on admission and before the event, and outcomes. The performance of qSOFA at both moments was analyzed using the area under the ROC curve.

the average age was 69 years. There was a predominance of men (61.5%), white (97.2%), catholic (73.7%), married (89.6%) and employed (66%). Comorbidities were present in 69.7%, and 58.8% were classified as "urgent" upon admission. The most frequent deterioration was respiratory failure (16.7%), and the outcome was discharge (68%). Patients with positive qSOFA on admission had a higher percentage of respiratory failure, cardiopulmonary arrest, and "very urgent" risk classification, and those with negative qSOFA showed a higher percentage of discharge (p< 0.0001). Upon admission, qSOFA showed 66% sensitivity and 55% specificity, and prior to the event it showed 48% sensitivity and 88% specificity for identifying clinical deterioration. Patients with positive qSOFA on admission were 350 times more likely to experience deterioration.

qSOFA showed low sensitivity for identifying deterioration at both moments and high specificity before the event.

Being widespread across the globe, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) keeps evolving and generating new variants and continuously poses threat to public health, especially to the population with chronic comorbidities. Diabetes mellitus is one of high-risk factors for severe outcome of coronavirus disease 2019 (COVID-19). Establishment of animal models that parallel the clinical and pathological features of COVID-19 complicated with diabetes is thus highly essential. Here, in this study, we constructed leptin receptor gene knockout hamsters with the phenotype of diabetes mellitus (db/db), and revealed that the diabetic hamsters were more susceptible to SARS-CoV-2 and its variants than wild-type hamsters. SARS-CoV-2 and its variants induced a stronger immune cytokine response in the lungs of diabetic hamsters than in wild-type hamsters. Comparative histopathology analyses also showed that infection of SARS-CoV-2 and the variants caused more severe lung tissue injury in diabetic hamsters, and may induce serious complications such as diabetic kidney disease and cardiac lesions. Our findings demonstrated that despite the decreased respiratory pathogenicity, the SARS-CoV-2 variants were still capable of impairing other organs such as kidney and heart in diabetic hamsters, suggesting that the risk of evolving SARS-CoV-2 variants to diabetic patients should never be neglected. This hamster model may help better understand the pathogenesis mechanism of severe COVID-19 in patients with diabetes. It will also aid in development and testing of effective therapeutics and prophylactic treatments against SARS-CoV-2 variants among these high-risk populations.

Human health is influenced by the gut microbiota, particularly in aspects of host immune homeostasis and intestinal immune response. Tryptophan (Trp) not only acts as a nutrient enhancer but also plays a critical role in the balance between host immune tolerance and gut microbiota maintenance. Both endogenous and bacterial metabolites of Trp, exert significant effects on gut microbial composition, microbial metabolism, the host immunity and the host-microbiome interface. Trp metabolites regulate host immunity by activating aryl hydrocarbon receptor (AhR), thereby contributing to immune homeostasis. Among Trp metabolites, AhR ligands include endogenous metabolites (such as kynurenine), and bacterial metabolites (such as indole and its derivatives). Here, we present a comprehensive analysis of the relationships between Trp metabolism and 14 key microbiota, encompassing fungi (e.g., Candida albicans, Aspergillus), bacteria (e.g., Ruminococcus gnavus, Bacteroides, Prevotella copri, Clostridium difficile, Escherichia coli, lactobacilli, Mycobacterium tuberculosis, Pseudomonas aeruginosa, Staphylococcus aureus, Helicobacter. Pylori), and viruses (e.g., SARS-CoV-2, influenza virus). This review clarifies how the gut microbiota regulates Trp metabolism and uncovers the underlying mechanisms of these interactions. And increased mechanistic insight into how the microbiota modulate the host immune system through Trp metabolism may allow for the identification of innovative therapies that are specifically designed to target Trp absorption, Trp metabolites, the gut microbiota, or interactions between Trp and gut microbiota to treat both intestinal and extra-intestinal inflammation as well as microbial infections.

Patients with coronavirus disease-19 (COVID-19) often develop systemic inflammation, which is associated with increased mortality. Elevated blood glucose levels can exacerbate the cytokine storm, further worsening disease severity and accelerating patient death. Therefore, this study aims to investigate the association between glucose levels and mortality in hospitalized patients, providing insights into the importance of optimizing glucose management in hospitalized COVID-19 patients.

A retrospective cohort study was conducted, involving adult COVID-19 patients in a university hospital. The primary outcome was in-hospital mortality. Propensity score matching (PSM) was utilized to match patients' baseline characteristics. Discrimination capacity of different models was assessed using C-statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Trends in blood glucose over time were detected using the ordinary least squares model.

Among the 4583 COVID-19 patients during the study period, 2147 (46.8%) exhibited normal glycemia, while 2436 (53.2%) had admission hyperglycemia. After adjusting for confounding factors through multivariate regression analysis, patients with hyperglycemia showed significantly higher odds of in-hospital mortality (adjusted odds ratio [aOR]: 3.10, 95% CI: 2.25 to 4.28; P < 0.001). PSM analysis yielded similar results (aOR: 2.66, 95% CI: 2.09 to 3.41; P < 0.001). The incorporation of admission glucose significantly improved C-statistics (P < 0.001), IDI (P < 0.001), and NRI (P < 0.001) for predicting mortality.

This study concludes that blood glucose levels ≥ 6.1 mmol/L can independently predict all-cause mortality and clinical sequelae in COVID-19 patients. Furthermore, even a mild increase in blood glucose was associated with a significantly higher risk of mortality in these patients. These findings underscore the importance of managing hyperglycemia and monitoring blood glucose in individuals with COVID-19.

With the COVID-19 pandemic becoming endemic, vigilance for Long COVID-related cardiovascular issues remains essential, though their specific pathophysiology is largely unexplored.

Our study investigates the persistent cardiovascular symptoms observed in individuals long after contracting SARS-CoV-2, a condition commonly referred to as "Long COVID", which has significantly affected millions globally.

We meticulously describe the cardiovascular outcomes in five patients, encompassing a range of severe conditions such as sudden cardiac death during exercise, coronary atherosclerotic heart disease, palpitation, chest tightness, and acute myocarditis.

All five patients were diagnosed with myocarditis, confirmed through endomyocardial biopsy and histochemical staining, which identified inflammatory cell infiltration in their heart tissue. Crucially, electron microscopy revealed widespread mitochondrial vacuolations and the presence of myofilament degradation within the cardiomyocytes of these patients. These findings were mirrored in SARS-CoV-2-infected mice, suggesting a potential underlying cellular mechanism for the cardiac effects associated with Long COVID.

Our findings demonstrate a profound impact of SARS-CoV-2 on mitochondrial integrity, shedding light on the cardiovascular implications of Long COVID.

Patients with ARDS have heterogeneous lungs which exposes them to the risk of lung injury exacerbation by mechanical ventilation. Functional lung CT imaging gives a comprehensive description of regional lung mechanical behaviour. Here, we investigated whether CT registration-based regional lung function parameters are associated with survival in patients with COVID-ARDS.

We conducted a two-centre prospective observational study of adult COVID-ARDS patients with an indication for CT within 72 h of onset. Dual volume CT images were aligned using image-registration. Regional lung functional parameters, and their spatial distributions, were analysed by univariable Cox proportional hazard models with survival as the main outcome. Selected variables based on the univariable analysis were included in a stepwise Cox model adjusted for age, sex, body mass index and SAPSII.

94 patients were included in the study. Recruitment was associated with a higher (HR = 1.45, p = 0.023) hazard of death, while apical (sΔVz) and central (sΔVx) displacement of specific volume change centre-of-mass were associated with a lower hazard of death (HR = 0.72, p = 0.041; HR = 0.68, p = 0.031, respectively).

Our data show that in addition to recruitment, the spatial distribution of specific volume change, a surrogate measure of regional lung ventilation, is associated with the risk of death in mechanically ventilated COVID-19 ARDS patients. Our findings suggest that CT image-registration based functional biomarkers may have prognostic value in COVID-ARDS patients.

This study was retrospectively registered in Clinical Trials under NCT06113276 ( https://clinicaltrials.gov/study/NCT06113276 ) on 27/10/2023.

In the early COVID-19 pandemic, the strain on healthcare facilities highlighted the need for reliable biomarkers to predict progression to severe COVID-19. Neutrophils, the most abundant leukocytes in circulation, are early defenders against pathogens. In a Singaporean adult cohort, early neutrophil mediators were assessed for their suitability as prognostic biomarkers of COVID-19 complications. Plasma levels of myeloperoxidase (MPO), elastase, soluble urokinase plasminogen activator receptor (suPAR), and soluble suppressor of tumorigenicity 2 (sST2) in 35 nonsevere and 14 severe cases were measured twice, 2 to 7 d apart after hospitalization. Nineteen controls were included. The levels of MPO, elastase, suPAR, and sST2 were significantly higher in patients with severe COVID-19 compared with those with mild and healthy controls. At baseline sampling, MPO and suPAR predicted severe COVID-19 and had AUROCs of 0.76 and 0.87, respectively. MPO and suPAR at cut-off values of 26.41 ng/mL and 3.19 ng/mL, respectively showed approximately 71% sensitivity and 81% to 84% specificity to differentiate severe COVID-19. In contrast, elastase and neutrophil counts were less predictive of severe disease. In adult COVID-19, MPO and suPAR may be reliable prognostic biomarkers of severe disease during acute COVID-19. Further validation of these markers in a larger cohort and in other infectious diseases is warranted.

Multidomain lifestyle trials have been shown to be effective in changing people's behaviour during the intervention, but less is known about long-term effects of such interventions. The aim of this study was to investigate how self-reported lifestyle and self-evaluated health changed over a 10-year period in older adults participating in the FINGER randomised controlled trial. Effects of the initial lifestyle intervention and the COVID-19 pandemic on these behaviour changes were evaluated.

A two-year multicentre FINGER trial recruited community-dwelling people aged 60-77 years at risk of cognitive impairment (n=1259). Participants were randomised to a multidomain lifestyle intervention or regular health advice (control). They underwent study visits annually during the original trial period (at baseline, one, and two years) and twice during the follow-up (five and seven years), and responded to a survey during the COVID-19 pandemic at approximately 10 years. Generalised estimating equations (GEE) and linear mixed-effects regression model were used to analyse physical, cognitive, and social activity, food consumption, smoking, alcohol consumption, and self-evaluated health.

People in the intervention group were better able to maintain their level of physical activity up to the five-year follow-up. The intervention group also improved their diet quality: difference in fish consumption was maintained up to the seventh year, and consumption of vegetables and fruits increased during the active intervention. Cognitive and social activities increased and self-evaluated health and memory improved during the active period, but decreased thereafter, without a group difference. During the COVID-19 pandemic, physical and cognitive activities increased.

Multidomain lifestyle intervention was beneficial for improving physical activity and healthy food choices in older people both in the short and long term, but had no effect on other activities, smoking, alcohol use, or self-evaluated health. Increased physical activity was the most evident pandemic-associated change in older adults' lifestyle.

ClinicalTrials.gov, NCT01041989. Registered 04/01/2010 - Retrospectively registered, https://clinicaltrials.gov/ .

Coronavirus disease identified in 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus-2, had a global impact on human health and the economy. The aim of this study was to quantify cytokines, chemokines, and acute phase proteins in the plasma of patients with COVID-19 to elucidate potential biomarkers to inform prognostic and treatment decisions. Clustering analysis using the K-prototypes method identified underlying biological patterns in patients with COVID-19. The penalized multinomial logistic regression analysis identified two comorbidities (hypertension, congestive heart failure) and thirteen analytes as potential risk factors for COVID-19 progression with 88.2% accuracy. Based on a patient's age, high concentrations of interleukin (IL)-6, monocyte chemoattractant protein-1, and pentraxin 3 were important biomarkers for lethal COVID-19. Decreased concentrations of interferon gamma-induced protein-10, IL-10, and soluble tumor necrosis factor receptor I were found to be associated with mild COVID-19, while increasing concentrations of these analytes could be used to predict COVID-19 severity.

Severe COVID-19 typically results in pulmonary sequelae. However, current research lacks clarity on the differences in these sequelae among various clinical subtypes. This study aimed to evaluate the changing lung imaging features and predictive factors in patients with COVID-19 pneumonia in northern China over a 12-month follow-up period after the relaxation of COVID-19 restrictions in 2022.

Imaging and clinically relevant data from three groups (moderate, severe, and critical) of patients with varying severity were prospectively analyzed. Low-dose CT scans were conducted at 3, 6, and 12 months after discharge, with chest CT images evaluated at baseline and each follow-up using qualitative and quantitative analyses. Clinical symptoms and pulmonary function recovery at 12 months were documented. The correlation between lung function and CT results was analyzed. Univariate and multivariable logistic regression analyses were employed to examine factors influencing prognosis, while a post-hoc analysis model was utilized to investigate the relationships among different groups, time points, and chest CT findings.

Among the 103 hospitalized patients with COVID-19 pneumonia, 64 completed the 12-month evaluation. The median age was 63.70 ± 12.15%, and 62.5% (40/64) were men. During the follow-up period, while 67.19% (43/64) showed abnormalities, including fibrotic changes in 9.38% (6/64). Multivariable logistic regression identified age ≥ 65 (OR: 8.66; 95% CI: 1.86, 40.34; P = 0.006), length of hospital stays (OR: 1.23; 95% CI: 1.03, 1.47; P = 0.022), and baseline consolidation volume as a percentage of the whole lung (OR: 56.95; 95% CI: 1.198, 2706.782; P = 0.04) as independent risk factors for persistent CT lung abnormalities at 1 year. After 1 year, 34.38% (22/64) of patients still had abnormal lung function, and 9.38% (6/64) had pulmonary fibrosis and restrictive ventilatory dysfunction. The relationship between lung function and CT findings is weak correlation. The mixed model analysis revealed significant differences between groups, particularly between the moderate and severe groups, and significant changes in CT values over time.

One year after infection, more than one third of even moderate patients with mild symptoms had persistent pulmonary abnormalities. In our study, fibrotic changes were seen in severe and critically ill patients and remained stable 6 months after discharge from hospital. Imaging parameters can predict the prognosis. The larger the extent of baseline consolidation, the worse the prognosis of elderly patients.

The hypoxia-inducible factor-1 alpha (HIF-1 alpha) is a major regulator of adaptive response to hypoxia, common in patients with severe coronavirus disease 2019 (COVID-19). In addition, HIF-1 alpha regulates the expression of the most important proteins necessary for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of cells. The study included 129 hospitalized COVID-19 patients. Genotypes of HIF-1A gene polymorphisms rs11549465 and rs2057482 were determined by the RT-PCR method. We have observed lower mean platelet counts in carriers of HIF-1A rs11549465CC genotype (p = .050) and a significant association of thrombocytopenia with rs11549465CC/rs2057482CT HIF-1A genotypes combination (p = .037) in the group of patients under the age of 40. HIF-1A rs11549465CC genotype and rs11549465CC/rs2057482CT genotype combination could be predictive markers for thrombocytopenia in COVID-19 patients. Identification of such predictive markers for severe disease may contribute to a more efficient response of health systems to the SARS-CoV-2 pandemic.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to a significant burden on global healthcare systems. COVID-19-induced acute kidney injury (AKI) is among one of the complications, that has emerged as a critical and frequent condition in COVID-19 patients. This AKI among COVID-19 patients is associated with poor outcomes, and high mortality rates, especially in those with severe AKI or requiring renal replacement therapy. COVID-19-induced AKI represents a significant complication with complex pathophysiology and multifactorial risk factors. Indeed, several pathophysiological mechanisms, including direct viral invasion of renal cells, systemic inflammation, endothelial and thrombotic abnormalities as well as nephrotoxic drugs and rhabdomyolysis are believed to underlie this condition. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include acute tubular necrosis, glomerular injury, and the presence of viral particles within renal tissue and urine. Identified risk factors for developing AKI vary among studies, depending on regions, underlying conditions, and the severity of the disease. Moreover, histopathological and immunohistopathological findings commonly observed in postmortem studies include show acute tubular necrosis, glomerular injury, and viral particles within renal tissue and urine. While, identified risk factors for developing AKI vary among studies, according to regions, underlying conditions, and the gravity of the disease. This narrative review aims to synthesize current knowledge on the incidence, pathophysiology, risk factors, histopathology, and outcomes of AKI induced by COVID-19.

Amid changing variant and immunity landscapes since early in the coronavirus disease 2019 (COVID-19) pandemic, common COVID-19 symptoms need better understanding in relation to prior immunity or infecting variant.

American Red Cross blood donors were surveyed during February-April 2022 about prior COVID-19 vaccinations and symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Donations were tested for anti-nucleocapsid antibodies to inform infection history. Restricting analysis to donors with survey-reported infections during the Omicron BA.1-predominant period (19 December 2021 through 19 March 2022), we used multivariable logistic regression to compare symptoms by existing immunity from prior infection or vaccination. Restricting analysis to those with no existing immunity, we compared symptoms by variant-predominant period of their first reported infection (BA.1 vs before).

Among 9505 donors with a BA.1-predominant period infection, donors with prior infection (n = 1115), vaccination (n = 5888), or both (n = 1738) were less likely than those without prior immunity (n = 764) to report loss of taste or smell, lower respiratory tract, constitutional, or gastrointestinal symptoms and more likely to report upper respiratory tract symptoms. Stronger associations followed recent prior infection, vaccination, or more vaccine doses. Among 8539 donors without prior immunity, those with survey-reported infections during the BA.1-predominant period (n = 764) were less likely to report loss of taste or smell, or lower respiratory tract symptoms than those with infections before this period (n = 7775).

Our data suggest that both prior immunity and Omicron predominance redistributed COVID-19 symptoms toward upper respiratory tract presentations and likely both contributed to a decrease in COVID-19 severity over time. These findings may better inform COVID-19 identification in high-immunity settings and demonstrate additional benefits of vaccination.

The sensitivity of reverse-transcription polymerase chain reaction (RT-PCR) is limited for diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Chest computed tomography (CT) is reported to have high sensitivity; however, given the limited availability of chest CT during a pandemic, the assessment of more readily available imaging, such as chest radiographs, augmented by artificial intelligence may substitute for the detection of the features of coronavirus disease 2019 (COVID-19) pneumonia.

We trained a deep convolutional neural network to detect SARS-CoV-2 pneumonia using publicly available chest radiography imaging data including 8,851 normal, 6,045 pneumonia, and 200 COVID-19 pneumonia radiographs. The entire cohort was divided into training (n = 13,586) and test groups (n = 1510). We assessed the accuracy of prediction with independent external data.

The sensitivity and positive predictive values of the assessment by artificial intelligence were 96.8% and 90.9%, respectively. In the first external validation of 204 chest radiographs among 107 patients with confirmed COVID-19, the artificial intelligence algorithm correctly identified 174 (85%) chest radiographs as COVID-19 pneumonia among 97 (91%) patients. In the second external validation with 50 immunocompromised patients with leukemia, the higher probability of the artificial intelligence assessment for COVID-19 was correlated with suggestive features of COVID-19, while the normal chest radiographs were closely correlated with the likelihood of normal chest radiographs by the artificial intelligence prediction.

The assessment method by artificial intelligence identified suspicious lung lesions on chest radiographs. This novel approach can identify patients for confirmatory chest CT before the progression of COVID-19 pneumonia.

We previously demonstrated that artificial intelligence (AI)-directed chest computed tomography (CT)-based total opacity scores (TOS) are associated with high-risk obstructive sleep apnea (OSA) based on the Berlin Questionnaire. In the current study, we examined the association between TOS severity and OSA severity based on polysomnography (PSG) recordings among participants with a history of Coronavirus disease-2019 (COVID-19) infection.

This was a post-hoc analysis of 56 patients who underwent CT imaging after being diagnosed with COVID-19 pneumonia as well as overnight PSG for a validation study with a median of 406 days after the initial COVID-19 onset. The AI software quantified the overall opacity scores, which included consolidation and ground-glass opacity regions on CT scans. TOS was defined as the volume of high-opacity regions divided by the volume of the entire lung, and severe TOS was defined as the score ≥15. OSA was defined as an apnea-hypopnea index (AHI) of at least 15 events/h.

In total, 21 participants had OSA and 35 had no OSA. The median TOS was 10.5 [interquartile range (IQR) 1.6-21.2] in the OSA group and 2.8 (IQR 1.4-9.0) in the non-OSA group (P = 0.047). In a multivariate logistic regression analysis, OSA, AHI, and oxygen desaturation index were associated with severe TOS (P < 0.05 for all, respectively) adjusted for age, sex, body mass index, and hypertension.

AI-directed CT-based TOS severity in patients with COVID-19 pneumonia was associated with OSA severity based on PSG recordings. These results support our previous findings suggesting an association between questionnaire-based high-risk OSA and worse outcomes in COVID-19 pneumonia.

It remains unclear about the association between stroke and Coronavirus disease 2019 (COVID-19). Therefore, a Mendelian randomization (MR) analysis was conducted to explore the relationship between them.

In this study, the most recent large-scale genome-wide association studies (GWASs) were selected from the publicly available COVID-19 GWAS meta-analysis (Round 7) as the exposure. Data from a recent original stroke GWAS were used as the outcome for the experimental group, while the stroke GWAS data from the IEU GWAS database were used as the validation group. In addition, an MR analysis was conducted to explore the causal relationships of susceptibility, hospitalization, and severity of COVID-19 with stroke and its subtypes. In addition, the results of the experimental and validation groups were integrated to perform a meta-analysis.

The MR analysis results corroborated that there was a positively causal relationship between the hospitalization (OR, 1.11; p = 0.015) (ORmeta, 1.11; p < 0.001), and severity (OR, 1.06; p = 0.043) (ORmeta, 1.07; p = 0.002) of COVID-19 and cardioembolic stroke (CES). This result is supported by the validation group and sensitivity analysis.

This study demonstrates for the first time that COVID-19 hospitalization and COVID-19 severity are risk factors for CES.

Given their unique phagocytic function, inflammatory site tropism, and ability to penetrate deep into the lesion sites, macrophages are considered to have promising application potential in the field of living-cell drug delivery. The methods of drug delivery using macrophages primarily include intracellular phagocytic and extracellular drug loading. Comparatively, extracellular drug loading is potential less cytotoxicity and has minimal effects on the motility and orientation of cells. In this review, we provide an overview of the methods of extracellular drug loading, and examine the effects of the different properties of nanoformulations on extracellular drug-loaded delivery systems. In addition, we assess the prospects and challenges of a self-propelled macrophage-based drug delivery system. We hope this research contributes to optimizing the design of these drug delivery systems.

Respiratory sequelae, induced by lung injury, reduced muscle strength, and nutritional disturbance, are common in hospitalized patients with coronavirus disease 2019 (COVID-19). Therefore, optimal treatment is essential for reducing the mortality in severe forms of the disease and critically ill patients. Pulmonary rehabilitation (PR) has been used in many chronic respiratory diseases, but the role of early PR in severe and critically ill COVID-19 patients remains to be fully understood.

Hospitalized severe to critically ill COVID-19 patients were recruited from Beijing Chaoyang Hospital between December 1, 2022, and June 30, 2023. In all, we recruited 272 patients, with 39 in the PR group and 233 in the control group. The PR intervention consisted of the prone position, airway clearance therapy (ACT), and resistance respiratory training (RRT). The primary outcome was the composite disease progression outcome rate, defined as death or intensive care unit (ICU) admission. Adverse events (AEs) and serious adverse events (SAEs) were recorded in the PR group. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) was used to balance confounding bias, generating weighting cohort and matched cohort.

The rate of the primary outcome was lower in the PR group (28.2% [11/39] in the PR group vs. 48.9% [114/233] in the control group). Significant differences were observed in both the original and weighting cohorts. Subgroup analyses showed that receiving ≥ 2 types of PR, receiving RRT, length from admission to intervention ≤ 4 days, and baseline P/F ≤ 150 mmHg were associated with lower rates of progression. Total rates of 2.6% (1/39) for AEs and 10.26% (4/39) for SAEs were reported.

Early pulmonary rehabilitation may prevent disease progression and reduce mortality in patients with severe COVID-19. These findings may be helpful for formulating an optimal rehabilitation strategy.

Infectious diseases can sometimes lead to pandemics, often transmitted through public and social gatherings, including in-person hospital visits. Consequently, there is an urgent need for innovative approaches to prevent their spread. Taking COVID-19 as an example, we have explored a remote, contactless hospital online model that offers the public online medical consultations, professional psychological counseling, and chronic disease management consultations, thereby mitigating the risk of new transmissions resulting from hospital visits. This model was implemented, validated, and practiced at West China Hospital in China from 29 January 2020, to 12 March 2020. It was also applicable to other infectious diseases, such as influenza A. In this research, we utilized the hospital's internet platform, supplemented by telephone services, to offer the following to the public: 1) General medical education and consultation related to epidemics and psychological anxiety; 2) Online screening for at-risk populations; 3) Online prescription and medication delivery services for patients with chronic diseases. Consequently, over a period of more than 1 month, the online epidemic platform completed a total of 32,755 cases, including 8,783 internet consultations and 1,082 telephone consultations for the public, as well as 22,890 internet consultations for chronic disease patients. Among these, 289 high-risk individuals were identified, with 3 cases confirmed as COVID-19 during follow-up diagnoses, while no infections were detected in the remaining individuals. In conclusion, this innovative medical model serves as a significant supplement to existing healthcare systems and has the potential to be expanded to other hospitals and other infectious diseases. It is particularly beneficial in scenarios where medical resources are limited, populations are under quarantine, and there is a large demand for medical services and anxiety management during infectious disease pandemics.

The aim of this systematic review and meta-analysis is to synthesize and appraise the evidence on prevalence of cognitive impairment following acute respiratory distress syndrome (ARDS) of any cause.

We systematically searched PubMed, Scopus, and Web of Science for observational studies focused on cognitive impairment in adult survivors of ARDS. Risk of bias and certainty of evidence (GRADE) were assessed. A meta-analysis using a random effects model was performed to estimate the overall prevalence of cognitive impairment after ARDS, with subgroup analyses for COVID-19-related ARDS (C-ARDS). Additionally, a meta-regression was conducted to assess the influence of demographic and clinical predictors on cognitive outcomes. Heterogeneity was assessed using τ2 and the I2 statistic.

We identified 14 studies with 1451 participants, with 650 participants (range: 13-98) included in the analyses. In the subgroup of C-ARDS, 12 studies with 563 participants (range: 13-98) were considered. The pooled prevalence of cognitive impairment following ARDS was 36% (95% CI 26-46%), with high heterogeneity between studies (I2 = 92%, τ2 = 0.03). In C-ARDS cohorts, the prevalence was 34% (95% CI 22-45%), with similar levels of heterogeneity (I2 = 92.7%, τ2 = 0.03). Meta-regression analysis showed  that older age predicted a higher prevalence of cognitive impairment following ARDS (b = 0.02, p = 0.033), reducing between-study heterogeneity (I² = 60.04%, τ² = 0.01). ICU stay, sex, and time from ICU discharge to cognitive assessment showed no significant associations (p > 0.05).

This meta-analysis corroborates previous findings that cognitive impairment remains a persistent issue for ARDS survivors. The prevalence of cognitive impairments following ARDS highlights the importance of future research to unravel the complex underlying mechanisms contributing to these deficits and to develop targeted strategies for prevention and rehabilitation in survivors.

The HDP prediction model was constructed and validated by using the demographic characteristics, blood routine and biochemical screening indicators in early pregnancy to reduce the incidence of HDP. 16,112 pregnant women admitted to Yuyao People's Hospital from May 1, 2018 to April 30, 2022 were randomly divided into modeling group (n = 11279) and validation group (n = 4833) according to a ratio of 7:3. Demographic characteristics, blood routine and biochemical screening data of 8-12+ 6 weeks gestation were obtained from Ningbo Health Records system. Univariate analysis and multivariate binary Logistic regression analysis were used to determine the independent risk factors of HDP, and the scoring system was established by using the nomogram. Univariate analysis and multivariate binary Logistic regression analysis showed that Age, BMI, previous medical history, HB, TG, HDL and ALB were independent risk factors for HDP (P < 0.001). In the modeling group, AUC = 0.809, sensitivity = 74.30%, specificity = 73.10%, and in the validation group, AUC = 0.801, sensitivity = 77.60%, specificity = 68.90%. Hosmer-Lemeshow goodness of fit test showed that modeling group: P = 0.195 > 0.05, validation group: P = 0.775 > 0.05. The prediction model of early pregnancy Age, BMI, previous medical history, HB, TG, HDL and ALB can effectively predict the occurrence of HDP.

Cytokine storm (CS) is a severe systemic inflammatory syndrome characterized by the excessive activation of immune cells and a significant increase in circulating levels of cytokines. This pathological process is implicated in the development of life-threatening conditions such as fulminant myocarditis (FM), acute respiratory distress syndrome (ARDS), primary or secondary hemophagocytic lymphohistiocytosis (HLH), cytokine release syndrome (CRS) associated with chimeric antigen receptor-modified T (CAR-T) therapy, and grade III to IV acute graft-versus-host disease following allogeneic hematopoietic stem cell transplantation. The significant involvement of the JAK-STAT pathway, Toll-like receptors, neutrophil extracellular traps, NLRP3 inflammasome, and other signaling pathways has been recognized in the pathogenesis of CS. Therapies targeting these pathways have been developed or are currently being investigated. While novel drugs have demonstrated promising therapeutic efficacy in mitigating CS, the overall mortality rate of CS resulting from underlying diseases remains high. In the clinical setting, the management of CS typically necessitates a multidisciplinary team strategy encompassing the removal of abnormal inflammatory or immune system activation, the preservation of vital organ function, the treatment of the underlying disease, and the provision of life supportive therapy. This review provides a comprehensive overview of the key signaling pathways and associated cytokines implicated in CS, elucidates the impact of dysregulated immune cell activation, and delineates the resultant organ injury associated with CS. In addition, we offer insights and current literature on the management of CS in cases of FM, ARDS, systemic inflammatory response syndrome, treatment-induced CRS, HLH, and other related conditions.

In recent decades, the potentiality of marine natural products (MNPs) in the medical field has been increasingly recognized. Natural compounds derived from marine microorganisms, algae, and invertebrates have shown significant promise for treating inflammation-related diseases. In this review, we cover the three primary sources of MNPs and their diverse and unique chemical structures and bioactivities. This review aims to summarize the progress of MNPs in combating inflammation-related diseases. Moreover, we cover the functions and mechanisms of MNPs in diseases, highlighting their functions in regulating inflammatory signaling pathways, cellular stress responses, and gut microbiota, among others. Meanwhile, we focus on key technologies and scientific methods to address the current limitations and challenges in MNPs.