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.

Assessing immune responses across diverse populations is essential for refining public health strategies. Blood donors offer valuable insights into community-level immunity. This study aims to investigate immune responses associated with inactivated COVID-19 booster immunization and breakthrough infections in blood donors. This study was conducted in a cohort of blood donors from six centers across five of China's seven major geographical regions, spanning from December 2021 to February 2023. Blood samples were collected before booster vaccination, at 1, 3, and 6 months post-vaccination, as well as 1 month post-infection. SARS-CoV-2-specific antibodies, T cell specific IFNγ levels, and neutralizing antibodies against wild-type and Omicron strains were measured. Platelet count, anti-PF4 antibody, and D-dimer levels were assessed. Demographic characteristics were analyzed to determine their impact on immunogenicity. SARS-CoV-2-specific antibodies and IFNγ levels significantly increased post-booster, peaking one month after immunization. Antibodies continued to decrease at six months, while IFNγ levels remained stable at this point. Pseudovirus neutralization assays revealed elevated neutralizing antibodies following the booster dose, with minimal response to the XBB.1.5 variant. Following Omicron infection, antibody and IFNγ levels surpassed that observed post-booster. Participants aged 36-49 and those over 50 exhibited weaker immune responses post-booster than those ages 18-35, while those with BMI above 28 showed lower IFNγ levels. This study demonstrates the utility of blood donor samples for tracking immunization effectiveness against emerging pathogens, and highlights enhanced immune responses after booster immunization and breakthrough infections, underscoring the need for tailored vaccination strategies for different groups.

The dynamics of the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) breakthrough infections remain unclear, particularly when compared to responses in naive individuals. In this longitudinal prospective cohort study, 13 participants were recruited. Peripheral blood samples were collected every other day until day 7 after symptom onset. Transcriptome sequencing, single-cell sequencing, T-cell receptor (TCR) sequencing, B-cell receptor (BCR) sequencing, Olink proteomics, and antigen-antibody binding experiments were then performed. During the incubation periods of breakthrough infections, peripheral blood exhibited type 2 cytokine response, which shifted to type 1 cytokine response upon symptom onset. Plasma cytokine levels of C-X-C motif chemokine ligand 10, monocyte chemoattractant protein-1, interferon-γ, and interleukin-6 show larger changes in breakthrough infections than naïve infections. The inflammatory response in breakthrough infections rapidly subsided, returning to homeostasis by day 5 after symptom onset. Notably, the levels of monocyte-derived S100A8/A9, previously considered a marker of severe disease, physiologically significantly increased in the early stages of mild cases and persisted until day 7, suggesting a specific biological function. Longitudinal tracking also revealed that antibodies anti-Receptor Binding Domain (anti-RBD) in breakthrough infections significantly increased by day 7 after symptom onset, whereas cytotoxic T lymphocytes appeared by day 5. This study presents a reference for interpreting the immunological response to breakthrough infectious disease in humans.

This study enrolled 119 elderly patients with severe lower respiratory tract infections (LRTIs) and used machine learning (ML) to evaluate the predictive value of unconventional T lymphocytes (uT cells) in sepsis and 90-day prognosis.

We used random forest (RF) and LASSO analyses to screen model uT cells (identified by RF-LASSO overlapping). The ML models, including LR, LDA, RandomForest, XGBoost, KNN, QDA, NaiveBayes, and ANN, were developed. These models were evaluated and compared based on accuracy, precision, recall, F1 score, sensitivity, specificity, area under the ROC curve (AUROC), and Brier score.

Two T cells were identified as factors of sepsis diagnosis: CD3+ and CD4+CD25+CD127dim. The LDA model demonstrated superior performance, achieving an accuracy of 0.806, AUROC of 0.771, F1 score of 0.720, and a low Brier score of 0.182. Four T cells were identified for predicting the 90-day prognosis: CD3+, CD3+CD4+, CD4+CD28+, and CD4+CD25+CD127dim. For the 90-day prognosis, the LDA model again performed best, with an accuracy of 0.972, F1 score of 0.952, AUROC of 0.935, and a low Brier score of 0.059.

The LDA model is optimal for both diagnosing sepsis and predicting the 90-day prognosis in elderly patients with severe LRTIs. Key T-cell markers identified for sepsis include CD3+ and CD4+CD25+CD127dim, while the 90-day prognosis model includes CD3+, CD3+CD4+, CD4+CD28+, and CD4+CD25+CD127dim T cells. These markers should be prioritized for clinical testing.

Not applicable.

SARS-CoV-2 infections directly or indirectly cause unconscionable vascular events, significantly increasing the morbidity and mortality of COVID-19. Biomarkers associated with cardiac injury often elevate in individuals with COVID-19. Cytokine storm is a mechanism underlying myocardial cell injury caused by SARS-CoV-2 infections. Cell apoptosis in AC16 cells overexpressing structural and helper proteins of SARS-CoV-2 was detected by Western blot, MTT and TUNEL assay. The M protein was determined to play the most pronounced role in inducing apoptosis. Transcriptome sequencing on AC16 cells overexpressing the M protein was performed to screen differentially expressed genes (DEGs), which were further subjected to the gene set enrichment analysis. The regulatory effect of CXCL10 on cell apoptosis of AC16 cells overexpressing M protein was finally explored. Overexpression of M protein significantly increased the Bax/Bcl-2 and cleaved caspase-3/caspase-3(CC3/C3) ratios and the percentage of TUNEL-positive cells in AC16 cells, while markedly reducing cell viability. CXCL10 was the most prominent DEG in AC16 cells overexpressing M protein. Knockdown of CXCL10 partially reversed the increases in the Bax/Bcl-2 and cleaved caspase-3/caspase-3 ratios, the percentage of TUNEL-positive cells, as well as the release of pro-inflammatory cytokines in AC16 cells overexpressing M protein. The M protein of SARS-CoV-2 triggers the production of CXCL10 and apoptosis of myocardial cells.

NETosis, the process through which neutrophils release neutrophil extracellular traps (NETs), has emerged as a crucial mechanism in host defense and the pathogenesis of autoimmune responses. During the SARS-CoV-2 pandemic, this process received significant attention due to the central role of neutrophil recruitment and activation in infection control. However, elevated neutrophil levels and dysregulated NET formation have been linked to coagulopathy and endothelial damage, correlating with disease severity and poor prognosis in COVID-19. Moreover, it is known that SARS-CoV-2 can induce persistent low-grade systemic inflammation, known as long COVID, although the underlying causes remain unclear. It has been increasingly acknowledged that excessive NETosis and NET generation contribute to further pathophysiological abnormalities following SARS-CoV-2 infection. This review provides an updated overview of the role of NETosis in autoimmune diseases, but also the relationship between COVID-19 and long COVID with autoimmunity (e.g., latent and overt autoimmunity, molecular mimicry, epitope spreading) and NETosis (e.g., immune responses, NET markers). Finally, we discuss potential therapeutic strategies targeting dysregulated NETosis to mitigate the severe complications of COVID-19 and long COVID.

Anticoagulants have an important role in the prevention of cardiovascular disorders. Costus speciosus (Costaceae) is a medicinal herb used to treat COVID-19-induced thrombosis. The purpose of this study was to assess the anticoagulant activity of various C. speciosus aqueous (CSAE), ethanol (SCEE), and methanol (CSME) extracts in vivo and in vitro utilizing thrombin time (TT), activated partial thromboplastin time (aPTT), and prothrombin time (PT). Different concentrations of the three extracts were used to evaluate the anticoagulation effects in vitro. In the in vivo assay, male Sprague Dawley rats were used to test the CSME as in vivo anticoagulants. Three groups of rats included the control group and the groups that received CSME daily at a low (200 mg/kg) or high dose (400 mg/kg b.w) for 2 weeks. The molecular docking of the major bioactive constituents of the methanolic extract against the binding site of the thrombin inhibitor complex was evaluated. The HPLC detected 13, 10 and 11 polyphenols in the methanolic, ethanolic and aqueous extracts, respectively. The in vitro results showed that all the studied extracts had anticoagulant activity and increased aPTT, TT, and PT time. The in vivo experiment supported the in vitro results and demonstrated that CSME greatly prolonged the anticoagulant characteristics when compared to the negative control. Both findings suggested that these extracts have significant anticoagulant activity, with CSME being more effective and potentially useful in pharmaceutical applications as a natural anticoagulant medication.

Inborn errors of immunity (IEI) are congenital disorders of the immune system. Due to impaired immune system, they are at a higher risk to develop a more severe COVID-19 course compared to general population.

Herein, we aimed to systematically review various aspects of IEI patients infected with SARS-CoV-2. Moreover, we performed a meta-analysis to determine the frequency of COVID-19 in patients with different IEI.

Embase, Web of Science, PubMed, and Scopus were searched introducing terms related to IEI and COVID-19.

3646 IEI cases with a history of COVID-19 infection were enrolled. The majority of patients had critical infections (1013 cases, 27.8%). The highest frequency of critical and severe cases was observed in phenocopies of IEI (95.2%), defects in intrinsic and innate immunity (69.4%) and immune dysregulation (23.9%). 446 cases (12.2%) succumbed to the disease and the highest mortality was observed in IEI phenocopies (34.6%). COVID-19 frequency in immunodeficient patients was 11.9% (95% CI: 8.3 to 15.5%) with innate immunodeficiency having the highest COVID-19 frequency [34.1% (12.1 to 56.0%)]. COVID-19 case fatality rate among IEI patients was estimated as 5.4% (95% CI: 3.5-8.3%, n = 8 studies, I2 = 17.5%).

IEI with underlying defects in specific branches of the immune system responding to RNA virus infection experience a higher frequency and mortality of COVID-19 infection. Increasing awareness about these entities and underlying genetic defects, adherence to prophylactic strategies and allocating more clinical attention to these patients could lead to a decrease in COVID-19 frequency and mortality in these patients.

Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). This study aimed to develop a machine learning (ML) model that predicts the need for such interventions and compare its accuracy to that of logistic regression (LR).

This retrospective observational study trained separate models using random-forest classifier (RFC), support vector machines (SVMs), Extreme Gradient Boosting (XGBoost), and multilayer perceptron (MLP) to predict three endpoints: eventual use of invasive ventilation, vasopressors, and RRT during hospitalization. RFC-based models were overall most accurate in a derivation COVID-19 CAP cohort and were validated in one COVID-19 CAP and two non-COVID-19 CAP cohorts.

This study is part of the Community-Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) Research program.

Two thousand four hundred twenty COVID-19 and 1909 non-COVID-19 CAP patients over 18 years old hospitalized and not needing invasive ventilation, vasopressors, and RRT on the day of admission were included.

None.

Performance was evaluated with area under the receiver operating characteristic curve (AUROC) and accuracy. RFCs performed better than XGBoost, SVM, and MLP models. For comparison, we evaluated LR models in the same cohorts. AUROC was very high ranging from 0.74 to 0.95 in predicting ventilation, vasopressors, and RRT use in our derivation and validation cohorts. ML used and variables such as Fio2, Glasgow Coma Scale, and mean arterial pressure to predict ventilator, vasopressor use, creatinine, and potassium to predict RRT use. LR was less accurate than ML, with AUROC ranging 0.66 to 0.8.

A ML algorithm more accurately predicts need of invasive ventilation, vasopressors, or RRT in hospitalized non-COVID-19 CAP and COVID-19 patients than regression models and could augment clinician judgment for triage and care of hospitalized CAP patients.

Abnormalities in liver biochemistry are common in COVID-19 patients. Hepatic vein Doppler waveform, typically triphasic, may become biphasic or monophasic in cirrhosis, correlating with liver dysfunction, fibrosis, inflammation, and portal hypertension. This study investigates liver ultrasound (US) features in COVID-19 patients, correlating hepatic vein Doppler waveform and portal vein velocity (PVV) with inflammatory indexes and clinical outcomes.

Fifty-seven patients with SARS-CoV-2 infection participated in a crosssectional study. Bedside upper abdomen US evaluations, including B-mode and Doppler, were conducted using a convex probe. Hepatic vein Doppler waveforms were classified as triphasic, biphasic, or monophasic, and the hepatic vein waveform index (HVWI) was calculated. PVV was measured over three cardiac cycles. Tracings were blindly analyzed by three operators to ensure consistency.

Low HVWI and high PVV correlated with elevated LDH, ALT, D-dimer, and ferritin (p < 0.05). HVWI showed significant negative correlations with ferritin, D-dimer, and ALT (p < 0.05). D-Dimer and ferritin were higher in patients with biphasic/monophasic waveforms (p < 0.05). High PVV and larger spleen diameters predicted worse respiratory outcomes, including CPAP and tracheal intubation (p < 0.05). Optimal cut-off values for PVV (21.7 cm/s) and spleen diameter (9.84 cm) maximized sensitivity and specificity for predicting these outcomes. FIB-4 scores did not correlate with respiratory outcomes or hepatic hemodynamics (p > 0.05). Hemodynamic alterations were not significantly influenced by the presence of SLD (Steatotic Liver Disease).

COVID-19 patients exhibit altered intrahepatic hemodynamics, with hepatic vein waveform abnormalities potentially reflecting liver inflammation and fibrosis. PVV and spleen diameter may serve as non-invasive predictors of respiratory outcomes.

This study aimed to implement a multi-state risk prediction model to predict the progression of COVID-19 cases among hospitalized patients in Kurdistan province by analyzing hospital care data.

This retrospective analysis consisted of data from 17,286 patients admitted to hospitals with COVID-19 from March 23, 2019, to December 19, 2021, in various areas in the Kurdistan province. A multi-state prediction model was used to show that each transition is predicted by a different set of variables. These variables include underlying diseases (like diabetes, hypertension, etc.) and sociodemographic information (like sex and age). Model aims to predict the likelihood of recovery, the need for critical care intervention (e.g., transfer to isolation units or the ICU), or exits from the hospitalization course. We performed the statistical analysis using R software and the mstate package.

Of the hospitalized patients studied, 5.6% died of the disease, 6.6% were admitted to ICUs, and 38.72% were treated in isolation units. Mortality rates in general wards, isolation units, and the ICU were 3.48%, 4.56%, and 26.6%, respectively. Significant predictors for ICU admission include age over 60 years (HR: 1.46, 95% CI 1.37-1.55), kidney-related conditions (HR: 2.19, 95% CI 1.65-2.91), cardiovascular diseases (HR: 1.68, 95% CI 1.46-1.94), lung disease (HR: 1.89,‏95% CI 1.43-2.05), and cancer (HR: 2.46,‏95% CI 1.77-3.41). The likelihood of in-hospital death is significantly increased by age over 60 years (HR: 2.40, 95% CI 2.09-2.76), diabetes (HR: 1.97, 95% CI 1.45-2.68), high blood pressure (HR: 2.30, 95% CI 1.78-2.97), and history of heart disease (HR: 3.01, 95% CI 2.29-3.95).

The model helps the provider and policymakers to make an informed decision depending on patient management and resource allocation within the health care systems.

Understanding vaccination decision-making processes is vital for guiding vaccine promotion within pandemic contexts and for routine immunization efforts. Vaccine-related attitudes influencing individual decision-making can be affected by broader cultural and normative contexts. We conducted 73 qualitative interviews with adults in China (n = 40) and Germany (n = 33) between December 2020 and April 2021 to understand COVID-19 vaccination intentions and preferences, and we analyzed transcripts using a five-step framework approach. During early analysis, we identified moral considerations in line with the tenets of the Model of Moral Motives (MMM) as a recurrent theme in the data. The MMM guided further analysis steps, particularly with its distinction between motives that are proscriptive (focus on avoiding harm by inhibiting "bad" behavior) and prescriptive (focus on actively seeking positive outcomes). Proscriptive vaccination arguments that compelled vaccination in our data included avoiding negative attention, being a law-abiding citizen, preventing harm to others, and protecting one's country. Prescriptive motives focused on self-efficacious behavior such as protecting the health of oneself and others via widespread but voluntary vaccination, prioritizing elderly and predisposed individuals for vaccination, and favoring a fair and equitable distribution of vaccines at the global level. In the interviews in China, both lines of arguments emerged, with a general tendency toward more proscriptive reasoning; interviews conducted in Germany tended to reflect more prescriptive motives. We encourage research and vaccine promotion practice to reflect moral considerations when aiming to understand public health preventive behavior and when developing tailored health promotion campaigns.

The COVID-19 pandemic disrupted healthcare systems and possibly impacted the management of heart failure (HF). This study examined the impact of the pandemic on HF hospitalization activities, outcomes, and costs in Victoria, Australia.

Data on HF hospitalizations were acquired from the Victorian Admitted Episodes Dataset. All consecutive patients hospitalized for HF in both public and private hospitals in Victoria between February 2019 and March 2021 were extracted using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Australian Modification. Data were analysed using descriptive analysis and interrupted time series analysis. A total of 85 564 completed admissions were identified, of which 45 080 were hospitalized in the pre-COVID-19 period and 40 484 were hospitalized in the COVID-19 impacted period. A higher average cost per completed admission in the COVID-19 impacted period was observed, while average length of stay (LOS) was not different between the two periods. It was revealed that monthly total LOS and hospitalization activity cost across all HF admissions dropped at the beginning of the pandemic and continued to decrease until the end of the observation period. However, these changes were not statistically significant.

The impacts of COVID-19 on HF hospitalization activities and associated outcomes at the beginning of the pandemic appeared relatively small and were not sustained. Further studies using other data (i.e. linkage data) are required to understand if, or how, the pandemic impacted on HF management in Australia, especially in the long COVID-19 era.

Type III interferons (IFN-λ), which include IFN-λ1 (or interleukin [IL]-29), IFN-λ2 (IL-28A), IFN-λ3 (IL-28B) and IFN-λ4, exert their effects through a unique receptor complex composed of interferon lambda receptor 1 (IFNLR1) and IL-10 receptor subunit beta (IL-10R2). Studies have highlighted their critical role in modulating immune response, particularly in the context of autoimmune diseases, viral infections and cancer. Unlike type I IFNs, which are broadly expressed, IFN-λ displays a more tissue-specific expression pattern, predominantly acting on epithelial cells and certain immune cell types, such as neutrophils and B cells. This specificity allows IFN-λ to play a pivotal role in mucosal immunity, particularly at barrier sites, such as the respiratory and gastrointestinal tracts. Emerging evidence suggests that IFN-λ has a dual role in both enhancing antiviral immunity and regulating inflammation, thus offering a promising therapeutic strategy for diseases like systemic lupus erythematosus, rheumatoid arthritis, asthma and various cancers. However, the precise mechanisms by which IFN-λ influence immune modulation and disease progression remain an area of active investigation. This review aims to provide an overview of the structure, function and signalling pathways of IFN-λ, exploring their role in immune-related diseases and discussing potential avenues for therapeutic intervention.

Soluble Delta-like ligand 1 (sDLL1) has demonstrated promising results as an early biomarker of bacterial sepsis, but its role in viral infections remains unclear. This study investigated the association between sDLL1 levels and clinical outcomes in patients hospitalized for COVID-19. In this secondary analysis of a single-center prospective observational trial, we measured plasma sDLL1 levels in 46 patients admitted with PCR-confirmed SARS-CoV2 infection between December 2020 and April 2021. Patients were divided into a high-sDLL1 group, upper quartile of patients with the highest measured sDLL1 levels, and low-sDLL1 group, lower three quartiles of patients. Clinical outcomes, including secondary infections, organ dysfunction, and mortality, were compared between groups. Patients in the high-sDLL1 group (n = 11, 24%) showed higher rates of secondary infections (63% vs. 20%, OR 7, CI 1.6 to 31, p = 0.01) with higher odds of pulmonary secondary infections (46% vs. 11%, OR 6.5, CI 1.3 to 31, p = 0.03). Organ dysfunction was more prevalent in the high-sDLL1-group, indicated by a higher maximal Sequential Organ-Failure Assessment (SOFA) score (median (IQR) 11 (8.5-14) vs. 3 (0.5-8), p < 0.01) as well as higher rates of vasopressor support (64% vs. 26%, OR 5.1, CI 1.2 to 21, p = 0.03) and renal replacement therapy (36% vs. 9%, OR 6.1, CI 1.1 to 3.6, p < 0.05). The high-sDLL1 group also showed increased 90-day mortality (45% vs. 11%, OR 6.5, CI 1.3 to 31, p = 0.03). These findings suggest that high levels of sDLL1 are associated with adverse outcomes in viral sepsis, warranting further investigation in larger, prospective studies.

Emerging and re-emerging viruses are currently known as a major public health issue. These viruses can cause various human complications such as cardiovascular diseases (CVDs), both in adults and pediatric populations. Although various CVDs have been previously reported for emerging and re-emerging viruses, the mechanisms underlying these complications remain relatively unknown. Children and infants, while commonly developing less severe symptoms, may experience notable cardiovascular manifestations during infections caused by emerging and re-emerging viral infections, which can result in both acute and long-term complications. The present review aims to discuss various cardiovascular complications linked to emerging and re-emerging viral pathogens (including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dengue virus (DENV), Zika virus (ZIKV), and chikungunya virus (CHIKV)) such as arrhythmias, myocarditis, vascular disorders, and thromboembolic conditions, particularly among the pediatric population. This review also addresses the potential mechanisms by which SARS-CoV-2, DENV, ZIKV, and CHIKV may impact the cardiovascular system and their clinical implications. Moreover, it discusses the diagnostic challenges for viral-caused cardiovascular disorders in children, owing to their common subtle or atypical manifestations. Finally, it addresses the present therapeutic specifically used for pediatric cases.

Cytomegalovirus (CMV) respiratory infection is associated with a high mortality rate. This observational cohort study investigated the long-term survival of patients after CMV respiratory infection and risk factors affecting their prognosis.

Overall, 569 inpatients with CMV respiratory infection enrolled in this study. The prevalence of comorbidities, clinical characteristics, 30-d, 1-year, and 5-year mortality rates, and prognostic risk factors was analysed.

The 30-d, 1-year, and 5-year mortality rates of CMV respiratory infection were 21.6%, 51.4%, and 69.2%, respectively. Based on the different underlying diseases, the 1- and 5-year mortality rates were higher in patients with connective tissue diseases (61.7% vs. 79.4%), post-chemoradiotherapy (56.0% vs. 85.0%), interstitial pneumonia or long-term users of glucocorticoids (55.2% vs. 75.7%), and non-immunocompromised patients (53.8% vs. 68.3%). The 30-d mortality rate had the lowest in organ transplant recipients (6.8%), whereas the 5-year mortality rate was the lowest in patients with nephrotic syndrome (38.3%). Additionally, 76% of CMV infections, 85% of Pneumocystis pneumonia infections, and 70% of Aspergillus pneumonia infections occurred within the first 6 months of glucocorticoid or immunosuppressant use. The presence of interstitial pneumonia, respiratory failure, high Pneumonia Severity Index (PSI) and CURB-65 scores, and persistent lymphocytopenia were indicative of a poor 30-d prognosis, while post-organ transplantation was associated with a favourable prognosis.

The mortality rate of CMV respiratory infection was found to be high, especially in patients with connective tissue diseases, cancer chemotherapy and radiation therapy, interstitial pneumonia, and non-immunocompromised patients. In patients on long-term immunosuppressants and corticosteroids, particularly within the first 6 months, vigilance needs to be exercised for CMV respiratory infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with endothelial dysfunction, which may also compromise the microcirculation within ocular tissues. This prospective study evaluated associations between radial peripapillary capillary (RPC) vessel density (VD) and systemic treatment, age, hypoxia, D-dimer, and interleukin-6 (IL-6) levels in patients recovering from coronavirus disease 2019 (COVID-19) related pneumonia.

Sixty-three individuals who were admitted to the hospital due to COVID-19 bilateral pneumonia underwent ophthalmic examination two months post-discharge. RPC VD was measured using optical coherence tomography angiography. Associations with age, arterial hypertension, and systemic treatment (dexamethasone, remdesivir, and oxygen therapy), oxygen saturation, D-dimer, and IL-6 levels were evaluated. The control group comprised 43 control participants with no history of COVID-19 who attended routine ophthalmic examinations.

No ophthalmic abnormalities were detected. RPC VD did not differ significantly with hypertension or systemic treatment with dexamethasone and remdesivir. However, patients receiving oxygen therapy had higher RPC VD. A borderline inverse correlation was observed between inferior RPC VD and age. There were no correlations between RPC VD and oxygen saturation. Significant inverse correlations were found between nasal RPC and mean RPC with D-dimer levels and between inferior RPC VD and IL-6 levels. No significant differences in RPC parameters were observed when comparing the COVID-19 group with controls.

Hypertension or systemic treatment had no significant effect on RCP VD. However, VD in specific RPC areas correlated inversely with D-dimer and IL-6 levels, highlighting the need for monitoring peripapillary microvasculature for potential long-term ocular effects of COVID-19.

Coronary calcification, as defined by computed tomography (CT), can be quantified with a score (CAC score). It is an established prognostic and predictive imaging marker of the cardiovascular risk profile. The prognostic relevance of the CAC score has been demonstrated for acute diseases, including the coronavirus disease 2019 (COVID-19) in preliminary studies. The aim of the present study was to prove the prognostic relevance of the CAC score in patients with coronavirus disease 2019.The present study used a nationwide radiological research platform to conduct a multicenter retrospective study. The study included a total of 541 patients, 176 of whom were female (32.5%). The mean age of the patients was 61.2 years ± 15.6 years. The coronavirus (SARS-COV-2) disease was confirmed in all patients by PCR testing. The CAC score was calculated using the Weston score, which is a semiquantitative method. The primary outcome of the study was 30-day mortality.The overall mortality rate within the 30-day period was 21.2%, with 115 patients dying. The mean Weston score was 3.0 ± 3.6. 128 patients (23.7%) exhibited no evidence of coronary calcifications, as indicated by a Weston Score of 0. In the univariable regression analysis, the presence of calcifications was found to be associated with mortality, with an odds ratio of 1.68 (95% confidence interval 1.08-2.59, p=0.01). However, this result did not remain statistically significant in the multivariable analysis (p=0.49). The Weston score was found to be associated with mortality in the univariable analysis, with an odds ratio (OR) of 1.10 (95% CI 1.04-1.14, p < 0.001), and in the multivariable analysis, with an OR of 1.06 (95% CI 1.005-1.138, p = 0.036).The imaging marker CAC score has been demonstrated to have a significant prognostic impact on 30-day mortality in patients diagnosed with coronavirus disease 2019 (COVID-19). It is incumbent upon the radiologist to acknowledge the sole presence of coronary calcifications as a relevant prognostic factor. The prognostic relevance of the calcifications was found to be greater in cases where more extensive calcification was present. · Coronary calcifications assessed by CT are prognostic markers for 30-day COVID-19 mortality.. · Calcification extent has greater prognostic value than the mere presence of calcifications.. · The study highlights the need to integrate coronary calcifications into clinical risk scores.. · Bucher AM, Frodl E, Ehrengut C et al. Prognostic value of CT-defined coronary sclerosis in COVID-19: results of a multicenter study based on the Weston score. Rofo 2025; DOI 10.1055/a-2583-0235.

A significant proportion of patients who are hospitalized with coronavirus disease 2019 (COVID-19), particularly those being admitted to ICUs, exhibit the development of secondary bacterial infections (SBIs). However, there is a lack of detailed epidemiological investigations and genetic information of Carbapenem-Resistant Acinetobacter baumannii (CRAB) based on whole genome sequencing (WGS), which is one of the frequently detected bacteria among COVID-19 patients, to confirm alterations in the clonal structure and infection mechanism.

A total of 37 unique CRAB strains, sourced from patients, along with an additional 2 CRAB strains form the environment, were isolated. Among the cohort of 37 patients, 22 individuals succumbed to CRAB infection, resulting in a mortality rate of 54.46%. The median duration of illness for these patients was 7.95 days, highlighting the severity and rapid progression of CRAB infections in this patient population. A total of 22 CRAB strains, isolated from deceased individuals, in addition to two strains isolated from the environment, were subjected to further investigation. All 24 CRAB isolates exhibited a high ability to form biofilm and displayed a similar spectrum of resistance. Except for two isolates from patients with COVID-19, all the remaining CRAB isolates were categorized as ST195 and demonstrated highly close genetic background based on analysis of WGS. The ST195 strain of CRAB harbored three copies of the blaOXA-23 gene located on the chromosome, each of which was carried by Tn2006. Notably, one Tn2006 element was integrated within Tn6022, leading to the formation of AbaR4-like resistance islands Tn6166-I.

Our findings underscore the significance of SBIs in the COVID-19 pandemic, particularly those caused by CRAB and specifically those belonging to MLST types that were previously prevalent in ICUs.

This study aimed to develop a predictive model for secondary infections in patients with severe or critical COVID-19 by analyzing clinical characteristics and laboratory indicators.

A total of 307 patients with severe or critical COVID-19 admitted to Peking University Third Hospital from December 2022 to February 2023 were retrospectively analyzed, including 156 patients with secondary infection and 151 patients without secondary infection. The Boruta algorithm identified significant variables, and eight machine learning models were evaluated based on area under the curve (AUC) performance. The optimal model selected was further assessed, with model interpretability provided using SHapley Additive exPlanations (SHAP).

Nine predictive factors were identified: Mechanical Ventilation, Procalcitonin (PCT), Interleukin-8 (IL-8), Interleukin-6 (IL-6), Blood Urea Nitrogen, Glucose, Creatine Kinase, Lactate Dehydrogenase, and Mean Platelet Volume (MPV). The random forest model demonstrated the best performance, with further evaluation showing an average AUC of 0.981 (CI 0.965-0.998) on the training set and 0.836 (CI 0.761-0.912) on the test set. SHAP analysis identified MPV, PCT, and IL-8 as the strongest predictors of secondary infections.

We developed an effective predictive model for secondary infection risk in severe COVID-19 patients using readily available clinical parameters, enabling early clinical intervention. This machine learning approach demonstrates potential for improving patient management.

This study does not involve clinical trial interventions. Therefore, clinical trial registration was not applicable.

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.

Population-based data are needed to reliably assess the impact of SARS-CoV-2 infection during pregnancy.

To estimate the population-based incidence of SARS-CoV-2 infection and its severe forms in the obstetric population, identify risk factors of severe SARS-CoV-2 infection (severe COVID-19) and describe delivery, maternal and neonatal outcomes by disease severity, using a definition of severity based on organ dysfunction.

A prospective population-based study conducted over the three first pandemic waves between March 2020 and April 2021 in 281 maternity hospitals in six French regions included all women with SARS-CoV-2 infection during pregnancy or within 7 days post-partum, whether symptomatic or not, hospitalised or not. Severe COVID-19 forms were defined a priori using clinical, biological and management criteria of organ dysfunction. We calculated infection and severe infection rates and studied associations between sociodemographic, medical and pregnancy characteristics and severe COVID-19 by univariate and multivariate modified Poisson regression modelling.

From a population of 385,214 deliveries in the participating regions, 6015 women with SARS-CoV-2 infection were identified, including 337 severe cases. The rates of severe COVID-19 were 1.1, 0.9 and 3.6 per 1000 deliveries during the first, second and third pandemic waves, respectively, and the proportions of severe COVID-19 were 8.6%, 3.4% and 9.3%, respectively. On multivariate analysis, the risk of severe COVID-19 was associated with younger and older age, migrant status, living with > 4 people, overweight or obesity, chronic hypertension or diabetes and infection ≥ 22 weeks of gestation rather than earlier in pregnancy. Neonatal morbidity occurred mostly with severe maternal infection.

Using an organ-based definition of severity and population-based data, rates of severe COVID-19 appeared lower than in previous studies. A permanent perinatal surveillance system is needed to assess efficiently and rapidly the impact of future pandemics.

Reports of prolonged SARS-CoV-2 nucleic acid detection have been described. Of 175 adult patients readmitted after being hospitalized with COVID-19 between March 2020 and June 2021, 35 had positive SARS-CoV-2 nucleic acid amplification test (NAAT) 30 days or more from their initial NAAT. Higher albumin levels at the initial hospitalization were associated with a decreased risk of prolonged viral detection.

SARS-CoV-2 and its subvariants continue to spread globally. People living with HIV (PLWH), who have weakened immune systems, have heightened concerns about the virus. Thus, the relationship between COVID-19 and HIV remains unclear, and the risks of COVID-19 for PLWH have yet to be fully understood. The study conducted a retrospective cross-sectional survey on the Wenjuanxing platform to identify lifestyle risk factors and epidemic phenotypes associated with the severity of COVID-19 in PLWH. All respondents were over 18 years old and were receiving antiretroviral therapy. The survey included questions about their health status during the COVID-19 illness, and questions about basic sociodemographic information, lifestyle factors, and HIV treatment history. This study included 984 HIV patients with a mean age of 54.44 ± 14.4 years. Among the participants, 635 (64.53%) were male. A total of 33 (3.35%) respondents were unvaccinated, while 951 (96.65%) had received at least one vaccine dose, with 868 (88.21%) participants having received three or more vaccine doses. The association between the severity of COVID-19 symptoms and CD4 count (p = 0.652) and HIV viral load (p = 0.916) was found to be statistically insignificant. In reduced multivariate logistic model, passive smoking increased the risk of severe COVID-19 symptoms compared with non-smokers (odds ratios [OR] 1.66; 95% confidence interval [CI] 1.11-2.48). Mild (OR 2.23; 95% CI 1.55-3.24) and moderate/severe anxiety (OR 5.22; 95% CI 2.36-13.28) were also positively associated with severe COVID-19 symptoms compared to individuals with no anxiety. Comorbidity (OR 1.5; 95% CI 1.04-2.17) demonstrated a significant association with severe COVID-19 symptoms. Moderate/severe anxiety was significantly associated with a higher hospital admission rate (OR 2.62; 95% CI 1.27-5.37) compared to those without anxiety. Patients who consumed whole grains more than three times per week had a lower risk of hospital admission (OR 0.61; 95% CI 0.41-0.89). However, both anxiety and wholegrain intake were nonsignificant for hospitalization rates in individuals who tested positive for COVID-19 through real-time PCR or antigen test. In full multivariate logistic model for SARS-CoV-2 infection of hospitality, CD4 count (> 500 cells/mm3) (OR 0.64; 95% CI 0.41-0.99) and the CD4 count (200-500 cells/mm3) (OR 0.68; 95% CI 0.45-1.04) were significantly associated with hospital admission rates compared to CD4 count (< 200 cells/mm3), but the results were inconsistent in the reduced logistic models and analysis of Group B. This study indicates that anxiety is positively associated with worsened COVID-19 symptoms and higher hospitalization rates, suggesting a significant link between anxiety and the severity of COVID-19. However, the study did not find evidence of a correlation between CD4 count, HIV viral load, and the severity of COVID-19 or hospitalization rates.

COVID-19 is caused by SARS-CoV-2 and has a diverse spectrum of clinical presentations ranging from asymptomatic cases to severe and critical cases that result in the death of the patient. Alongside the viral factors host factors like Age, deregulation of the immune response and presence of comorbidity determine the patient's outcome. Here we sought to assess the impact of age on natural antibody response, CBC-based inflammatory markers, and outcome of COVID-19 patients. We divided the participants into three groups, young (≤ 35 years), middle-aged (40-60 years), and old (≥ 65 years) patients and collected and analyzed sociodemographic, clinical, and laboratory parameters. We found that elderly patients showed higher (P < 0.05) levels of inflammation like increased neutrophil percentages, NLR, lymphopenia, and low Hgb levels, compared to middle-aged and young patients. Interestingly these markers were also associated with mortality of COVID-19 patients. On the other hand, no significant difference was observed in ion concentration, lipid profile, and coagulation test between the three age groups. We also found that elderly patients showed significantly (P < 0.05) decreased levels of natural antibody response to SARS-CoV-2 infection compared with the two groups. Lastly, we assessed the effect of dexamethasone treatment, even if statistically not significant (P > 0.05) we observed a positive trend among patients under dexamethasone in the aspect of decreasing inflammatory markers. To conclude we showed that SARS-CoV-2 is characterized by an age-dependent deregulation of inflammatory markers that are associated with mortality among COVID-19 patients.

to analyze the factors associated with mortality in patients with cardiovascular disease affected by Coronavirus Disease-2019.

this was a cross-sectional study using data from the monitoring of notifications during the pandemic. The sample included cases with cardiovascular comorbidity and clinical outcomes. The dependent variable was the progression of the case to death. Associations were tested using the binary logistic regression method, using the Odds Ratio.

the prevalence was female (50.6%), elderly (71.1%), self-declared non-white (71.0%), with multiple comorbidities associated with cardiovascular disease (60.3%), diabetes being the main one (44.8%). The study suggests that patients who were men (OR 1.13; p = 0.028), elderly (OR 2.57; p = 0.000), self-declared white (OR 1.71; p = 0.000), and had multiple comorbidities (OR 1.70; p = 0.000) were associated with a greater chance of death.

the factors associated with a higher chance of death were related to gender, age group, and the presence of comorbidities, showing the vulnerability of this population to infection.

Background/Objectives: SARS-CoV-2 infection has the potential to cause multi-organ involvement and, when associated with Epstein-Barr virus (EBV) coinfection, may worsen the course of disease in pediatric patients by influencing the immune response. Methods: Our retrospective-observational study included 406 hospitalized children with post-COVID-19 status or SARS-CoV-2/EBV coinfection. Results: Hypovitaminosis D was more common in the coinfected sublot (59.18%) than in the COVID-19 one (50.74%), with a higher frequency of severe vitamin D deficiency (16.33% vs. 7.35%). Hypovitaminosis D was significantly associated with female sex (p = 0.033) only in the COVID-19 subgroup. Hypervitaminosis D, although rare, was only associated with severe forms of the disease (7.69%). Between clinical severity and vitamin D level, a statistically significant association of moderate intensity was identified only in the COVID-19 subgroup (χ2 = 11.708, φ = 0.293, p = 0.020). In the same subgroup, a significant correlation was found between vitamin D levels and serum potassium values (χ2 = 10.527, p = 0.032). Moreover, in the COVID-19 subgroup, an association between abnormal sodium levels and increased D-dimer levels was found (χ2 = 7.074, p = 0.029). Conclusions: These results underline the importance of monitoring immunologic, vitamin, and electrolyte imbalance in the management of these cases and highlight the need for personalized therapeutic strategies to prevent long-term complications.

Sepsis, defined as a dysregulated host response to infection, is one of the leading causes of mortality worldwide. It unleashes in the organism a cascade of molecules, cytokines, and proteins which leads to an inflammatory storm. If this response to infection is uncontrolled, any organ is susceptible to damage. Acute kidney injury (AKI) is one of the most frequent organ dysfunctions in septic patients, and while it can be reversible, its presence leads to a higher burden of morbidity and mortality. While serum creatinine is essential in evaluating kidney function, the pathophysiology of AKI is not completely elucidated, and a plethora of novel biomarkers have been studied in the hope of an early diagnosis and fast treatment. While the liver is not as affected by sepsis, it plays an important role as a guardian by providing acute-phase proteins, activating neutrophils, and controlling iron balance. Acute liver failure (ALF) could impair the organism's capacity to contain and eliminate pathogens. Some molecules have been associated with either AKI or ALF, although biomarkers specific for organ dysfunction are difficult to validate. The aim of this review is to understand the role of several molecules in the pathophysiology of sepsis and their clinical ability for diagnosing or predicting sepsis-induced hepato-renal dysfunction.

Although much is known about the pathophysiology of severe COVID-19, there are still areas that remain to be determined. It is well established that the pivotal molecular event is a hyperinflammatory response also referred to as a cytokine storm. The aim of this retrospective cohort study was to determine miRNAs which might be predictive for the admission to the intensive care unit (ICU). We analyzed blood samples from 210 COVID-19 patients and the control group consisted of 80 healthy individuals. Results revealed the miRNA expression pattern has the potential to predict the severity of COVID-19, reflecting the clinical symptoms of the infection, such as the need for oxygen therapy and concomitant pneumonia. In particular, low expression of miRNAs miR106a-5p, miR17-5p, miR181a-5p, miR191-5p, miR20a-5p and miR451a, especially in the initial phase of the disease, is associated with an unfavorable clinical course of SARS-CoV-2 infection (admission to the ICU).

COVID-19 progression and recovery involve complex gene expression changes and immune dysregulation, but their dynamic alterations remain poorly understood. Current clinical indicators lack precision in distinguishing severe cases, highlighting the need for molecular biomarkers and diagnostic tools.

Three transcriptomic datasets were analyzed: 1) COVID-19 progression from Healthy, Moderate, Severe, to ICU patients; 2) recovery stages (1, 3, and 6 months) compared to Healthy controls; and 3) COVID-19 ICU versus non-ICU patients. Differential expression analysis, immune cell infiltration estimation, machine learning (LASSO regression and random forest), and functional enrichment were used to identify key genes and molecular mechanisms.

Gene expression analysis revealed dynamic changes during COVID-19 progression. Adaptive immune cells (e.g., B cells and T cells) decreased, while innate immune cells (e.g., monocytes and neutrophils) increased, particularly in ICU patients. Recovery analysis showed significantly reduced adaptive immune cells at 1 month, with partial recovery by 3 and 6 months. Machine learning identified CCR5, CYSLTR1, and KLRG1 as diagnostic biomarkers for distinguishing ICU from non-ICU patients, with AUC values of 0.916, 0.885, and 0.899, respectively.

This study identified CCR5, CYSLTR1, and KLRG1 as efficient diagnostic biomarkers for severe COVID-19 using machine learning and revealed immune regulatory features across COVID-19 progression and recovery.

This study aimed to analyze the characteristics of patients who fail high-flow nasal cannula(HFNC) therapy for acute hypoxemic respiratory failure(AHRF) and to identify predictors of treatment failure.

This single-center, retrospective, observational study analyzed clinical data from 388 patients with AHRF. Patients were divided into two groups: the HFNC success group (HFNC-S, n = 256) and the HFNC failure group (HFNC-F, n = 132). The primary endpoint was the need for escalation of respiratory support to tracheal intubation in the enrolled patients. The demographic data, laboratory tests, blood gas analysis data, CT severity scores, and disease severity scores were analysed to determine the difference between patients who were successful and those who failed HFNC treatment. Univariate and multivariate logistic regression models were used to assess potential predictors of failure of HFNC for patients with acute hypoxaemic respiratory failure.

The mean age of patients enrolled was 67.97 ± 14.40 years. The HFNC-F group had significantly higher PSI(Pneumonia Severity Index) score, CURB(Confusion, Urea, Respiratory Rate, Blood Pressure, and Age)-65 score, CPIS(Clinical Pulmonary Infection Score) score, CT score and SOFA(Sequential Organ Failure Assessment) scores compared to the HFNC-S group. Within 12 h of the initiation of treatment, the HFNC-F group exhibited significantly lower oxygen saturation index (PaO2/FiO2) and significantly higher respiratory rate. Additionally, the HFNC-F group exhibited significantly higher levels of C-reactive protein (CRP), platelet count (PLT), D-dimer, interleukin-10 (IL-10), total bilirubin (TB) and creatinine (CB), but lower albumin levels. Multivariate analysis identified CT score, SOFA score, interleukin-1β (IL-1β), and albumin as independent predictors of HFNC failure.

HFNC is effective for treating AHRF. CT score, SOFA score, IL-1β, and albumin are independent predictors of HFNC failure.

Middle-aged  and elderly patients with cardiovascular disease (CVD) who have recovered from SARS-CoV-2 infection may experience depressive symptoms due to the physical and psychological impact of the pandemic.

To investigate the prevalence and predictors of depressive symptoms among the middle-aged and elderly with CVD who have recovered from SARS-CoV-2 infection in Wuhan, China, and to develop a prediction model for depressive symptoms.

A cross-sectional study was conducted among 462 former SARS-CoV-2 middle-aged and elderly patients with CVD in Jianghan District, Wuhan, China from June 10 to July 25, 2021. Depressive symptoms were assessed by the Patient Health Questionnaire-9 (PHQ-9). Potential predictors of depressive symptoms were selected by the least absolute shrinkage and selection operator (LASSO) regression. A prediction model was developed by random forest (RF) and logistic regression models and compared by the area under the receiver operating characteristic curve (AUROC). The discrimination, calibration, and practical utility of the prediction model were evaluated by the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Bootstrap sampling was used for internal validation.

The prevalence of depressive symptoms among the participants was 35.93%. The prediction model included age, stethalgia after recovery, insomnia after recovery, post-traumatic stress disorder (PTSD), anxiety, fatigue, and perceived social support as predictors. The AUROC of the logistic regression model was 0.909 (95%CI: 0.879 ~ 0.939), indicating good discrimination. The calibration curve showed good calibration. The DCA showed that the prediction model had a net benefit for a wide range of risk thresholds. The internal validation confirmed the stability of the prediction model.

Depressive symptoms are common among middle-aged and elderly CVD patients who have recovered from SARS-CoV-2 infection in Wuhan, China. A prediction model with satisfactory performance was developed to estimate the risk of depressive symptoms among this population. Interventions targeting long COVID symptoms and social support should be considered to prevent depressive symptoms in CVD patients.

This study aims to identify parameters predicting COVID-19 inflammation score (CIS) response and survival probability in critically ill patients with hyperinflammation treated with the Janus kinase (JAK) 1/2 inhibitor ruxolitinib. This is a single arm, non-randomized, open-label, phase-II study for frontline treatment in adults in the intensive care unit (ICU). Ninety-two critically ill COVID-19 patients with CIS ≥ 10 were treated in the RuxCoFlam trial (NCT04338958) with ruxolitinib between April 2020 and June 2021. Median ICU treatment duration was 15 days (range, 2-73). Out of 81 evaluable patients, 62 (77%) showed CIS reduction ≥ 25% on day 7 (CIS response). In multiple logistic regression analyses, higher CIS on day 0 (odds ratio (OR), 1.56; 95% confidence interval (CI), 1.01-2.41; p = 0.046) and male gender (OR, 4.76; 95% CI, 1.22-16.67; p = 0.024) were significantly associated with CIS response. Sixty-day survival probability was higher in CIS-responders compared to non-responders (74% vs. 32%; p < 0.001). Multiple Cox regression analysis revealed younger age (10-year difference) (hazard ratio (HR), 0.65; 95% CI, 0.46-0.91; p = 0.012) and CIS response (HR, 0.19; 95% CI, 0.08-0.45; p < 0.001) as significant parameters for survival probability. In conclusion, reduced risk of death in CIS-responders underlines the usefulness of CIS for the assessment of hyperinflammatory disorders, such as COVID-19, under JAK1/2 inhibitor therapy.