Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I² = 0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I² = 0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.

Background: Malnutrition status, body composition indicators, and bioelectrical impedance analysis (BIA) parameters have been associated with increased risk of death in several pathologies. The aim of this study was to describe the associations between phase angle (PhA) indicators obtained by BIA with length of hospital stay, days on mechanical ventilation, and 60-day mortality in critically ill patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: This is a prospective cohort of mechanically ventilated patients with coronavirus disease 2019 (COVID-19). We assessed nutrition risk and body composition with BIA within 48 h from intensive care unit admission. Logistic and linear regression models were used to analyze the association between variables and clinical outcomes.Survival analysis by PhA value was performed using Kaplan-Meier curves.Results: Sixty-seven patients were included. PhA (odds ratio [OR], 0.36; P = .002), standardized PhA (SPA) (OR, 0.45; P = .001), and extracellular water/total body water ratio (OR, 3.25; P = .002) were significant predictors of 60-day mortality. PhA <3.85 • in females and <5.25 • in males showed good and fair discrimination, respectively, for mortality prediction. Using cutoff values, low PhA was associated with a significantly increased risk of 60-day mortality (hazard ratio, 3.08; 95% CI, 1.12-8.41; P = .02). No association was detected for SPA. Conclusion:Low PhA values could be a predictor of 60-day mortality in critically ill patients with COVID-19. This biological marker could be incorporated as part of nutrition and mortality risk assessment in this population.

Background: Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aimed to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. Methods: Rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified published and unpublished RCTs by September 14, 2020 (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, PubMed, Cochrane COVID-19 registry). All-cause mortality was extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine/chloroquine. Prespecified subgroup analyses included patient setting, diagnostic confirmation, control type, and publication status. Results: Sixty-two trials were potentially eligible. We included 16 unpublished trials (1596 patients) and 10 publications/preprints (6317 patients). The combined summary OR on all-cause mortality for hydroxychloroquine was 1.08 (95%CI: 0.99, 1.18; I-square=0%; 24 trials; 7659 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I-square=0%; 4 trials; 307 patients). We identified no subgroup effects. Conclusions: We found no benefit of hydroxychloroquine or chloroquine on the survival of COVID-19 patients. For hydroxychloroquine, the confidence interval is compatible with increased mortality (OR 1.18) or negligibly reduced mortality (OR 0.99). Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), is a global health threat with the potential to cause severe disease manifestations in the lungs. Although COVID-19 has been extensively characterized clinically, the factors distinguishing SARS-CoV-2 from other respiratory viruses are unknown. Here, we compared the clinical, histopathological, and immunological characteristics of patients with COVID-19 and pandemic influenza A(H1N1). We observed a higher frequency of respiratory symptoms, increased tissue injury markers, and a histological pattern of alveolar pneumonia in pandemic influenza A(H1N1) patients. Conversely, dry cough, gastrointestinal symptoms and interstitial lung pathology were observed in COVID-19 cases. Pandemic influenza A(H1N1) was characterized by higher levels of IL-1RA, TNF-α, CCL3, G-CSF, APRIL, sTNF-R1, sTNF-R2, sCD30, and sCD163. Meanwhile, COVID-19 displayed an immune profile distinguished by increased Th1 (IL-12, IFN-γ) and Th2 (IL-4, IL-5, IL-10, IL-13) cytokine levels, along with IL-1β, IL-6, CCL11, VEGF, TWEAK, TSLP, MMP-1, and MMP-3. Our data suggest that SARS-CoV-2 induces a dysbalanced polyfunctional inflammatory response that is different from the immune response against pandemic influenza A(H1N1). Furthermore, we demonstrated the diagnostic potential of some clinical and immune factors to differentiate both diseases. These findings might be relevant for the ongoing and future influenza seasons in the Northern Hemisphere, which are historically unique due to their convergence with the COVID-19 pandemic.