Search

Background: Gender-related factors might affect vulnerability to Covid-19. The aim of this study was to describe the role of gender on clinical features and 28-day mortality in Covid-19 patients., Methods: Observational study of Covid-19 patients hospitalized in Bergamo, Italy, during the first three weeks of the outbreak. Medical records, clinical, radiological and laboratory findings upon admission and treatment have been collected. Primary outcome was 28-day mortality since hospitalization., Results: 431 consecutive adult patients were admitted. Female patients were 119 (27.6%) with a mean age of 67.0 ± 14.5 years (vs 67.8 ± 12.5 for males, p = 0.54). Previous history of myocardial infarction, vasculopathy and former smoking habits were more common for males. At the time of admission PaO 2 /FiO 2 was similar between men and women (228 [IQR, 134-273] vs 238 mmHg [150-281], p = 0.28). Continuous Positive Airway Pressure (CPAP) assistance was needed in the first 24 h more frequently in male patients (25.7% vs 13.0%; p = 0.006). Overall 28-day mortality was 26.1% in women and 38.1% in men (p = 0.018). Gender did not result an independent predictor of death once the parameters related to disease severity at presentation were included in the multivariable analysis (p = 0.898). Accordingly, the Kaplan-Meier survival analysis in female and male patients requiring CPAP or non-invasive ventilation in the first 24 h did not find a significant difference (p = 0.687)., Conclusion: Hospitalized women are less likely to die from Covid-19; however, once severe disease occurs, the risk of dying is similar to men. Further studies are needed to better investigate the role of gender in clinical course and outcome of Covid-19.

Backgrounds: Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19., Methods and Findings: We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07-1.09), male sex (HR 1.62, 95%CI 1.30-2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39-2.12), diabetes (HR 1.21, 95%CI 1.02-1.45), coronary heart disease (HR 1.40 95% CI 1.09-1.80), chronic liver disease (HR 1.78, 95%CI 1.16-2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002-1.0005). The AUC was 0.822 (95%CI 0.722-0.922) in the derivation cohort and 0.820 (95%CI 0.724-0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp)., Conclusions: A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19., Competing Interests: The authors have declared that no competing interests exist.