ObjectivesSeveral physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage.SettingRetrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020.ParticipantsConsecutive patients≥18 years admitted for COVID-19.Main outcome measuresSimple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS).ResultsMean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001).ConclusionsThe COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.

Purpose COVID-19 is a novel threat to patients with adrenal insufficiency (AI), whose life expectancy and quality (QoL) are impaired by an increased risk of infections and stress-triggered adrenal crises (AC). If infected, AI patients require prompt replacement tailoring. We assessed, in a cohort of AI patients: prevalence and clinical presentation of COVID-19; prevalence of AC and association with intercurrent COVID-19 or pandemic-related psychophysical stress; lockdown-induced emotional burden, and health-related QoL. Methods In this monocentric (Ancona University Hospital, Italy), cross-sectional study covering February-April 2020, 121 (40 primary, 81 secondary) AI patients (59 males, 55 ± 17 years) completed telematically three questionnaires: the purposebuilt "CORTI-COVID", assessing medical history and concern for COVID-19-related global health, AI-specific personal health, occupational, economic, and social consequences; the AddiQoL-30; the Short-Form-36 (SF-36) Health Survey. Results COVID-19 occurred in one (0•8% prevalence) 48-year-old woman with primary AI, who promptly tailored her replacement. Dyspnea lasted three days, without requiring hospitalization. Secondary AI patients were not involved. No AC were experienced, but pandemic-related stress accounted for 6/14 glucocorticoid up-titrations. Mean CORTI-COVID was similar between groups, mainly depending on "personal health" in primary AI (ρ = 0.888, p < 0.0001) and "economy" in secondary AI (ρ = 0.854, p < 0.0001). Working restrictions increased occupational concern. CORTI-COVID correlated inversely with QoL. AddiQoL-30 and SF-36 correlated strongly. Comorbidities worsened patients' QoL. Conclusion If educational efforts are made in preventing acute events, AI patients seem not particularly susceptible to COVID-19. The novel "CORTI-COVID" questionnaire reliably assesses the pandemic-related emotional burden in AI. Even under unconventional stress, educated AI patients preserve a good QoL.