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.

for the CoViD-19 Lombardia Team OBJECTIVES: The aims of this study are to report the prevalence of delirium on admission to the unit in patients hospitalized with SARS-CoV-2 infection, to identify the factors associated with delirium, and to evaluate the association between delirium and in-hospital mortality. DESIGN: Multicenter observational cohort study. SETTINGS: Acute medical units in four Italian hospitals. PARTICIPANTS: A total of 516 patients (median age 78 years) admitted to the participating centers with SARS-CoV-2 infection from February 22 to May 17, 2020. MEASUREMENTS: Comprehensive medical assessment with detailed history, physical examinations, functional status, laboratory and imaging procedures. On admission, delirium was determined by the Diagnostic and Statistical Manual of Mental Disorders (5th edition) criteria, 4AT, m-Richmond Agitation Sedation Scale, or clinical impression depending on the site. The primary outcomes were delirium rates and in-hospital mortality. RESULTS: Overall, 73 (14.1%, 95% confidence interval (CI) = 11.0-17.3%) patients presented delirium on admission. Factors significantly associated with delirium were dementia (odds ratio, OR = 4.66, 95% CI = 2.03-10.69), the number of chronic diseases (OR = 1.20, 95% CI = 1.03; 1.40), and chest X-ray or CT opacity (OR = 3.29, 95% CI = 1.12-9.64 and 3.35, 95% CI = 1.07-10.47, for multiple or bilateral opacities and single opacity vs no opacity, respectively). There were 148 (33.4%) in-hospital deaths in the no-delirium group and 43 (58.9%) in the delirium group (P-value assessed using the Gray test <.001). As assessed by a multivariable Cox model, patients with delirium on admission showed an almost twofold increased hazard ratio for in-hospital mortality with respect to patients without delirium (hazard ratio = 1.88, 95% CI = 1.25-2.83). CONCLUSION: Delirium is prevalent and associated with in-hospital mortality among older patients hospitalized with SARS-CoV-2 infection.

The aim of the study is to describe the clinical characteristics and outcomes of a series of older patients consecutively admitted into a non-ICU ward due to SARS-CoV-2 infection (14, males 11), developing delirium. Hypokinetic delirium with lethargy and confusion was observed in 43% of cases (6/14 patients). A total of eight patients exhibited hyperkinetic delirium and 50% of these patients (4/8) died. The overall mortality rate was 71% (10/14 patients). Among the four survivors we observed two different clinical patterns: two patients exhibited dementia and no ARDS (acute respiratory distress syndrome), while the remaining two patients exhibited ARDS and no dementia. The observed different clinical patterns of delirium (hypokinetic delirium; hyperkinetic delirium with or without dementia; hyperkinetic delirium with or without ARDS) identified patients with different prognosis: we believe these observations may have an impact on the management of older subjects with delirium due to COVID-19.

Objectives: To assess the association of pre-morbid functional status [Barthel Index (BI)] and frailty [modified Frailty Index (mFI)] with in-hospital mortality and a risk scoring system developed for COVID-19 in patients !75 years diagnosed with COVID-19. Design: Retrospective bicentric observational study. Setting and Participants: Data on consecutive patients aged !75 years admitted with COVID-19 at 2 Italian tertiary care centers were collected from February 22 to May 30, 2020. Methods: Overall, 221 consecutive patients with COVID-19 aged !75 years were admitted to 2 hospitals in the study period and were included in the analysis. Clinical, functional (BI), frailty (mFI), laboratory, and imaging data were collected. Mortality risk on admission was assessed with the COVID-19 Mortality Risk Score (COVID-19 MRS), a dedicated score developed for hospital triage. Results: Ninety-seven (43.9%) patients died. BI, frailty, age, dementia, respiratory rate, PaO 2 /FiO 2 ratio, creatinine, and platelet count were associated with mortality. Analysis of the area under the receiver operating characteristic (AUC) indicated that the predictivity of age was modest and the combination of BI, mFI, and COVID-19 MRS yielded the highest prediction accuracy (AUC COVID-19MRSþBIþmFI vs AUC Age : 0.87 vs 0.59; difference: þ0.28, lower boundeupper bound: 0.17-0.34, P < .001). Conclusions and Implications: Premorbid BI and mFI are associated with mortality and improved the accuracy of the COVID-19 MRS. Functional status may prove useful to guide clinical management of older individuals.

Patients with OAG may have different temperament profiles than non-clinical individuals. Such categorisation may be useful for predicting how they face the illness, for providing better care as well as for early recognition of mood disorders symptoms.