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Coronavirus disease of 2019 (COVID-19) is associated with severe acute respiratory failure. Early identification of high-risk COVID-19 patients is crucial. We aimed to derive and validate a simple score for the prediction of severe outcomes. A retrospective cohort study of patients hospitalized for COVID-19 was carried out by the Italian Society of Internal Medicine. Epidemiological, clinical, laboratory, and treatment variables were collected at hospital admission at five hospitals. Three algorithm selection models were used to construct a predictive risk score: backward Selection, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. Severe outcome was defined as the composite of need for non-invasive ventilation, need for orotracheal intubation, or death. A total of 610 patients were included in the analysis, 313 had a severe outcome. The subset for the derivation analysis included 335 patients, the subset for the validation analysis 275 patients. The LASSO selection identified 6 variables (age, history of coronary heart disease, CRP, AST, D-dimer, and neutrophil/lymphocyte ratio) and resulted in the best performing score with an area under the curve of 0.79 in the derivation cohort and 0.80 in the validation cohort. Using a cut-off of 7 out of 13 points, sensitivity was 0.93, specificity 0.34, positive predictive value 0.59, and negative predictive value 0.82. The proposed score can identify patients at low risk for severe outcome who can be safely managed in a low-intensity setting after hospital admission for COVID-19.

International guidelines recommend the use of pharmacological prophylaxis in hospitalized medical patients at high risk of venous thromboembolism (VTE). The same international guidelines suggest the employment of standardized risk assessment models (RAMs) when evaluating the administration of pharmacological prophylaxis in acutely ill medical patients. The Padua Prediction Score and the Improve Bleeding Score have been indicated as the best available RAMs to predict thrombotic and haemorrhagic risk in hospitalized medical patients, but it is still unknown whether their combined use may lead to a significant reduction in thrombotic and haemorrhagic events. It is also unclear whether their extensive use can affect to some extent health expenditure associated with pharmacological VTE prophylaxis. The purpose of this single-centre, prospective and retrospective observational study is to investigate these unanswered questions. All patients admitted to our Internal Medicine Department between May 2015 and August 2015, i.e., before the introduction and extensive use of RAMs, were consecutively enrolled (retrospective group). Similarly, all patients admitted between November 2016 and February 2017-once RAMs clinical use became a consolidated practice-have also been consecutively recruited (prospective group). Consecutively, 203 patients were enrolled in the retrospective group and 210 patients were enrolled in the prospective group. Three events of major bleeding and one event of pulmonary embolism were observed in the prospective group; three events of major hemorrhage and two events of pulmonary embolism were observed in the retrospective group (p = not significant). A statistically significant decrease in pharmacological VTE prophylaxis among study groups was detected: 43.3% of prospective group patients and 56.7% of retrospective group patients received pharmacological prophylaxis (p = .028). Overall, 299 drug doses for VTE prophylaxis have been spared after RAMs introduction (p = .0001) and health expenditure decreased by 27.2% (i.e., 1.67 € saved for each single patient). In conclusion, the extensive use of RAMs in our population of hospitalized medical patients did not statistically affect VTE rate or incidence of major bleeding, but it resulted in a significant drop in health expenditure related with pharmacological prophylaxis. Awaiting new clinical trials, a broad use of RAMs may be a safe strategy for reducing health expenditure associated with VTE prophylaxis in hospitalized medical patients.

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