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Clinical Prediction Guide Ageno W, Cogliati C, Perego M, et al. Clinical risk scores for the early prediction of severe outcomes in patients hospitalized for COVID-19. Intern Emerg Med. 2021 Feb 23. pii: 10.1007/s11739-020-02617-4. doi: 10.1007/s11739-020-02617-4.
Abstract

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.

Ratings
Discipline / Specialty Area Score
Hospital Doctor/Hospitalists
Internal Medicine
Infectious Disease
Comments from MORE raters

Hospital Doctor/Hospitalists rater

This retrospective cohort analysis of outcomes among 610 adults with Covid-19, admitted to 5 hospitals in north Italy, applied three different statistical methods to derive simple potentially useful clinical predictor scores of a 'severe' clinical outcome (observed in 51% of patients). Derivation data were from 3 hospitals, and validation data from 2. The best predictor had AOC 0.76 (derivation) and 0.80 (validation), where a score of 7 or less of 13 points had a negative predictive value of 0.82 for a 'severe' outcome. The authors of this impressively argued study suggest their score can be used to triage patients to less intense supportive wards on presentation.