Predicting the risk of severe COVID-19 outcomes in primary care: development and validation of a vulnerability index for equitable allocation of effective vaccines.

ABSTRACT

BACKGROUND: General practitioners (GPs) need a valid, user-friendly tool to identify patients most vulnerable to COVID-19, especially in the hypothesis of a booster vaccine dose. The aim of this study was to develop and validate a GP-friendly prognostic index able to forecast severe COVID-19 outcomes in primary care. Indeed, no such prognostic score is as yet available in Italy. RESEARCH DESIGN AND METHODS: In this retrospective cohort study, a representative sample of 47,868 Italian adults were followed up for 129,000 person-months. The study outcome was COVID-19-related hospitalization and/or death. Candidate predictors were chosen on the basis of systematic evidence and current recommendations. The model was calibrated by using Cox regression. Both internal and external validations were performed. RESULTS: Age, sex and several clinical characteristics were significantly associated with severe outcomes. The final multivariable model explained 60% (95%CI 58-63%) of variance for COVID-19-related hospitalizations and/or deaths. The area under the receiver-operator curve (AUC) was 84% (95% CI 83-85%). On applying the index to an external cohort, the AUC was 94% (95% CI 93-95%). CONCLUSIONS: This index is a reliable prognostic tool that can help GPs to prioritize their patients for preventive and therapeutic interventions.