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

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.

Automated summary

This study developed and validated a prognostic index for GPs to prioritize COVID-19 patients for preventive and therapeutic interventions, showing a high accuracy in predicting severe outcomes.