# A Vulnerability Index to Assess the Risk of SARS-CoV-2-Related Hospitalization/Death: Urgent Need for an Update after Diffusion of Anti-COVID Vaccines

## TL;DR

This paper updates a risk prediction tool for severe SARS-CoV-2 outcomes in vaccinated individuals to better inform healthcare decisions.

## Contribution

The study recalibrates the HS-CoVId vulnerability index to account for the impact of anti-COVID vaccination on hospitalization/death risk.

## Key findings

- The updated model explains 58% of variation in hospitalization/death outcomes among vaccinated individuals.
- The model achieved an AUC of 83%, indicating strong discrimination ability.
- Calibration of the model was robust, with a p-value of 0.904 for equivalence.

## Abstract

Background: There are algorithms to predict the risk of SARS-CoV-2-related complications. Given the spread of anti-COVID vaccination, which sensibly modified the burden of risk of the infection, these tools need to be re-calibrated. Therefore, we updated our vulnerability index, namely, the Health Search (HS)-CoVulnerabiltyIndex (VI)d (HS-CoVId), to predict the risk of SARS-CoV-2-related hospitalization/death in the primary care setting. Methods: We formed a cohort of individuals aged ≥15 years and diagnosed with COVID-19 between 1 January and 31 December 2021 in the HSD. The date of COVID-19 diagnosis was the study index date. These patients were eligible if they had received an anti-COVID vaccine at least 15 days before the index date. Patients were followed up from the index date until one of the following events, whichever came first: COVID-19-related hospitalization/death (event date), end of registration with their GPs, and end of the study period (31 December 2022). To calculate the incidence rate of COVID-19-related hospitalization/death, a patient-specific score was derived through linear combination of the coefficients stemming from a multivariate Cox regression model. Its prediction performance was evaluated by obtaining explained variation, discrimination, and calibration measures. Results: We identified 2192 patients who had received an anti-COVID vaccine from 1 January to 31 December 2021. With this cohort, we re-calibrated the HS-CoVId by calculating optimism-corrected pseudo-R2, AUC, and calibration slope. The final model reported a good predictive performance by explaining 58% (95% CI: 48–71%) of variation in the occurrence of hospitalizations/deaths, the AUC was 83 (95% CI: 77–93%), and the calibration slope did not reject the equivalence hypothesis (p-value = 0.904). Conclusions: Two versions of HS-CoVId need to be differentially adopted to assess the risk of COVID-19-related complications among vaccinated and unvaccinated subjects. Therefore, this functionality should be operationalized in related patient- and population-based informatic tools intended for general practitioners.