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
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Published:2024-03-15
Issue:2
Volume:16
Page:260-268
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ISSN:2036-7449
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Container-title:Infectious Disease Reports
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language:en
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Short-container-title:Infectious Disease Reports
Author:
Lapi Francesco1, Marconi Ettore1, Domnich Alexander2ORCID, Cricelli Iacopo3ORCID, Rossi Alessandro4, Grattagliano Ignazio4ORCID, Icardi Giancarlo25ORCID, Cricelli Claudio4
Affiliation:
1. Health Search, Italian College of General Practitioners and Primary Care, 50142 Florence, Italy 2. Hygiene Unit, San Martino Policlinico Hospital-IRCCS for Oncology and Neurosciences, 16132 Genoa, Italy 3. Genomedics S.r.l., 50141 Firenze, Italy 4. Italian College of General Practitioners and Primary Care, 50142 Florence, Italy 5. Department of Health Sciences, University of Genoa, 16132 Genoa, Italy
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.
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