Modeling Mortality Prediction in Older Adults with Dementia Receiving COVID-19 Vaccination

Overview

Journal BMC Geriatr

Publisher Biomed Central

Specialty Geriatrics

Date 2024 May 24

PMID 38789939

Authors

Zorian Radomyslsky

Sara Kivity

Yaniv Alon

Mor Saban

Affiliations

Soon will be listed here.

Abstract

Objective: This study compared COVID-19 outcomes between vaccinated and unvaccinated older adults with and without cognitive impairment.

Method: Electronic health records from Israel from March 2020-February 2022 were analyzed for a large cohort (N = 85,288) aged 65 + . Machine learning constructed models to predict mortality risk from patient factors. Outcomes examined were COVID-19 mortality and hospitalization post-vaccination.

Results: Our study highlights the significant reduction in mortality risk among older adults with cognitive disorders following COVID-19 vaccination, showcasing a survival rate improvement to 93%. Utilizing machine learning for mortality prediction, we found the XGBoost model, enhanced with inverse probability of treatment weighting, to be the most effective, achieving an AUC-PR value of 0.89. This underscores the importance of predictive analytics in identifying high-risk individuals, emphasizing the critical role of vaccination in mitigating mortality and supporting targeted healthcare interventions.

Conclusions: COVID-19 vaccination strongly reduced poor outcomes in older adults with cognitive impairment. Predictive analytics can help identify highest-risk cases requiring targeted interventions.

Citing Articles

A national population-based study of mortality and risk factors in COVID-19-hospitalized patients in Spain (2020-2021).

Ramos-Rincon J, Sanchez-Paya J, Gonzalez-De-La-Aleja P, Rodriguez-Diaz J, Merino E Front Public Health. 2025; 13:1488283.

PMID: 39980912 PMC: 11841506. DOI: 10.3389/fpubh.2025.1488283.

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