BMC Geriatrics (May 2024)

Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination

  • Zorian Radomyslsky,
  • Sara Kivity,
  • Yaniv Alon,
  • Mor Saban

DOI
https://doi.org/10.1186/s12877-024-04982-7
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 11

Abstract

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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.

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