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Updated: Jun 25, 2025

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
Published on: January 24, 2020
Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination
Zorian Radomyslsky1,2, Sara Kivity3, Yaniv Alon4
1Maccabi Healthcare Services, 6812509, Tel Aviv-Jaffa, Israel. radomysl_z@mac.org.il.
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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