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Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination
- Source :
- BMC Geriatrics, Vol 24, Iss 1, Pp 1-11 (2024)
- Publication Year :
- 2024
- Publisher :
- BMC, 2024.
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 14712318
- Volume :
- 24
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Geriatrics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.70c7d78fb1f438c967286fcbc162e73
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12877-024-04982-7