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

被引:1
作者
Radomyslsky, Zorian [1 ,2 ]
Kivity, Sara [1 ]
Alon, Yaniv [3 ]
Saban, Mor [3 ]
机构
[1] Maccabi Healthcare Serv, Tel Aviv Jaffa 6812509, Israel
[2] Ariel Univ, Sch Hlth Sci, Ariel, Israel
[3] Tel Aviv Univ, Fac Med & Hlth Sci, Sch Hlth Profess, Nursing Dept, IL-69978 Tel Aviv, Israel
关键词
Cognitive impairment; Older adults; COVID-19; vaccination; Mortality; Predictive analytics;
D O I
10.1186/s12877-024-04982-7
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
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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页数:11
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