Maccabi Healthcare Services, 6812509, Tel Aviv-Jaffa, Israel.
Ariel University, School of Health Sciences, Ariel, Israel.
BMC Geriatr. 2024 May 24;24(1):454. doi: 10.1186/s12877-024-04982-7.
This study compared COVID-19 outcomes between vaccinated and unvaccinated older adults with and without cognitive impairment.
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.
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.
COVID-19 vaccination strongly reduced poor outcomes in older adults with cognitive impairment. Predictive analytics can help identify highest-risk cases requiring targeted interventions.
本研究比较了合并和不合并认知障碍的接种和未接种疫苗的老年患者的 COVID-19 结局。
分析了 2020 年 3 月至 2022 年 2 月以色列的电子健康记录，纳入了一个年龄在 65 岁及以上的大队列（N=85288）。机器学习构建了预测患者死亡风险的模型。评估的结果是 COVID-19 疫苗接种后的死亡率和住院率。
我们的研究强调了 COVID-19 疫苗接种后认知障碍老年患者的死亡率显著降低，生存率提高到 93%。使用机器学习进行死亡率预测，我们发现 XGBoost 模型，通过逆概率处理加权增强，效果最佳，AUC-PR 值为 0.89。这突出了预测分析在识别高危个体中的重要性，强调了疫苗接种在降低死亡率和支持有针对性的医疗干预方面的关键作用。
COVID-19 疫苗接种显著降低了认知障碍老年患者的不良结局。预测分析可以帮助识别需要有针对性干预的高风险病例。
