构建一个全面的护理风险评估模型,用于多种慢性疾病的老年住院患者:一个多中心的横截面研究
1Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University / West China School of Nursing, Sichuan University, Chengdu 610041,China.
概括
使用随机森林的新护理风险模型准确预测了多种慢性疾病的老年住院患者的风险. 该模型显示了临床使用的强大潜力,用于识别需要专门护理的患者.
科学领域:
- 老年医学 老年医学
- 医疗信息学 医疗信息学
- 护理科学 护理科学
背景情况:
- 老年人往往有多种慢性疾病,增加了对不良护理事件的风险.
- 准确识别护理风险对于有效的患者管理和住院老年患者的改善结果至关重要.
研究的目的:
- 开发和验证一个全面的护理风险模型,用于多种慢性疾病的老年住院患者.
- 确定导致这群脆弱人群中护理风险的关键因素.
主要方法:
- 利用Python构建和比较后勤回归,决策树和随机森林模型.
- 从中国四川省的4458名老年住院患者收集的数据 (2020年3月 - 2022年6月).
- 使用包括准确性,精度,回忆,宏F1和曲线下面面积 (AUC) 在内的指标评估模型性能.
主要成果:
- 该研究包括4458名患者,平均年龄为74.31岁,平均患有2.81种慢性疾病.
- 高血压,糖尿病和冠状动脉心脏病是最常见的疾病.
- 随机森林模型表现出优异的预测性能,AUC为0.933,确定了12.4%的患有护理风险事件的患者.
结论:
- 随机森林模型在预测护理风险方面明显优于后勤回归和决策树模型.
- 开发的模型显示出高准确性和在老年护理中实际临床应用的潜力.
- 这种工具可以帮助医疗保健提供者主动识别老年住院患者的风险和进行干预.
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