在结肠直肠手术后预测住院时间,使用手术内风险因素
Daitlin Esmee Huisman1,2, Erik Wouter Ingwersen1,2, Joanna Luttikhold3
1From the Department of Surgery, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
概括
开发准确的停留时间 (LOS) 预测模型对于结直肠外科手术至关重要. 整合手术内数据显著提高了预测准确性,帮助资源管理和患者护理.
科学领域:
- 医疗信息学 医疗信息学
- 手术结果研究研究.
- 医疗保健服务研究 医疗服务研究
背景情况:
- 预测停留时间 (LOS) 对于患者护理,医院资源优化和管理期望至关重要.
- 在结直肠外科手术中,长期的LOS通常与并发症有关,这凸显了需要准确的预测模型的需要.
- 改进的LOS预测可以提高患者的治疗结果和医疗保健效率.
研究的目的:
- 开发和比较两种不同的住院时间 (LOS) 预测模型,用于接受结直肠手术的患者.
- 评估结合手术内变量对LOS预测准确性的影响.
主要方法:
- 开发了两个随机森林模型:一个术前预测 (PP) 模型和一个术后预测 (IP) 模型,包括术前和术后变量.
- 模型使用10倍交叉验证进行了验证,通过曲线下面积 (AUC) 和校准曲线评估性能.
- 使用DeLong测试比较了这两种模型的分辨力.
主要成果:
- 这项研究分析了2140名接受结肠直肠手术的患者.
- 与PP模型 (AUC = 0.75) 相比,IP模型显示出更高的预测准确性 (AUC = 0.84).
- 模型之间的歧视差异在统计学上是显著的 (P < 0.001),两个模型都显示出良好的校准.
结论:
- 整合手术内参数显著提高了结直肠外科手术LOS预测模型的准确性.
- 更准确的LOS预测可以帮助管理患者流动并优化医疗保健资源分配.
- 这种改进的预测能力支持在面对不断增加的患者数量时更好地管理医疗保健.
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