心脏手术后长期集中治疗室停留的预测模型:系统性审查和验证研究
Roelof G A Ettema1, Linda M Peelen, Marieke J Schuurmans
1University of Applied Science Utrecht, Faculty of Health Care, Bolognalaan 101 3584 CJ Utrecht, Netherlands. Roelof.Ettema@hu.nl
Circulation
|August 4, 2010
概括
这项研究验证了预测心脏手术后长时间集中治疗室 (ICU) 停留的模型. 帕森网和EuroSCORE模型在识别面临延长ICU治疗时间风险的患者方面表现出卓越的性能.
科学领域:
- 心脏病学 心脏病学
- 关键护理医学 关键护理医学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 预测心脏手术后的长时间重症监护室 (ICU) 停留对于资源分配至关重要.
- 现有的预测模型缺乏广泛的定量验证.
- 这项研究旨在确定和验证心脏手术后长期住院ICU长度的模型.
研究的目的:
- 系统地审查和定量验证心脏手术后长时间ICU停留的现有预测模型.
- 使用大型注册表数据库评估识别模型的歧视和校准.
主要方法:
- 系统的文献审查以确定预测模型.
- 将已识别的模型应用于11,395次心脏手术干预的注册数据库.
- 将预测的概率与实际结果进行比较,以评估模型性能 (区分和校准).
主要成果:
- 确定了20个模型,其中14个被纳入分析.
- 对于一般心脏手术群体,帕森网模型显示出最好的歧视 (AUC=0.75),其次是EuroSCORE (AUC=0.71).
- 大多数模型表现出良好的校准,表明可靠的概率估计.
结论:
- 尽管Parsonnet和EuroSCORE模型是为死亡率预测而设计的,但在识别长时间住入ICU的患者方面表现优越.
- 这些经过验证的模型可以帮助改善心脏手术ICU的患者管理和资源规划.
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