A new risk prediction model for critical care: The Intensive Care National Audit & Research Centre (ICNARC) model
A new risk prediction model for critical care: The Intensive Care National Audit & Research Centre (ICNARC) model
复制标题
DOI：
10.1097/01.ccm.0000259468.24532.44
复制
发表时间：
2007-04-01
影响因子：
8.8
通讯作者：
Rowan, Kathy
中科院分区：
文献类型：
--
作者：
Harrison, David A.;Parry, Gareth J.;Rowan, Kathy
目的：开发一种新的模型来改进英国设计中成人重症监护病房的入院风险预测。前瞻性队列研究。背景：从1995年12月到2003年8月，在英格兰、威尔士和北爱尔兰的163个成人普通重症监护室。共有216,626名患者入院接受重症监护。没有。测量和主要结果。评估了不同的生理学测量建模方法的性能，并选择了最佳方法来产生新的生理学分数。这一生理学评分与其他与重症监护入院相关的信息--年龄、诊断类别、入院来源和入院前的心肺复苏--相结合，开发了一个风险预测模型。对诊断类别和生理学评分之间的相互作用进行建模，可以将经常被排除在风险预测模型之外的入院组包括在内。新模型在200个重复验证样本中显示出良好的判别力(平均c指数0.870)和拟合度(平均夏皮罗R值0.665，平均Brier评分0.132)，并且与符合所有模型的患者队列中现有已发表的风险预测模型的重新校正版本相比，表现得很好。所有模型都拒绝了完美匹配的假设，包括重症监护国家审计与研究中心(ICNARC)模型，这在如此大的队列中是可以预期的。ICNARC模型表现出比现有风险预测模型更好的区分性和整体适合性，即使在重新校准这些模型之后也是如此。我们建议用它来取代之前在英国发表的风险调整模型。
Objective: To develop a new model to improve risk prediction for admissions to adult critical care units in the UK.Design. Prospective cohort study.Setting: The setting was 163 adult, general critical care units in England, Wales, and Northern Ireland, December 1995 to August 2003.Patients. Patients were 216,626 critical care admissions.Interventions. None.Measurements and Main Results. The performance of different approaches to modeling physiologic measurements was evaluated, and the best methods were selected to produce a new physiology score. This physiology score was combined with other information relating to the critical care admission-age, diagnostic category, source of admission, and cardiopulmonary resuscitation before admission-to develop a risk prediction model. Modeling interactions between diagnostic category and physiology score enabled the inclusion of groups of admissions that are frequently excluded from risk prediction models. The new model showed good discrimination (mean c index 0.870) and fit (mean Shapiro's R 0.665, mean Brier's score 0.132) in 200 repeated validation samples and performed well when compared with recalibrated versions of existing published risk prediction models in the cohort of patients eligible for all models. The hypothesis of perfect fit was rejected for all models, including the Intensive Care National Audit & Research Centre (ICNARC) model, as is to be expected in such a large cohort.Conclusions. The ICNARC model demonstrated better discrimination and overall fit than existing risk prediction models, even following recalibration of these models. We recommend it be used to replace previously published models for risk adjustment in the UK.