Harrison David A, Brady Anthony R, Parry Gareth J, Carpenter James R, Rowan Kathy
Intensive Care National Audit & Research Centre, London, UK.
Crit Care Med. 2006 May;34(5):1378-88. doi: 10.1097/01.CCM.0000216702.94014.75.
To assess the performance of published risk prediction models in common use in adult critical care in the United Kingdom and to recalibrate these models in a large representative database of critical care admissions.
Prospective cohort study.
A total of 163 adult general critical care units in England, Wales, and Northern Ireland, during the period of December 1995 to August 2003.
A total of 231,930 admissions, of which 141,106 met inclusion criteria and had sufficient data recorded for all risk prediction models.
None.
The published versions of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE II UK, APACHE III, Simplified Acute Physiology Score (SAPS) II, and Mortality Probability Models (MPM) II were evaluated for discrimination and calibration by means of a combination of appropriate statistical measures recommended by an expert steering committee. All models showed good discrimination (the c index varied from 0.803 to 0.832) but imperfect calibration. Recalibration of the models, which was performed by both the Cox method and re-estimating coefficients, led to improved discrimination and calibration, although all models still showed significant departures from perfect calibration.
Risk prediction models developed in another country require validation and recalibration before being used to provide risk-adjusted outcomes within a new country setting. Periodic reassessment is beneficial to ensure calibration is maintained.
评估英国成人重症监护中常用的已发表风险预测模型的性能,并在一个具有代表性的大型重症监护入院数据库中对这些模型进行重新校准。
前瞻性队列研究。
1995年12月至2003年8月期间,英格兰、威尔士和北爱尔兰的163个成人综合重症监护病房。
共231930例入院患者,其中141106例符合纳入标准,且记录了所有风险预测模型的足够数据。
无。
通过专家指导委员会推荐的适当统计方法组合,对急性生理与慢性健康状况评估(APACHE)II、APACHE II英国版、APACHE III、简化急性生理评分(SAPS)II和死亡概率模型(MPM)II的已发表版本进行区分度和校准评估。所有模型均显示出良好的区分度(c指数在0.803至0.832之间),但校准并不完美。通过Cox方法和重新估计系数对模型进行重新校准,虽所有模型仍与完美校准存在显著偏差,但区分度和校准得到了改善。
在另一个国家开发的风险预测模型,在用于新的国家环境中提供风险调整后的结果之前,需要进行验证和重新校准。定期重新评估有助于确保校准得以维持。