Cook D A
School of Information Technology and Electrical Engineering, University of Queensland and Princess Alexandra Hospital, Brisbane, Queensland, Australia.
Anaesth Intensive Care. 2006 Apr;34(2):164-75. doi: 10.1177/0310057X0603400205.
Models that estimate the probability of death of intensive care unit patients can be used to stratify patients according to the severity of their condition and to control for casemix and severity of illness. These models have been used for risk adjustment in quality monitoring, administration, management and research and as an aid to clinical decision making. Models such as the Mortality Prediction Model family, SAPS II, APACHE II, APACHE III and the organ system failure models provide estimates of the probability of in-hospital death of ICU patients. This review examines methods to assess the performance of these models. The key attributes of a model are discrimination (the accuracy of the ranking in order of probability of death) and calibration (the extent to which the model's prediction of probability of death reflects the true risk of death). These attributes should be assessed in existing models that predict the probability of patient mortality, and in any subsequent model that is developed for the purposes of estimating these probabilities. The literature contains a range of approaches for assessment which are reviewed and a survey of the methodologies used in studies of intensive care mortality models is presented. The systematic approach used by Standards for Reporting Diagnostic Accuracy provides a framework to incorporate these theoretical considerations of model assessment and recommendations are made for evaluation and presentation of the performance of models that estimate the probability of death of intensive care patients.
估计重症监护病房患者死亡概率的模型可用于根据患者病情严重程度进行分层，并控制病例组合和疾病严重程度。这些模型已用于质量监测、管理、运营和研究中的风险调整，并辅助临床决策。诸如死亡率预测模型家族、简化急性生理学评分系统II（SAPS II）、急性生理与慢性健康状况评分系统II（APACHE II）、急性生理与慢性健康状况评分系统III（APACHE III）以及器官系统衰竭模型等模型，可提供重症监护病房患者院内死亡概率的估计值。本综述探讨了评估这些模型性能的方法。模型的关键属性包括区分度（按死亡概率排序的准确性）和校准度（模型对死亡概率的预测反映真实死亡风险的程度）。应在预测患者死亡概率的现有模型以及后续为估计这些概率而开发的任何模型中评估这些属性。文献中包含一系列评估方法，本文对其进行了综述，并介绍了重症监护死亡率模型研究中使用的方法调查。《诊断准确性报告标准》所采用的系统方法提供了一个框架，以纳入这些模型评估的理论考量，并针对评估和呈现估计重症监护患者死亡概率模型的性能提出了建议。
