de Rooij Sophia E, Abu-Hanna Ameen, Levi Marcel, de Jonge Evert
Department of Geriatrics, Academic Medical Center, University of Amsterdam, Meibergdreef 9 1105 AZ, Amsterdam, The Netherlands.
Crit Care. 2007;11(2):R33. doi: 10.1186/cc5716.
Current prognostic models for intensive care unit (ICU) patients have not been specifically developed or validated in the very elderly. The aim of this study was to develop a prognostic model for ICU patients 80 years old or older to predict in-hospital mortality by means of data obtained within 24 hours after ICU admission. Aside from having good overall performance, the model was designed to reliably and specifically identify subgroups at very high risk of dying.
A total of 6,867 consecutive patients 80 years old or older from 21 Dutch ICUs were studied. Data necessary to calculate the Glasgow Coma Scale, Acute Physiology and Chronic Health Evaluation II, Simplified Acute Physiology Score II (SAPS II), Mortality Probability Models II scores, and ICU and hospital survival were recorded. Data were randomly divided into a developmental (n = 4,587) and a validation (n = 2,289) set. By means of recursive partitioning analysis, a classification tree predicting in-hospital mortality was developed. This model was compared with the original SAPS II model and with the SAPS II model after recalibration for very elderly ICU patients in the Netherlands.
Overall performance measured by the area under the receiver operating characteristic curve and by the Brier score was similar for the classification tree, the original SAPS II model, and the recalibrated SAPS II model. The tree identified most patients with very high risk of mortality (9.2% of patients versus 8.9% for the original SAPS II and 5.9% for the recalibrated SAPS II had a risk of more than 80%). With a cut-point at a risk of 80%, the positive predictive values were 0.88 for the tree, 0.83 for the original SAPS II, and 0.87 for the recalibrated SAPS II.
Prognostic models with good overall performance may also reliably identify subgroups of very elderly ICU patients who have a very high risk of dying before hospital discharge. The classification tree has the advantage of identifying the separate factors contributing to bad outcome and of using few variables. Up to 9.5% of patients were found to have a risk to die of more than 85%.
目前针对重症监护病房（ICU）患者的预后模型尚未专门针对高龄患者开发或验证。本研究的目的是通过ICU入院后24小时内获取的数据，为80岁及以上的ICU患者开发一种预后模型，以预测住院死亡率。除了具有良好的整体性能外，该模型旨在可靠且特异性地识别死亡风险极高的亚组。
对来自荷兰21个ICU的6867例连续80岁及以上的患者进行了研究。记录了计算格拉斯哥昏迷量表、急性生理与慢性健康状况评估II、简化急性生理学评分II（SAPS II）、死亡概率模型II评分以及ICU和医院生存情况所需的数据。数据被随机分为一个开发集（n = 4587）和一个验证集（n = 2289）。通过递归划分分析，开发了一个预测住院死亡率的分类树。将该模型与原始SAPS II模型以及荷兰高龄ICU患者重新校准后的SAPS II模型进行了比较。
分类树、原始SAPS II模型和重新校准后的SAPS II模型在通过受试者工作特征曲线下面积和Brier评分衡量的整体性能方面相似。该树识别出了大多数死亡风险极高的患者（9.2%的患者，而原始SAPS II为8.9%，重新校准后的SAPS II为5.9%的患者风险超过80%）。在风险切点为80%时，分类树的阳性预测值为0.88，原始SAPS II为0.83，重新校准后的SAPS II为0.87。
具有良好整体性能的预后模型也可以可靠地识别出在出院前死亡风险极高的高龄ICU患者亚组。分类树的优点是能够识别导致不良结局的单独因素且使用的变量较少。发现高达9.5%的患者死亡风险超过85%。
