Shann F, Pearson G, Slater A, Wilkinson K
Intensive Care Unit, Royal Children's Hospital, Parkville, Victoria, Australia.
Intensive Care Med. 1997 Feb;23(2):201-7. doi: 10.1007/s001340050317.
To develop a logistic regression model that predicts the risk of death for children less than 16 years of age in intensive care, using information collected at the time of admission to the unit.
Three prospective cohort studies, from 1988 to 1995, were used to determine the variables for the final model. A fourth cohort study, from 1994 to 1996, collected information from consecutive admissions to all seven dedicated paediatric intensive care units in Australia and one in Britain.
2904 patients were included in the first three parts of the study, which identified ten variables for further evaluation. 5695 children were in the fourth part of the study (including 1412 from the third part); a model that used eight variables was developed on data from four of the units and tested on data from the other four units. The model fitted the test data well (deciles of risk goodness-of-fit test p = 0.40) and discriminated well between death and survival (area under the receiver operating characteristic plot 0.90). The final PIM model used the data from all 5695 children and also fitted well (p = 0.37) and discriminated well (area 0.90).
Scores that use the worst value of their predictor variables in the first 12-24 h should not be used to compare different units: patients mismanaged in a bad unit will have higher scores than similar patients managed in a good unit, and the bad unit's high mortality rate will be incorrectly attributed to its having sicker patients. PIM is a simple model that is based on only eight explanatory variables collected at the time of admission to intensive care. It is accurate enough to be used to describe the risk of mortality in groups of children.
利用重症监护病房收治时收集的信息,开发一种逻辑回归模型,以预测16岁以下儿童在重症监护中的死亡风险。
采用1988年至1995年的三项前瞻性队列研究来确定最终模型的变量。第四项队列研究于1994年至1996年进行,收集了澳大利亚所有七个专门的儿科重症监护病房以及英国一个此类病房连续收治患者的信息。
2904例患者纳入了研究的前三部分,从中确定了10个变量以供进一步评估。5695名儿童纳入了研究的第四部分(包括第三部分的1412名);基于四个病房的数据开发了一个使用八个变量的模型,并在其他四个病房的数据上进行了测试。该模型与测试数据拟合良好(风险拟合优度检验十分位数p = 0.40),且在死亡和存活之间有良好的区分度(受试者工作特征曲线下面积为0.90)。最终的儿科重症监护病房死亡风险指数(PIM)模型使用了所有5695名儿童的数据,拟合情况也良好(p = 0.37),区分度也良好(面积为0.90)。
不应使用在前12至24小时内采用预测变量最差值的评分来比较不同病房:在管理不善的病房中治疗不当的患者得分会高于在管理良好的病房中治疗的类似患者,而管理不善的病房的高死亡率将被错误地归因于其收治的患者病情更重。PIM是一个简单的模型,仅基于重症监护病房收治时收集的八个解释变量。它足够准确,可用于描述儿童群体中的死亡风险。