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小儿死亡风险(PRISM)评分

Pediatric risk of mortality (PRISM) score.

作者信息

Pollack M M, Ruttimann U E, Getson P R

机构信息

Department of Anesthesiology (Division of Critical Care), Children's Hospital National Medical Center, Washington, DC 20010.

出版信息

Crit Care Med. 1988 Nov;16(11):1110-6. doi: 10.1097/00003246-198811000-00006.

Abstract

The Pediatric Risk of Mortality (PRISM) score was developed from the Physiologic Stability Index (PSI) to reduce the number of physiologic variables required for pediatric ICU (PICU) mortality risk assessment and to obtain an objective weighting of the remaining variables. Univariate and multivariate statistical techniques were applied to admission day PSI data (1,415 patients, 116 deaths) from four PICUs. The resulting PRISM score consists of 14 routinely measured, physiologic variables, and 23 variable ranges. The performance of a logistic function estimating PICU mortality risk from the PRISM score, age, and operative status was tested in a different sample from six PICUs (1,227 patients, 105 deaths), each PICU separately, and in diagnostic groups using chi-square goodness-of-fit tests and receiver operating characteristic (ROC) analysis. In all groups, the number and distribution of survivors and nonsurvivors in adjacent mortality risk intervals were accurately predicted: total validation group (chi 2(5) = 0.80; p greater than .95), each PICU separately (chi 2(5) range 0.83 to 7.38; all p greater than .10), operative patients (chi 2(5) = 2.03; p greater than .75), nonoperative patients (chi 2(5) = 2.80, p greater than .50), cardiovascular disease patients (chi 2(5) = 4.72; p greater than .25), respiratory disease patients (chi 2(5) = 5.82; p greater than .25), and neurologic disease patients (chi 2(5) = 7.15; p greater than .10). ROC analysis also demonstrated excellent predictor performance (area index = 0.92 +/- 0.02).

摘要

儿童死亡风险(PRISM)评分是在生理稳定性指数(PSI)的基础上开发的,旨在减少儿科重症监护病房(PICU)死亡风险评估所需的生理变量数量,并对其余变量进行客观加权。单变量和多变量统计技术应用于来自四个PICU的入院日PSI数据(1415例患者,116例死亡)。由此产生的PRISM评分由14个常规测量的生理变量和23个变量范围组成。在来自六个PICU的不同样本(1227例患者,105例死亡)中,分别对每个PICU以及在诊断组中,使用卡方拟合优度检验和受试者操作特征(ROC)分析,测试了根据PRISM评分、年龄和手术状态估计PICU死亡风险的逻辑函数的性能。在所有组中,相邻死亡风险区间内幸存者和非幸存者的数量及分布均得到准确预测:总验证组(卡方(5) = 0.80;p大于0.95),每个PICU分别(卡方(5)范围为0.83至7.38;所有p大于0.10),手术患者(卡方(5) = 2.03;p大于0.75),非手术患者(卡方(5) = 2.80,p大于0.50),心血管疾病患者(卡方(5) = 4.72;p大于0.25),呼吸系统疾病患者(卡方(5) = 5.82;p大于0.25),以及神经系统疾病患者(卡方(5) = 7.15;p大于0.10)。ROC分析也显示出优异的预测性能(面积指数 = 0.92±0.02)。

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