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疾病严重程度测量指标的统计学验证

Statistical validation of a severity of illness measure.

作者信息

Wagner D P, Knaus W A, Draper E A

出版信息

Am J Public Health. 1983 Aug;73(8):878-84. doi: 10.2105/ajph.73.8.878.

Abstract

This paper provides statistical detail on the predictive power of a new severity of illness scale--APACHE (Acute Physiology and Chronic Health Evaluation)--on 833 consecutive medical admissions to an intensive care unit (ICU). In a multivariate logistic regression analysis of routine physiologic and other data obtained within 24 hours of ICU admission, severity of illness and age were significantly (p less than .0001) related to survival. Using the estimated equation to forecast death rates for independent data, APACHE allowed accurate estimates of death rates for groups of patients whose mortality at hospital discharge varied from 3 to 80 per cent. The Acute Physiology Score of APACHE is also strongly and significantly associated with outcome within a number of specific cardiovascular, neurologic, respiratory, and gastrointestinal diagnoses. After multi-institutional validation studies, APACHE could prove useful in a wide range of studies involving acutely ill patients.

摘要

本文提供了关于一种新的疾病严重程度量表——急性生理与慢性健康评估(APACHE)——对重症监护病房(ICU)连续收治的833例内科患者的预测能力的统计细节。在对ICU入院后24小时内获取的常规生理数据和其他数据进行的多变量逻辑回归分析中,疾病严重程度和年龄与生存率显著相关(p值小于0.0001)。使用估计方程预测独立数据的死亡率,APACHE能够准确估计出院时死亡率从3%到80%不等的患者群体的死亡率。APACHE的急性生理评分在一些特定的心血管、神经、呼吸和胃肠道诊断中也与预后密切且显著相关。经过多机构验证研究后,APACHE在涉及急性病患者的广泛研究中可能会被证明是有用的。

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Statistical validation of a severity of illness measure.疾病严重程度测量指标的统计学验证
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