A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

Mary E. Charlson , Peter Pompei, Kathy L. Ales, C.Ronald MacKenzie
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引用次数: 41428

Abstract

The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: “0”, 12% (181); “1–2”, 26% (225); “3–4”, 52% (71); and “⩾ 5”, 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: “0”, 8% (588); “1”, 25% (54); “2”, 48% (25); “ ⩾ 3”, 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank χ2 = 165; p < 0.0001). In this longer follow-up, age was also a predictor of mortality (p < 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.

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纵向研究中预后合并症分类的新方法:发展与验证
本研究的目的是开发一种前瞻性适用的方法来对可能改变死亡率风险的合并症进行分类,用于纵向研究。在559名医疗患者的队列中制定了一个考虑合并症数量和严重程度的加权指数。不同评分的1年死亡率为:“0”,12% (181);“1-2”,26% (225);“3-4”,52% (71);而“大于或等于5”,85%(82)。在为期10年的随访中,该指数在第二组685例患者中测试了其预测共病死亡风险的能力。不同评分下死于合并症的患者比例分别为:0.8%(588人);“1”,25% (54);“2”,48% (25);“大于或等于3”,59%(18)。随着合并症指数水平的升高,合并症导致的累计死亡率逐步升高(log rank χ2 = 165;p & lt;0.0001)。在更长时间的随访中,年龄也是死亡率的预测因子(p <0.001)。新指数的表现与卡普兰和范斯坦之前设计的系统相似。对共病进行分类的方法为纵向研究中估计共病死亡风险提供了一种简单、容易适用和有效的方法。由于本研究中患有任何特定疾病的患者数量相对较少,因此仍需要在更大的人群中进行进一步的工作来完善该方法。
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