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澄清困惑:混乱评估方法。一种检测谵妄的新方法。

Clarifying confusion: the confusion assessment method. A new method for detection of delirium.

作者信息

Inouye S K, van Dyck C H, Alessi C A, Balkin S, Siegal A P, Horwitz R I

机构信息

Yale University School of Medicine, New Haven, Connecticut.

出版信息

Ann Intern Med. 1990 Dec 15;113(12):941-8. doi: 10.7326/0003-4819-113-12-941.

Abstract

OBJECTIVE

To develop and validate a new standardized confusion assessment method (CAM) that enables nonpsychiatric clinicians to detect delirium quickly in high-risk settings.

DESIGN

Prospective validation study.

SETTING

Conducted in general medicine wards and in an outpatient geriatric assessment center at Yale University (site 1) and in general medicine wards at the University of Chicago (site 2).

PATIENTS

The study included 56 subjects, ranging in age from 65 to 98 years. At site 1, 10 patients with and 20 without delirium participated; at site 2, 16 patients with and 10 without delirium participated.

MEASUREMENTS AND MAIN RESULTS

An expert panel developed the CAM through a consensus building process. The CAM instrument, which can be completed in less than 5 minutes, consists of nine operationalized criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R). An a priori hypothesis was established for the diagnostic value of four criteria: acute onset and fluctuating course, inattention, disorganized thinking, and altered level of consciousness. The CAM algorithm for diagnosis of delirium required the presence of both the first and the second criteria and of either the third or the fourth criterion. At both sites, the diagnoses made by the CAM were concurrently validated against the diagnoses made by psychiatrists. At sites 1 and 2 values for sensitivity were 100% and 94%, respectively; values for specificity were 95% and 90%; values for positive predictive accuracy were 91% and 94%; and values for negative predictive accuracy were 100% and 90%. The CAM algorithm had the highest predictive accuracy for all possible combinations of the nine features of delirium. The CAM was shown to have convergent agreement with four other mental status tests, including the Mini-Mental State Examination. The interobserver reliability of the CAM was high (kappa = 0.81 - 1.0).

CONCLUSIONS

The CAM is sensitive, specific, reliable, and easy to use for identification of delirium.

摘要

目的

开发并验证一种新的标准化意识模糊评估方法(CAM),使非精神科临床医生能够在高风险环境中快速检测出谵妄。

设计

前瞻性验证研究。

地点

在耶鲁大学的普通内科病房和门诊老年评估中心(地点1)以及芝加哥大学的普通内科病房(地点2)进行。

患者

该研究纳入了56名年龄在65至98岁之间的受试者。在地点1,10名有谵妄和20名无谵妄的患者参与;在地点2,16名有谵妄和10名无谵妄的患者参与。

测量与主要结果

一个专家小组通过共识建立过程开发了CAM。CAM工具可在不到5分钟内完成,由来自《精神疾病诊断与统计手册》(DSM-III-R)的九条可操作标准组成。针对四条标准的诊断价值建立了一个先验假设:急性起病且病程波动、注意力不集中、思维紊乱以及意识水平改变。诊断谵妄的CAM算法要求同时存在第一条和第二条标准以及第三条或第四条标准中的任意一条。在两个地点,CAM做出的诊断与精神科医生做出的诊断同时进行了验证。在地点1和2,敏感性值分别为100%和94%;特异性值分别为95%和90%;阳性预测准确率值分别为91%和94%;阴性预测准确率值分别为100%和90%。CAM算法对谵妄九个特征的所有可能组合具有最高的预测准确率。CAM与包括简易精神状态检查表在内的其他四项精神状态测试具有趋同一致性。CAM的观察者间信度很高(kappa = 0.81 - 1.0)。

结论

CAM对于识别谵妄具有敏感性、特异性、可靠性且易于使用。

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