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用于验证老年抑郁症患者和痴呆患者脑电图睡眠判别能力的受试者工作特征分析。

Receiver operating characteristic analysis for validating EEG sleep discrimination of elderly depressed and demented patients.

作者信息

Houck P R, Reynolds C F, Mazumdar S, Kupfer D J

机构信息

Department of Psychiatry, University of Pittsburgh School of Medicine, PA 15213.

出版信息

J Geriatr Psychiatry Neurol. 1991 Jan-Mar;4(1):30-3. doi: 10.1177/089198879100400106.

Abstract

Receiver operating characteristic analysis is a useful tool in validating a diagnostic marker. This technique was applied to a discriminant function model using selected electroencephalographic sleep measures (sleep maintenance, percentage of rapid-eye-movement sleep, and percentage of indeterminate non-rapid-eye-movement sleep) in elderly patients with major depression or dementia of the Alzheimer type. The diagnostic model correctly classified 79.8% of elderly depressed and demented patients. The area under the curve was 0.86, statistically different from 0.5, which would be expected by chance (P less than .0001) and indicating good predictive power of the model. A logistic regression analysis demonstrated the reliability and stability of the diagnostic equation.

摘要

受试者工作特征分析是验证诊断标志物的一项有用工具。该技术应用于一个判别函数模型,该模型使用了选定的脑电图睡眠指标(睡眠维持、快速眼动睡眠百分比和不确定的非快速眼动睡眠百分比),用于患有重度抑郁症或阿尔茨海默病型痴呆症的老年患者。该诊断模型正确分类了79.8%的老年抑郁症和痴呆症患者。曲线下面积为0.86,与偶然预期的0.5有统计学差异(P小于0.0001),表明该模型具有良好的预测能力。逻辑回归分析证明了诊断方程的可靠性和稳定性。

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