Little information, great impact? A clinical tool for the prediction of electroconvulsive therapy effectiveness in depression

信息少,影响大?一种用于预测电休克疗法治疗抑郁症疗效的临床工具

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Abstract

BACKGROUND: The effectiveness of electroconvulsive therapy (ECT) for depression strongly depends on patient characteristics. Clinical factors may increase (e.g. age, psychotic symptoms) or decrease (e.g. episode duration) response rates. AIMS: This prospective study aimed to develop an instrument for the prediction of ECT response in patients with unipolar depression. METHOD: N = 45 patients were assessed using the Göttingen Response to ECT Assessment Tool (GREAT; seven items, 0 to 14 points). Clinical outcome was measured using the Montgomery Åsberg Depression Rating Scale (MADRS). Response was defined as ≥ 50% MADRS-improvement or a clinical global impression improvement (CGI-I) score ≤ 2. Analyses were conducted between responders and non-responders. RESULTS: Results showed a high correlation between GREAT-score and dichotomous response (r = 0.585) as well as MADRS-improvement (r = 0.554, both p < 0.001). Receiver operating characteristic (ROC)-analysis yielded an area under the curve (AUC) of 0.841 (asymptotic significance: p < 0.001). A cut-off point at ≥7 points predicted ECT response in individual cases with 80% accuracy. GLM-analyses showed a significantly better MADRS-improvement for patients with a GREAT-score ≥ 7 v. < 7 (interaction-effect: p < 0.001). CONCLUSIONS: Our prospective study shows that an instrument consisting of seven clinical items is able to predict ECT response in depression with good accuracy. Limitations include a relatively small sample size and the lack of further potential predictors suggested by recent studies. GREAT will thus be modified to further improve its accuracy. Currently, it may give clinicians a relevant estimate of the likelihood and the extent of the individual response to ECT.

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