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A novel Seizure Quality Index based on ictal parameters for optimizing clinical decision making in electroconvulsive therapy. Part 1: development

A novel Seizure Quality Index based on ictal parameters for optimizing clinical decision making... Early identification of patients at high risk for an unfavorable outcome to ECT during the course might be beneficial because it provides an opportunity for timely intensification or optimization of stimulus conditions. We aimed to develop a new Seizure Quality Index (SQI) that delivers a clinical relevant outcome prediction early in the treatment course and can be used within common clinical setting. An observational study was conducted. Patients (n = 86) with a depressive episode and the clinical decision for ECT (right unilateral, brief pulse) were included, and several ictal parameters derived from the second ECT session and the clinical outcome of the patients were documented. Optimal cut-off points for five different domains of ictal adequacy for younger and older patients for the prediction of “non-response” and “non-remission” based on seizure quality was determined by the Youden Index and a sum score was built. Logistic regression analyses tested the predictive power of derived models. For both outcome variables “non-response” and “non-remission”, the logistic regression models were statistically significant, albeit for remission only for subjects below the age of 65 years (χ 2 = 17.9, p = 0.001) and (χ 2 = 6.4, p = 0.020), respectively. The models correctly classified 87.2% (non-response) and 50.0% (non-remission) of the cases. ROC curve analysis showed an AUC of 0.87 (non-response) and 0.70 (non-remission). In elderly patients (> 65), no such model could be established due to a response rate of 100%. Our data provide promising, clinically relevant results about the prediction of response to ECT at an early stage for patients with depression. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Archives of Psychiatry and Clinical Neuroscience Springer Journals

A novel Seizure Quality Index based on ictal parameters for optimizing clinical decision making in electroconvulsive therapy. Part 1: development

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Medicine & Public Health; Psychiatry; Neurosciences; Neurology
ISSN
0940-1334
eISSN
1433-8491
DOI
10.1007/s00406-018-0910-6
Publisher site
See Article on Publisher Site

Abstract

Early identification of patients at high risk for an unfavorable outcome to ECT during the course might be beneficial because it provides an opportunity for timely intensification or optimization of stimulus conditions. We aimed to develop a new Seizure Quality Index (SQI) that delivers a clinical relevant outcome prediction early in the treatment course and can be used within common clinical setting. An observational study was conducted. Patients (n = 86) with a depressive episode and the clinical decision for ECT (right unilateral, brief pulse) were included, and several ictal parameters derived from the second ECT session and the clinical outcome of the patients were documented. Optimal cut-off points for five different domains of ictal adequacy for younger and older patients for the prediction of “non-response” and “non-remission” based on seizure quality was determined by the Youden Index and a sum score was built. Logistic regression analyses tested the predictive power of derived models. For both outcome variables “non-response” and “non-remission”, the logistic regression models were statistically significant, albeit for remission only for subjects below the age of 65 years (χ 2 = 17.9, p = 0.001) and (χ 2 = 6.4, p = 0.020), respectively. The models correctly classified 87.2% (non-response) and 50.0% (non-remission) of the cases. ROC curve analysis showed an AUC of 0.87 (non-response) and 0.70 (non-remission). In elderly patients (> 65), no such model could be established due to a response rate of 100%. Our data provide promising, clinically relevant results about the prediction of response to ECT at an early stage for patients with depression.

Journal

European Archives of Psychiatry and Clinical Neuroscience – Springer Journals

Published: Jun 6, 2018

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