predictors of the response and relapse/recurrence after ect for depressed patients

Conditions: Major Depressive Episode

Summary: objective: psychiatrists have long sought a quantifiable biomarker of electroconvulsive therapy (ect) response. although ect is highly effective for treatment of patients with major depressive episode, a high rate of relapse/recurrence is a major problem after discontinuation of ect. the purpose of this study is to examine the factors related to the response of ect, to predict ect response early, and to investigate the clinical predictors affecting the time to relapse/recurrence after ect. methods: patients with major depressive episode who require ect treatment will be enrolled. ect will be performed regularly. the 17-item hamilton rating scale for depression (hamd-17) and other scales will be assessed before ect, after every 10 days, till to an expected average of 50 days, and monthly during the 6-month follow-up period. other measures also will be performed before the first ect, at an expected average of 50 days, and at the end of follow-up period. predictors of the response and relapse/recurrence after ect and early prediction of ect response will be obtained by statistic methods.

objective: electroconvulsive therapy (ect) is a safe and the most effective treatment for patients with major depressive episode, but the mechanism underlying the therapeutic action of this treatment is still unknown. psychiatrists have long sought a quantifiable biomarker of ect treatment response. till now, no biomarker of ect is used in clinical practice, but potential biomarkers that have been studied include brain-derived neurotrophic factor (bdnf), dna polymorphism, rna, electroencephalogram (eeg), auditory evoked potential (aep), and cognitive function test. although ect is highly effective for treatment of major depressive episode, a high rate of relapse/recurrence is a major problem after discontinuation of ect. the purpose of this study is to examine the factors related to the response of ect for patients with major depressive episode, to predict the ect response, and to investigate the clinical predictors affecting the time to relapse/recurrence after ect. methods: subjects with major depressive episode diagnosed according to dsm-iv criteria who require ect treatment will be enrolled for study. ect will be performed regularly using a brief-pulse, constant-current device. ect will be given two or three times a week. the 17-item hamilton rating scale for depression (hamd-17), clinical global impression-severity (cgi-s), global assessment scale (gaf), uku side effect rating scale and other scales will be assessed before ect, after every 10 days, till to an expected average of 50 days, and monthly during the 6-month follow-up period. response will be defined as a reduction of 60% or more of the hamd-17 score after treatment. other measures collected before ect and at an expected average of 50 days include zung's depression scale (sds), short-form 36 (sf-36), work and social adjustment scale (wsas), plasma bdnf level, auditory evoked potentials (aep), electroencephalography (eeg), neuropsychological test, and rna. after ect, cgi-s, hamd-17, gaf and wsas are reexamined monthly for 6 months. the definition of relapse/recurrence will be readmission, a ham-d-17 score at least 18, or a cgi-s score at least 4 during the follow-up period. a logistic regression model will be used to obtain the predictors for ect response. to establish the early prediction of ect response, receiver operating characteristic curve (roc) will be used to determine the cutoff point. possible predictors related to relapse/recurrence will be analyzed using the cox proportional hazards regression model.

Eligibility criteria:
inclusion criteria: * clinical diagnosis of major depressive disorder or bipolar depression * poor drug response * severity or urgency of illness exclusion criteria: * subjects cannot write the imform consents * subjects with severe physical illness

Keywords: major depressive episode, electroconvulsive therapy