Impacts of Switching Antidepressants After Successful Electroconvulsive Therapy on the Maintenance of Clinical Remission in Patients With Treatment-Resistant Depression
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: There is no consensus regarding whether a previously prescribed, that is, failed, antidepressant should be continued or switched after a successful electroconvulsive therapy (ECT) for the maintenance of clinical remission in patients with treatment-resistant depression (TRD). In this study, we conducted a chart review to examine impacts of the antidepressant switch after the successful ECT on 1-year outcome in patients with TRD. MATERIALS AND METHODS: This retrospective chart review included inpatients with TRD (ie, those who failed to respond to adequate trials of 2 distinctly different classes of antidepressants) who showed clinical remission after ECT. Readmission rate and social functioning 6 months and 1 year after the successful ECT were compared between patients who experienced an antidepressant switch and those who continued prior regimen. RESULTS: Twenty-eight patients (mean age, 59 years; 9 men) were followed-up for 1 year. The patients who changed antidepressants after ECT (n = 7) experienced a readmission significantly less frequent than the others (n = 21) in 1 year (0% vs 43%, P = 0.043). In addition, the former showed significantly better social contacts at 6 months (P = 0.022) and 1 year (P = 0.015). There were no significant differences in baseline characteristics between the 2 groups. CONCLUSIONS: The patients who experienced an antidepressant switch after ECT required a readmission less frequently in 1 year than those who were maintained with the same antidepressant. The findings of this preliminary study suggest that a switch to another antidepressant after successful ECT may be encouraged for the maintenance of clinical remission in patients with TRD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it