Effectiveness and Cognitive Changes With Ultrabrief Right Unilateral and Other Forms of Electroconvulsive Therapy in the Treatment of Mania
Bibliographic record
Abstract
OBJECTIVE: Electroconvulsive therapy (ECT) is an effective treatment in mania. However, there is little evidence regarding the use of ultrabrief right unilateral (RUL-UB) ECT in treatment of acute manic episodes. The aim of this study was to report on the effectiveness and cognitive profile of ECT in bipolar mania, including a sample who received RUL-UB ECT. METHODS: This naturalistic study retrospectively collected data in 33 patients who received ECT with concurrent antipsychotics for mania between October 1, 2014, and July 30, 2016. Electroconvulsive therapy was given using RUL-UB, brief-pulse right unilateral, or brief-pulse bitemporal approaches, dosed according to the patient's seizure threshold. The Brief Psychiatric Rating Scale (BPRS), Young Mania Rating Scale (YMRS) score, and the Montreal Cognitive Assessment (MoCA) were administered to patients before and after the ECT course. RESULTS: For the whole sample, there was a significant improvement in BPRS (total score and manic subscale), YMRS, and MoCA total scores across the ECT treatment course. The overall BPRS response rate was 84%, and mean scores decreased from 42.1 (SD, 12.0) to 26.0 (SD, 4.0). The 13 patients who received RUL-UB ECT also showed significant improvement in BPRS, YMRS, and MoCA scores over the treatment course. CONCLUSIONS: Electroconvulsive therapy in general and also specifically RUL-UB ECT were effective in treating mania and also led to global cognitive improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".