Effectiveness of Electroconvulsive Therapy and Associated Cognitive Change in Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: There is limited evidence regarding the relative treatment effectiveness and cognitive effects of different types of electroconvulsive therapy (ECT) in schizophrenia. In this study, we sought to determine the overall effectiveness and compare the symptomatic and cognitive outcomes of patients with schizophrenia who received different modalities of ECT treatment. METHODS: Patients received 1 of 4 of the following ECT modalities: bitemporal ECT with age-based dosing, right unilateral ECT with seizure threshold-based dosing, bitemporal ECT with seizure threshold-based dosing, and bifrontal ECT with seizure threshold-based dosing ECT. The Brief Psychiatric Rating Scale (BPRS) and Montreal Cognitive Assessment (MoCA) were administered to 62 patients before and after the ECT course. RESULTS: There was a significant improvement in both the total and psychotic subscales of BPRS and MoCA scores across the patients after the course of ECT. The global improvements in both BPRS and MoCA scores after ECT were not influenced by the type of ECT administered. Age-based dosing, however, was associated with poorer memory outcomes posttreatment. The overall symptomatic response rate, defined as 40% or more reduction in the psychotic subscale of BPRS, was 64.5%. The response rates did not significantly differ between the 4 types of ECT. CONCLUSIONS: Our present findings suggest that an acute course of ECT is effective in schizophrenia and may have cognitive benefits for some patients.
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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 | 0.003 |
| 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".