A pilot study of the comparative efficacy of 100 Hz magnetic seizure therapy and electroconvulsive therapy in persistent depression
Bibliographic record
Abstract
BACKGROUND: Magnetic seizure therapy (MST) is a novel brain stimulation technique that uses a high-powered transcranial magnetic stimulation device to produce therapeutic seizures. Preliminary MST studies have found antidepressant effects in the absence of cognitive side effects but its efficacy compared to electroconvulsive therapy (ECT) remains unclear. The aim of this study was to investigate the therapeutic efficacy and cognitive profile of MST compared to standard right unilateral ECT treatment. METHODS: Thirty-seven patients completed a course of at least nine ECT or MST treatments in a randomized double-blind protocol. Assessments of depression severity and cognition were performed before and after treatment. RESULTS: No difference in the antidepressant effectiveness between the treatments was seen across any of the clinical outcome measures, although the overall response rates in both groups were quite low. In regards to cognition, following MST there were significant improvements in tests of psychomotor speed, verbal memory, and cognitive inhibition, with no reductions in cognitive performance. Following ECT there was significant improvement in only one of the cognitive inhibition tasks. With respect to the between-group comparisons, the MST group showed a significantly greater improvement on psychomotor speed than ECT. CONCLUSIONS: MST showed similar efficacy to right unilateral ECT in patients with treatment-resistant depression without cognitive side effects but in a sample that was only of sufficient size to demonstrate relatively large differences in response between the two groups. Future research should aim to optimize the methods of MST administration and compare its efficacy to ECT in large randomized controlled trials.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".