Accelerated Magnetic Seizure Therapy for Treatment of Major Depressive Disorder
Bibliographic record
Abstract
INTRODUCTION: Major depressive disorder is a prevalent and debilitating condition that afflicts millions of people worldwide. Magnetic seizure therapy (MST) is a promising convulsive neurostimulation treatment for depression with fewer cognitive adverse effects than electroconvulsive therapy. METHODS: A small case series of patients recruited as part of an open-label clinical trial is presented. Patients with depression underwent an accelerated MST protocol (aMST) consisting of 1 treatment per day for 6 consecutive weekdays. The primary outcome was severity on the HDRS17 (Hamilton Depression Rating Scale 17-item). In addition, patients underwent neuropsychological assessment with the Repeatable Battery for the Assessment of Neuropsychological Status and Stroop test. RESULTS: After completing aMST, all patients experienced improvement. Two patients met response criterion, and the third experienced a 27% decrease on the HDRS17. All 3 patients experienced improvement in cognitive performance with a global 20% mean improvement and strongest improvement in immediate and delayed verbal memory indices (mean improvement of 40% and 27%, respectively). There were no cases of prolonged confusion or delirium after MST treatments. There were no severe adverse effects in any of the 3 patients. CONCLUSIONS: Accelerated MST protocol was well tolerated and associated with positive outcomes in this small case series. Accelerated MST protocol was not associated with prolonged confusion or delirium and was associated with improvement in memory indices. Our results merit further research in large RCT to test whether accelerated MST protocol might be an efficacious treatment for major depressive disorder.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".