Continuation Magnetic Seizure Therapy for Treatment-Resistant Unipolar or Bipolar Depression
Bibliographic record
Abstract
Electroconvulsive therapy (ECT) is highly effective for treatment-resistant depression (TRD) but may be associated with adverse cognitive effects. Magnetic seizure therapy (MST) is a promising alternative convulsive treatment with a safer cognitive profile. Although there is emerging evidence for the efficacy of MST for TRD as an acute treatment, there are no published studies of continuation MST for the prevention of relapse. diagnosis of major depressive disorder or bipolar disorder who met response criteria after acute MST were offered continuation MST in a prospective, open-label trial between February 2012 and June 2019. They received 12 continuation MST sessions with decreasing frequency over the course of 6 months, with additional booster sessions if their depression symptoms started to worsen. The primary outcome was relapse of depression or psychiatric hospitalization. Secondary outcomes included relapse of suicidal ideation and neurocognitive outcomes. = .58). Mean (SD) survival time was 18.6 (1.6) weeks. All 17 participants who achieved resolution of baseline suicidality after acute MST remained free of suicidality during the continuation phase. Except for improvement in verbal fluency, neurocognitive test scores did not change during continuation MST. During 6 months of continuation MST, two-thirds of participants sustained improvements in depressive symptoms without any adverse cognitive effects. Future studies of continuation MST are warranted, particularly in comparison to ECT. ClinicalTrials.gov identifier: NCT01596608.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".