Repetitive Transcranial Magnetic Stimulation Promotes Rapid Psychiatric Stabilization in Acutely Suicidal Military Service Members
Bibliographic record
Abstract
OBJECTIVE: This study presents data for using accelerated transcranial magnetic stimulation (TMS) as an intervention for suicidal crisis (SC). METHODS: This prospective, single-site, randomized, double-blind trial enrolled active-duty military participants with SC to receive either active TMS (n = 59) or sham TMS (n = 61) 3 times per day for 3 consecutive days. Our primary outcome, the Beck Scale for Suicidal Ideation-current (SSI-C), was measured before each session of TMS. Secondary outcomes measured both the SSI-C and the Beck Scale for Suicidal Ideation-total daily for the 3 intervention days and at 1, 3, and 6 months of follow-up. RESULTS: In the modified intention to treat (mITT) analysis of SSI-C changes over treatment sessions, the TMS active group had accelerated decline in suicidal ideation as compared with sham: β for interaction was 0.12 points greater SSI-C decline per session (standard error [SE], 0.06) in TMS versus sham (P = 0.04). In both the mITT and per-protocol active TMS groups, the mean final SSI-C scores were below 3. These scores remained below 3 for the entire 6-month follow-up period. CONCLUSIONS: In this military trial of suicidal patients, we found that both active and sham accelerated TMS rapidly reduces SC. Moreover, in the mITT analysis, there was a statistically significant antisuicidal benefit of active TMS versus sham TMS in the primary outcome. Both the mITT and per-protocol groups moved from higher to approximately 7 times lower suicide risk strata and remained there for the duration of the study. Further studies are warranted to understand accelerated TMS' full potential as a treatment for SC.
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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".