Repetitive transcranial magnetic stimulation for the treatment of suicidality in opioid use disorder: a pilot feasibility randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Opioid use disorder (OUD) is a devastating condition with frequent suicidality, contributing to overdose deaths. Theta burst stimulation (TBS) to the dorsolateral prefrontal cortex (DLPFC) is used to treat major depressive disorder (MDD) and is effective in treating suicidal ideation. We piloted a randomized, double-blind, sham-controlled trial of bilateral rTMS for patients with OUD and MDD experiencing suicidality. METHODS: Sequential bilateral TBS was delivered guided by structural neuroimaging: continuous TBS to the right then intermittent TBS to the left DLPFC, daily (20 treatments). The primary objective was to determine the feasibility of this population. The primary clinical outcome was the scale for suicidal ideation (SSI), secondary outcomes included depressive symptoms and opioid cue-induced craving. ClinicalTrials.gov: NCT04785456. RESULTS: Eighty-seven individuals were pre-screened. The most common reasons for ineligibility included being unreachable by the study team, difficulty with scheduling/travel requirements, and medical/psychiatric instability. Six participants (5:1 M:F) were enrolled (3/arm), four had a fentanyl use history; two completed per protocol (1/arm). Of the participants with follow-up data, SSI scores decreased in 2/3 in the sham arm and 2/2 in the active arm; depression and opioid craving scores decreased in all participants. CONCLUSION: We present the first data piloting a structural neuroimaging-guided, multi-session rTMS treatment course in outpatients with suicidality and OUD in the current North American context. Recruitment and retention were the main challenges given the highly unstable medical and psychosocial context of this patient population. Future trials should consider a suitable environment to improve the feasibility of delivering this treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".