Intermittent theta-burst stimulation with adjunctive D-cycloserine rapidly resolves suicidal ideation and decreases implicit association with death/suicide
Bibliographic record
Abstract
Abstract Background Depressive disorders are the most common diagnosis among individuals who die by suicide, and intermittent theta-burst stimulation (iTBS) is a noninvasive treatment for those with difficult-to-treat depression who are at higher risk for suicide. Previous data suggests that pairing iTBS with D-cycloserine, a partial N-methyl-D-aspartate (NMDA) receptor agonist, improves antidepressant outcomes. However, its impact on suicide risk is not known. Methods We examine suicidal ideation and implicit suicide risk after iTBS+D-cycloserine in two clinical trials (open-label trial [n = 12] and randomized placebo-controlled trial [RCT, n = 50]) involving adults with major depressive disorder and the acute effects of D-cycloserine on implicit suicide risk in a crossover trial (n = 18). Implicit suicide risk was assessed using the computerized death/suicide implicit association test (IAT), and depressive symptoms and suicidal ideation were assessed using the clinician-rated Montgomery–Asberg Depression Rating Scale (MADRS). Results Open-label iTBS+D-cycloserine was associated with a rapid reduction in suicidal ideation, and iTBS+D-cycloserine was superior to iTBS+placebo in reducing suicidal ideation. Similarly, open-label iTBS+D-cycloserine was associated with decreased implicit suicide risk as measured by the death/suicide IAT, and iTBS+D-cycloserine was associated with greater decreases in death/suicide IAT scores compared to iTBS+placebo. A single acute dose of D-cycloserine in the absence of iTBS had no effect on implicit suicide risk. Conclusions Adjunctive D-cycloserine with iTBS is a promising strategy to reduce suicidal ideation and implicit suicide risk in depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.003 | 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".