Treatment of refractory obsessive–compulsive disorder with nutraceuticals (TRON): a 20-week, open label pilot study
Bibliographic record
Abstract
Abstract Background Obsessive–compulsive disorder (OCD) is often challenging to treat and resistant to psychological interventions and prescribed medications. The adjunctive use of nutraceuticals with potential neuromodulatory effects on underpinning pathways such as the glutamatergic and serotonergic systems is one novel approach. Objective To assess the effectiveness and safety of a purpose-formulated combination of nutraceuticals in treating OCD:N-acetyl cysteine, L-theanine, zinc, magnesium, pyridoxal-5′ phosphate, and selenium. Methods A 20-week open label proof-of-concept study was undertaken involving 28 participants with treatment-resistant DSM-5-diagnosed OCD, during 2017 to 2020. The primary outcome measure was the Yale-Brown Obsessive–Compulsive Scale (YBOCS), administered every 4 weeks. Results An intention-to-treat analysis revealed an estimated mean reduction across time (baseline to week-20) on the YBOCS total score of −7.13 (95% confidence interval = −9.24, −5.01), with a mean reduction of −1.21 points per post-baseline visit (P ≤ .001). At 20-weeks, 23% of the participants were considered “responders” (YBOCS ≥35% reduction and “very much” or “much improved” on the Clinical Global Impression-Improvement scale). Statistically significant improvements were also revealed on all secondary outcomes (eg, mood, anxiety, and quality of life). Notably, treatment response on OCD outcome scales (eg, YBOCS) was greatest in those with lower baseline symptom levels, while response was limited in those with relatively more severe OCD. Conclusions While this pilot study lacks placebo-control, the significant time effect in this treatment-resistant OCD population is encouraging and suggests potential utility especially for those with lower symptom levels. Our findings need to be confirmed or refuted via a follow-up placebo-controlled study.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".