Deep brain stimulation for treatment-refractory obsessive-compulsive disorder should be an accepted therapy in Australia
Bibliographic record
Abstract
Deep brain stimulation has shown promise for the treatment of severe, treatment-refractory obsessive-compulsive disorder. With the recent publication of the first Australian, randomised, sham-controlled trial of deep brain stimulation for obsessive-compulsive disorder, there are now four placebo-controlled trials demonstrating the efficacy of this therapy. Together with recent data identifying a biological substrate of effective stimulation that can predict response and that has been successfully reproduced, studies comparing and finding equivalent efficacy among different targets, as well as recent, large, open trials supporting the long-term effectiveness of deep brain stimulation, we argue that this should now be considered an accepted therapy for a select group of patients in the Australasian setting. We call on the Royal Australian and New Zealand College of Psychiatrists to revise their memorandum describing deep brain stimulation for obsessive-compulsive disorder as an ‘ experimental’ treatment and recognise that it has proven efficacy. We stress that this should remain a therapy offered only to those with high treatment-refractory illnesses and only at specialised centres where there is an experienced multidisciplinary team involved in work-up, implantation and follow-up and also where frameworks are in place to provide careful clinical governance and ensure appropriate fully informed consent.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.013 | 0.024 |
| 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".