DEEP BRAIN STIMULATION FOR TREATMENT-REFRACTORY OBSESSIVE-COMPULSIVE DISORDER
Bibliographic record
Abstract
Obsessive-compulsive disorder (OCD) is a common psychiatric disease that is marked by recurring, anxiety-provoking thoughts (obsessions) accompanied by repetitive and time-consuming behaviors (compulsions). Among the controversies in the OCD literature is the issue of the origin of the disease and whether brain changes observed with modern imaging techniques are the causes or results of OCD behaviors and thoughts. These issues remain unresolved; however, significant strides have been made in understanding the illness from both phenomenological and pathophysiological perspectives. The current staple of OCD management remains pharmacological in nature and often occurs in conjunction with cognitive behavioral therapy. Refractory cases, however, are occasionally referred for neurosurgical consultation, and several procedures have been examined. Success in the treatment of Parkinson's disease, the reversibility of the therapy, and a relatively safe side-effect profile have allowed deep brain stimulation (DBS) to be examined as an alternative treatment for some psychiatric conditions. Here we assess the possibility of applying DBS to the treatment of OCD. Morphological, functional metabolic, and volumetric data point to several brain regions that are important to the etiology and maintenance of OCD. Converging evidence from the genetics and neurocircuitry literature suggests that several subcortical structures play prominent roles in the disease. The functional modification of these structures could potentially provide symptom relief. Here, we review the ablative and DBS procedures for refractory OCD, and provide a research-driven hypothesis that highlights the ventromedial head of the caudate nucleus, and structures up- and downstream from it, as potential DBS targets for treatment-resistant disease. We hope that a research-driven approach, premised on converging evidence and previous experience, will lead to a safe and effective DBS procedure that will benefit patients who remain disabled despite presently available therapies.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".