Bilateral stereotactic anterior capsulotomy for obsessive-compulsive disorder: long-term follow-up
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Psychosurgery, such as anterior capsulotomy, is a therapeutic option for treatment-resistant obsessive-compulsive disorder (OCD). In this paper, we present a prospective, long-term follow-up study aimed at evaluating both the efficacy and the safety of anterior capsulotomy for the treatment of severe, refractory OCD. METHODS: Twenty-four patients were surgically treated in our centre between 1997 and 2009, 19 of whom were included in this study. Patients were assessed at 3, 6, 12, and 24 months and last follow-up (mean of 7 years) was carried out by phone. OCD symptom severity was evaluated using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). A patient with an improvement rate of over 35% in the Y-BOCS score was considered a responder, while a patient with a 25% improvement was considered a partial responder. RESULTS: With a mean improvement of 31% in the Y-BOCS score at long-term follow-up, 36.8% of the patients responded fully to the procedure and 10.5% were considered partial responders, for an overall response rate of 47.3% of patients. At the end of the study, 3/19 patients had recovered (Y-BOCS score <8) and 3/19 were in remission (Y-BOCS score <16). No cases of mortality were reported and the overall adverse event rate was 57.9%. Only 2 patients had permanent surgical complications. CONCLUSIONS: Anterior capsulotomy is an effective and safe technique for the treatment of severe refractory OCD in patients who have no other alternative to improve their symptoms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".