Effectiveness and safety of neuroablation for severe and treatment-resistant obsessive–compulsive disorder: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Background: Several neuroablative procedures are available for severe and treatment-resistant obsessive-compulsive disorder (OCD), but limited knowledge about their relative clinical advantages and disadvantages poses obstacles for treatment decision-making. Methods: We searched PubMed, Embase, Scopus, Web of Knowledge and the Cochrane Library for reports up to February 2019. We reviewed the literature on the effectiveness (assessed using the Yale-Brown Obsessive Compulsive Scale [Y-BOCS]) and safety of various neuroablative interventions for severe and treatment-resistant OCD. Results: We included 23 studies involving 487 patients in the systematic review; 21 studies with 459 patients entered meta-analysis. Overall, neuroablation achieved a response rate (proportion of patients with ≥ 35% reduction in Y-BOCS) of 55%. Most of the adverse events (88.4%) were mild and transient. The top 3 adverse events were headache (14.9%), cognitive deficits (9.1%) and behaviour problems (8.1%). Severe or permanent adverse events included personality changes (2.3%) and brain edema or brain cyst (1.5%). The response rates associated with capsulotomy, limbic leucotomy and cingulotomy were 59% (95% confidence interval [CI] 54-65), 47% (95% CI 23-72) and 36% (95% CI 23-50), respectively. Interventions with different coverages of the dorsal part of the internal capsule were associated with different adverse-event profiles but were unlikely to modify clinical effectiveness. Limitations: The level of evidence of most included studies was relatively low. Conclusion: Ablative surgeries are safe and effective for a large proportion of patients with severe and treatment-resistant OCD. Among the available procedures, capsulotomy seemed to be the most effective. Further research is needed to improve clinical effectiveness and minimize risks.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it