Clinical Perspectives on Psychiatric Neurosurgery
Bibliographic record
Abstract
INTRODUCTION: Surgical interventions such as stereotactic radiosurgery and magnetic resonance-guided focused ultrasound, and neuromodulatory interventions such as deep brain stimulation (DBS) and vagal nerve stimulation, are under investigation to remediate psychiatric conditions resistant to conventional therapies involving drugs and psychological supports. OBJECTIVE: Given the complicated history of psychiatric neurosurgery and its renaissance today, we sought to examine current perceptions and predictions about the field among practicing functional neurosurgeons. METHODS: We designed a 51-question online survey comprising Likert-type, multiple-choice, and rank-order questions and distributed it to members of the American Society for Stereotactic and Functional Neurosurgery (ASSFN). Descriptive and inferential statistical analyses were performed on the data. RESULTS: We received 38 completed surveys. Half (n = 19) of responders reported devoting at least a portion of their clinical practice to psychiatric neurosurgery, utilizing DBS and treating obsessive compulsive disorder (OCD) most frequently overall. Respondents indicated that psychiatric neurosurgery is more medically effective (OR 0, p = 0.03242, two-sided Fisher's exact test) and has clearer clinical indications for the treatment of OCD than for the treatment of depression (OR 0.09775, p = 0.005137, two-sided Fisher's exact test). Seventy-one percent of all respondents (n = 27) supported the clinical utility of ablative surgery in modern neuropsychiatric practice, 87% (n = 33) agreed that ablative procedures constitute a valid treatment alternative to DBS for some patients, and 61% (n = 23) agreed that ablative surgery may be an acceptable treatment option for patients who are unlikely to comply with postoperative care. CONCLUSIONS: This up-to-date account of practices, perceptions, and predictions about psychiatric neurosurgery contributes to the knowledge about evolving attitudes over time and informs priorities for education and further surgical innovation on the psychiatric neurosurgery landscape.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".