Trigeminal nerve integrated dose and pain outcome after gamma knife radiosurgery for trigeminal neuralgia.
Bibliographic record
Abstract
BACKGROUND: Gamma knife radiosurgery (GKRS) is an established treatment for trigeminal neuralgia. Identifying factors that influence outcome will help improve patients' results. METHODS: We conducted a retrospective review of all patients treated with GKRS for trigeminal neuralgia at our institution from 2005 to 2010. Patients' clinical features and treatment details were reviewed. Analysis was performed to identify predictors of response and recurrence. RESULTS: A hundred and forty five patients were treated. Mean follow up period was 24 months. At last follow up, 48 patients (33%) were pain free with no medications, and 48 patients (33%) were pain free maintained on medications. Twenty-eight patients (19%) had pain after the treatment but had significant reduction in their pain severity. Twenty-one patients (15%) did not have any significant pain reduction. Forty-four patients (30%) developed facial numbness. Recurrence occurred in 51 patients (35%). Post-treatment numbness was a predictor of good treatment response (OR 2.720, CI 1.193-6.200, p 0.0173). Higher integrated dose was a predictor of poor pain response to radiosurgery (OR 0.729, CI 0.566-0.940, p 0.0146). At an integrated dose value of 5.3 mJ or less, there was more than 50% chance of pain free outcome. Longer pain duration prior to treatment was the only independent predictor of increased recurrence risk (HR 1.038, 95%CI 1.001-1.075; p=0.0412). CONCLUSIONS: Radiosurgery is an effective treatment modality for trigeminal neuralgia. Post treatment numbness is associated with good treatment response and higher integrated dose predicts poor outcome after radiosurgery for trigeminal neuralgia.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".