Stereotactic Radiosurgery versus Neuroablative Techniques for Medically Refractory Trigeminal Neuralgia: A Systematic Review and Meta-Analysis of Outcomes
Bibliographic record
Abstract
INTRODUCTION: There is a lack of evidence to guide the choice between stereotactic radiosurgery (SRS) and neuroablative procedures for patients with medically refractory trigeminal neuralgia (TN). This meta-analysis aims to identify the outcomes of these interventions for TN. METHODS: Studies identified through PubMed, MEDLINE, and Embase, were cohort studies or clinical trials, had ≥20 participants, and had a ≥12-month follow-up. All participants were ≥16 years old and had primary refractory TN. Studies reported outcomes using the Barrow Neurological Institute (BNI) scale. The Shapiro-Wilk test, Mann-Whitney U test, two-tailed T Test, Spearman's R, and ANCOVA were used to test statistical significance. Screening was done according to PRISMA guidelines. Bias assessment was according to the Newcastle-Ottawa Scale. RESULTS: 3,288 patients from 37 studies were included (2,537 SRS, 751 neuroablative). Overall reporting of BNI I, II, III, IV, and V was 36.0%, 17.4%, 23.9%, 11.7%, and 10.9%, respectively, in the SRS cohort, and 63.6%, 10.4%, 11.1%, 7.3%, and 7.6%, respectively, in the neuroablative cohort (p < 0.0001). Recurrence was 41.6% in the SRS cohort and 22.5% in the neuroablative cohort (p < 0.001). The neuroablative cohort reported significantly higher rates of hypoesthesia (18.6% vs. 50.5%, p < 0.0001), and minor (19.6% vs. 2.2%, p < 0.0001) and major (3.4% vs. 1.3%, p < 0.001) adverse effects compared to SRS. CONCLUSION: The findings suggest improved pain relief and reduced recurrence with neuroablative procedures compared to SRS, albeit conferring a higher rate of adverse effects. Neuroablative techniques may be more appropriate for patients with medically refractory TN who are unsuitable for microvascular decompression.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.037 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".