433 Efficacy and Safety of Surgical Decompression for Migraine: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Migraine is a common disabling disease with high socioeconomic and personal impacts. Despite various medical options, many patients suffer refractory and chronic migraines. New surgical approaches are gaining traction as viable options to treat migraines. METHODS: The study was conducted in accordance with PRISMA guidelines. An inclusive search of several databases from January 1990 to December 2nd, 2020, was performed. Studies reporting various decompression approaches of peripheral nerves for chronic or refractory migraines were included and analyzed. The risk of bias of individual studies was assessed in accordance with the modified Newcastle-Ottawa Quality Assessment Scale. Only those studies representing their data of migraine with mean frequency and intensity of headache, as well as their complication event rate, were reported. RESULTS: Total, 22 studies comprising 1377 patients with migraines were included. Mean age of patients undergoing surgery was 44.22 (95% CI 42.96 - 45.48) years. Patients underwent surgery for migraine comprising decompression of supraorbital, supratrochlear, zygomaticotemporal, or occipital nerve. Most studies reported recovery from headache with improvement in mean headache frequency (range 4.4 to 16.6 days per month) and mean headache intensity (range 2.80 to 7.30 in visual analog scale). The risk of bias was high, with the bias being high in 10 studies and moderate in 11 studies. Total complication rate was 8.0% (95% CI 4.0%-13.0%) which included paresthesia, wound infection, and hypertrophic scarring in a follow-up duration of 2 to 66 months. Heterogeneity in outcome measures and moderate-to-high risk of bias in the majority of studies precluded for meta-analysis. CONCLUSION: Despite improvement in headache frequency and intensity reported on surgical decompression for migraine, available studies reported used variable outcome measures and had moderate-to-high risk of bias.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".