Lesser Occipital Nerve Decompression through a Single Vertical Midline Incision Reduces Reoperation Rates
Bibliographic record
Abstract
BACKGROUND: Nerve decompression surgery for occipital neuralgia of the lesser occipital nerve (LON) is often performed in combination with treatment of the greater occipital nerve (GON) and the third occipital nerve. The traditional surgical approach of combined GON/LON decompression requires multiple separate incisions. This study describes a single vertical midline incision approach and reports on the postoperative outcomes. METHODS: Among 1713 patients who were screened for nerve decompression surgery between 2011 and 2023, those who underwent combined GON/LON decompression for treatment of occipital neuralgia were identified retrospectively. Patients who underwent the single vertical midline incision approach were compared with those who underwent the separate incision approach. Outcomes included postoperative complications; LON reoperation; pain frequency (days per month), intensity (scale, 0 to 10), and duration (hours); and Migraine Head Index at final follow-up. RESULTS: A total of 124 patients underwent 184 combined GON/LON operations. LON decompression was performed through a midline incision in 91 patients (73.4%) and through a separate incision in 33 patients (26.6%). LON reoperation rates for pain recurrence were higher in the separate incision group as compared with the midline incision group (15.2% versus 4.4%; P < 0.05). At a median follow-up of 17.9 months after the last intervention, reductions in pain frequency, intensity, duration, and Migraine Head Index were comparable between both techniques ( P > 0.05). Postoperative complications were not significantly different between both groups ( P > 0.05). CONCLUSION: During combined GON/LON surgery, approaching the LON through the midline incision is feasible and allows for safe and effective LON decompression or neurectomy, with lower reoperation rates for recurrent pain. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".