Pulsed Radiofrequency Neuromodulation of the Greater Occipital Nerve for the Treatment of Headache Disorders in Adults: A Systematic Review
Bibliographic record
Abstract
Background: Pulsed radiofrequency neuromodulation (PRFN) of greater occipital nerve (GON) is considered in patients with headaches failing to achieve sustained analgesic benefit from nerve blocks with local anesthetic and steroids. However, the evidence supporting this practice is unclear. Aims: This narrative systematic review aims to explore the effectiveness and safety of GON PRFN on headaches. Methods: Databases were searched for studies, published up to February 1, 2024, investigating PRFN of GON for adults with headaches. Abstracts and posters were excluded. Primary outcome was change in headache intensity. Secondary outcomes included effect on monthly headache frequency (MHF), mental and physical health, mood, sleep, analgesic consumption, and side-effects. Two reviewers screened and extracted data. Results: Twenty-two papers (2 randomized controlled trials (RCT), 11 cohort, and 9 case reports/series) including 608 patients were identified. Considerable heterogeneity in terms of study design, headache diagnosis, PRF target and settings, and image-guidance was noted. PRFN settings varied (38-42°C, 40-60 V, and 150-400 Ohms). Studies demonstrated PRFN to provide significant analgesia and reduction of MHF in chronic migraine (CM) from 3 to 6 months; and significant pain relief for ON from six to ten months. Mild adverse effects were reported in 3.1% of cohort. A minority of studies reported on secondary outcomes. The quality of the evidence was low. Conclusions: Low-quality evidence indicates an analgesic benefit from PRFN of GON for ON and CM, but its role for other headache types needs more investigation. Optimal PRFN target and settings remain unclear. High-quality RCTs are required to further explore the role of this intervention. PROSPERO ID CRD42022363234.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 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) | 0.005 | 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".