Radiofrequency denervation of the hip joint for pain management: case report and literature review.
Bibliographic record
Abstract
BACKGROUND: A 55-year-old male presented with severe pain and functional limitations as a result of left hip osteoarthritis. He had failed multiple treatments while waiting for a hip arthroplasty, including physical therapy, medications, and various intra-articular injections. Thermal radiofrequency lesioning of the obturator and femoral articular branches to the hip joint was offered in the interim. OBJECTIVES: To our knowledge, this is the first report to describe an inferior-lateral approach for lesioning the obturator branch, the clinical application of successive lesions to increase denervation area, and outcomes in a patient receiving a second treatment with previously good results. METHODS: To discuss relevant and technical factors for this specific case, we reviewed previous literature on hip joint radiofrequency and critically evaluated previous anatomic studies in the context of radiofrequency. RESULTS: The first treatment provided significant benefit for a period of 6 months. A second treatment was employed providing only mild to moderate benefit until his joint replacement surgery 4 months later. Literature review revealed studies of low quality secondary to small sample sizes, patient selection methodology, inclusion of patients with heterogenous etiologies for pain, variable needle placement techniques, and lack of measurement of functional outcomes. LIMITATIONS: Case report and low quality studies in existing literature. CONCLUSIONS: Hip joint radiofrequency denervation is a promising avenue for adjunctive treatment of hip pain. Further cadaveric studies are required to clarify a multitude of technical parameters. Once these are well defined, future clinical studies should consider pain, functional, and economic outcomes in their design.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".