Surgical Knee Denervation for the Treatment of Pain Caused by Primary Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Denervation techniques have increased in popularity for treatment of primary knee osteoarthritis. However, few clinical trials have been conducted on surgical knee denervation. This study was conducted to evaluate the safety and efficacy of a surgical denervation technique for the treatment of primary knee osteoarthritis. METHODS: Patients were included in the trial if they had failed conservative management for osteoarthritis with corticosteroid injections and were not candidates for total knee arthroplasty. Patients were treated with a surgical knee denervation. Preoperative and postoperative scores were assessed to examine the improvement in pain, function, and quality of life. RESULTS: Twenty-four knee denervation procedures were performed in 21 patients. The average follow-up time was 21 months, with a minimum follow-up of 12 months. Patients experienced an improvement in pain with a decrease in visual analogue scale pain scores from 8.7 to 2.9, an improvement in function with a decrease in Western Ontario McMaster Arthritis Score scores from 69 to 32, and an improvement in quality of life with an increase in European quality of life index from 0.183 to 0.646. A clinically significant improvement in pain occurred in 92% of patients, whereas 75% of patients had an improvement in function and 83% had an improvement in quality of life. CONCLUSIONS: The treatment of recalcitrant knee pain in nonarthroplasty candidates is a difficult issue. This trial suggests that a surgical denervation technique provides improvement in pain, function, and quality of life. Surgical denervation may be a beneficial treatment for patients with recalcitrant pain from primary knee osteoarthritis. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".