Pulsed Radiofrequency of the Composite NerveSupply to the Knee Joint as a New Techniquefor Relieving Osteoarthritic Pain: A PreliminaryReport
Bibliographic record
Abstract
We report a new technique for pulsed radiofrequency (PRF) of the entire nerve supply of the knee as an option in treating osteoarthritis (OA) of knee. We targeted both sensory and motor nerves supplying all the structures around the knee: joint, muscles, and skin to address the entire nociception and stiffness leading to peripheral and central sensitization in osteoarthritis. Ten patients with pain, stiffness, and loss of function in both knees were treated with ultrasonography (USG) guided PRF of saphenous, tibial, and common peroneal nerves along with subsartorial, peripatellar, and popliteal plexuses. USG guided PRF of the femoral nerve was also done to address the innervation of the quadriceps muscle. Assessment of pain (Numerical Rating Scale [NRS], pain DETECT, knee function [Western Ontario and McMaster Universities Osteoarthritis Index- WOMAC]) were documented pre and post PRF at 3 and 6 months. Knee radiographs (Kellgren-Lawrence [K-L] grading) were done before PRF and one week later. All the patients showed a sustained improvement of NRS, pain DETECT, and WOMAC at 3 and 6 months. The significant improvement of patellar position and tibio-femoral joint space was concordant with the patient's reporting of improvement in stiffness and pain. The sustained pain relief and muscle relaxation enabled the patients to optimize physiotherapy thereby improving endurance training to include the daily activities of life. We conclude that OA knee pain is a product of neuromyopathy and that PRF of the sensory and motor nerves appeared to be a safe, effective, and minimally invasive technique. The reduction of pain and stiffness improved the knee function and probably reduced the peripheral and central sensitization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".