Is Cooled Radiofrequency Ablation the Hot New Treatment for Knee Osteoarthritis?
Bibliographic record
Abstract
Commentary Care for patients with arthritis has enormous public health and economic implications. It is estimated that, in 2015, 91.2 million Americans were diagnosed with some type of arthritis and 61.1 million of those were in the 18 to 64-year age range1. Medical expenditures related to arthritis were estimated at nearly 140 billion dollars in 20132. Thus, optimizing treatment for knee osteoarthritis (OA) has implications for both patient function and overall health-care costs. Initial treatment of knee OA often includes activity modification, weight loss, physical therapy/exercise, and oral medications. If pain persists, more invasive measures are employed, which may include corticosteroid injection, viscosupplementation, or “biologic” agents. If these measures fail or stop providing adequate pain relief, then surgical interventions such as knee replacement are employed. In their article, Chen et al. provide evidence for a different modality of treatment for knee OA—i.e., a technique of thermally damaging the genicular nerves around the knee, thereby blocking the afferent pain signals. They compare this technique with a single injection of hyaluronic acid (HA) in a well-designed prospective, randomized, multicenter trial. The patients all had symptomatic OA, and the mean age was 63 years. Eighty-eight patients were randomized to the cooled radiofrequency ablation (CRFA) cohort and 87 patients, to the HA cohort. Because these were 2 distinctly different treatments, the patients could not be blinded. CRFA was associated with improved pain relief, higher quality of life, and better knee function compared with a single HA injection. Unfortunately, the comparator that was chosen for this study, HA, is not recommended by the American Academy of Orthopaedic Surgeons for treatment of knee OA3, which makes the comparison between CRFA and HA less clinically relevant. If one looks only at the CRFA cohort, at 6 months the patients did well with 71% obtaining a ≥50% decrease in pain, 72% reporting improvement in the Global Perceived Effect score, and a mean improvement in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score of 48%. Despite these good results, one must keep in mind that this technique is substantially more labor-intensive and more costly than an office-based injection. CRFA is usually performed in a hospital setting under fluoroscopic guidance. All patients had initial injections of lidocaine to 4 areas around the knee: the superomedial portion of the femoral condyle, superolateral portion of the femoral condyle, inferomedial portion of the tibial condyle, and anterior aspect of the knee 2 cm above the patella. A patient who obtained ≥50% pain reduction was considered a responder and then returned for thermal ablation, which was again performed under fluoroscopic guidance. Cost analysis of the 2 techniques was not provided as part of this study. It is also important to keep in mind that the study was funded by the company that produces the CRFA devices. Much of what we do in orthopaedics is geared toward reducing pain and improving function, but pain is likely a protective adaptation to keep us from further damaging something that has been injured. Joint denervation has been shown to lead to progression of knee OA in animal models4. It may be that thermally denaturing the sensory nerves around the knee in order to block the afferent transmission of pain from the knee joint allows the patient to become more active for a time but subsequently leads to more rapid progression of OA. This may also be true for other modalities of treatment such as knee injections. Loss of sensation in a joint in other settings can lead to a Charcot joint, although the authors state they did not see evidence of this at 6 months and that other longer-term studies of CRFA have not shown this to be the case. We are unable to determine the long-term outcomes of loss of knee sensation from the current study, or whether the nerves regenerate and over what time frame. We look forward to future long-term studies related to CRFA. CRFA is not likely to replace the current treatments for OA, but it may have a role in delaying the need for knee replacement in some patients or may benefit patients who are not candidates for knee replacement. Chen et al. have given us one more tool in our armamentarium for treating patients with knee OA.
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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 | 0.008 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.017 | 0.016 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".