Radiofrequency ablation prior to total knee arthroplasty does not improve post-surgical pain or recovery: a double-blinded, multi-center, randomized clinical trial
Bibliographic record
Abstract
Background: Radiofrequency ablation (RFA) targeting the genicular nerves is an effective treatment for knee pain due to osteoarthritis. The aim of this study was to determine the effects of two RFA interventions delivered preoperatively on early postoperative pain management and subjective outcomes after total knee arthroplasty (TKA). Methods: One hundred forty-three participants were enrolled in this double blinded, sham-controlled prospective randomized trial. Participants assigned at random to traditional RFA (t-RFA) (n=50), cooled RFA (c-RFA) (n=49), or sham (n=44) procedures prior to TKA. Outcomes were recorded at postoperative day 3, week 1, week 2, week 12, month 6, and month 12 following TKA. Primary outcomes included hospital length of stay (LOS), opioid consumption (reported as MEQ, or daily morphine equivalents), time to narcotic cessation (reported in days), and pain scores (reported as NRS, or Numeric Rating Scale). Secondary outcomes included Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) measures. All side effects and complications were reported. Participants were followed for a year to detect any unexpected side effects. Results: Compared with sham controls, t-RFA and c-RFA did not affect inpatient LOS, pain scores, or opioid consumption. There were no reductions in time to opioid cessation, pain scores, or WOMAC scores at any time point post-TKA. Conclusions: RFA of the genicular nerves prior to TKA did not affect opioid use or time to cessation, pain, or WOMAC scores, following TKA. Current techniques of t-RFA and c-RFA of these specific geniculate nerves preoperatively are not indicated as routine interventions to improve short-term surgical recovery after TKA. Trial Registration: The trial was registered on ClinicalTrials.gov (NCT02925442).
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".