Radiofrequency Facet Joint Denervation in the Treatment of Low Back Pain
Bibliographic record
Abstract
STUDY DESIGN: A prospective double-blind randomized controlled trial was performed. OBJECTIVE: To assess the efficacy of percutaneous radiofrequency articular facet denervation for low back pain. SUMMARY OF BACKGROUND DATA: Uncontrolled observational studies in patients with low back pain have reported some benefits from the use of facet joint radiofrequency denervation. Because the efficacy of percutaneous radiofrequency had not been clearly shown in previous studies, a randomized controlled trial was conducted to assess the efficacy of the technique for improving functional disabilities and reduce pain. METHODS: For this study, 70 patients with low back pain lasting of more than 3 months duration and a good response after intraarticular facet injections under fluoroscopy were assigned randomly to receive percutaneous radiofrequency articular facet denervation under fluoroscopic guidance or the same procedure without effective denervation (sham therapy). The primary outcomes were functional disabilities, as assessed by the Oswestry and Roland-Morris scales, and pain indicated on a visual analog scale. Secondary outcomes included spinal mobility and strength. RESULTS: At 4 weeks, the Roland-Morris score had improved by a mean of 8.4% in the neurotomy group and 2.2% in the placebo group, showing a treatment effect of 6.2% (P = 0.05). At 4 weeks, no significant treatment effect was reflected in the Oswestry score (0.6% change) or the visual analog pain score (4.2% change). At 12 weeks, neither functional disability, as assessed by the Roland-Morris scale (2.6% change) and Oswestry scale (1.9% change), nor the pain level, as assessed by the visual analog scale (-7.6% change), showed any treatment effect. CONCLUSIONS: Although radiofrequency facet joint denervation may provide some short-term improvement in functional disability among patients with chronic low back pain, the efficacy of this treatment has not been established.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".