Randomized controlled trial comparing technical features and clinical efficacy of a multi-tined cannula versus a conventional cannula for cervical medial branch radiofrequency neurotomy in chronic neck pain
Bibliographic record
Abstract
Objectives: Compare procedural characteristics and clinical efficacy of cervical medial branch radiofrequency neurotomy (CMBRFN) using a multi-tined cannula (MTC) versus a conventional cannula (CC) to treat chronic neck pain. Design: Prospective, double-blinded randomized controlled trial. Methods: Patients who responded to dual medial branch blocks with ≥75% pain relief were randomized to receive RFN with either the MTC or the CC. Primary outcomes: procedural pain, procedure duration, fluoroscopy time and radiation dose. Secondary outcomes: proportion of patients reporting ≥50% numerical rating scale reduction and ≥30% neck disability index reduction at 3, 6 and 12 months. Results: Forty-two patients underwent treatment. There was no difference in procedural pain between the MTC and CC groups (NRS 4.7 ± 2.0 vs. 4.2 ± 1.8, p = 0.465), but three patients, all in the CC group, could not complete the procedure due to pain. CMBRFN in the MTC group was significantly faster than in the CC group (35.5 ± 7.3 min vs. 58.2 ± 14.8 min, p < 0.001), with less fluoroscopy time (167.6 ± 76.4 s vs. 260.8 ± 123.5 s, p = 0.004). Radiation dose was 8.95 ± 7.9 mGy in the MTC group and 11.53 ± 10.3 mGy in the CC group (p = 0.36). Rates of ≥50% NRS reduction were not significantly different between the two groups at 3 months, but at 6 and 12 months, they were significantly higher in the CC group. At 3, 6 and 12 months, rates of ≥30% NDI reduction were significantly higher in the CC group. Conclusions: The MTC offers technical advantages compared to the CC for both the operator and the patient. However, CMBRFN with the multi-tined cannula seems less effective to treat neck pain than with the conventional cannula.
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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 | 0.003 | 0.005 |
| 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 | 0.002 | 0.002 |
| 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".