End-on versus parallel radiofrequency lesioning for neurotomy of the cervical medial branch nerves: a study protocol of a prospective, randomized, double-blind clinical trial: the “EndPaRL” study
Bibliographic record
Abstract
BACKGROUND: Cervical facet joint disease is a common source of neck pain and its prevalence increases with aging. Conservative multimodal management options (e.g., strengthening of neck muscles, non-steroidal anti-inflammatory medications, massage, and thermal modalities) often fail to relieve pain. Cervical medial branch nerve (CMBN) radiofrequency neurotomy (RFN) is an effective minimally invasive technique for treating chronic neck pain secondary to facet joint disease. An end-on approach for this procedure has been proposed that may be technically easier and require less time while reducing post-procedural discomfort. The protocol presented here is for a study that aims to compare the efficacy of a new end-on approach using multi-tined cannulae, against the conventional parallel technique that employs straight cannulae for RFN of the CMBN in patients with chronic neck pain due to cervical facet joint disease. METHODS: A multicentre randomized, non-inferior, active comparator-controlled trial will be conducted with two parallel groups and blinding of participants and outcome assessor. The study will include 72 adults with chronic neck pain secondary to facet joint disease who are candidates for RFA of the CMBN. Participants will be randomized to either the conventional parallel or the end-on approach in a 1:1 ratio. The intensity of pain and pain-related domains (function, quality of life, sleep, adverse effects of the interventions, analgesic intake) will be measured at 1, 3, 6, and 12 months after the procedure. DISCUSSION: Neck pain secondary to cervical facet joint disease is prevalent and RFA of the CMBN is a validated treatment for relieving it. The conventional parallel technique can be technically challenging, and it can be associated with adverse effects while the newer end-on approach has the potential of being a simpler technique with less adverse effects. This trial will be the first non-inferiority study to compare the clinical efficacy of the end-on approach against the conventional parallel approach for RFN of CMBN in patients with chronic neck pain due to cervical facet joint disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT05818774. Registered on April 20, 2023.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".