Prospective Within Subject Comparison of Fluoroscopically Guided Lumbosacral Facet Joint Radiofrequency Ablation Using a Multi-Tined (Trident) Versus Conventional Monopolar Cannula.
Bibliographic record
Abstract
BACKGROUND: Radiofrequency ablation (RFA) for the lumbar facet joints has demonstrated efficacy in the management of chronic low back pain. The traditional technique uses a conventional monopolar (CM) cannula placed parallel to the putative nerve to produce a thermal lesion resulting in pain relief of the facet joints. A new multi-tined (MT) cannula has come onto the market that allows targeting the putative nerve using a perpendicular to the nerve approach. OBJECTIVES: This study describes the technique using the MT cannula and compares its efficacy and procedural characteristics to the CM cannula. STUDY DESIGN: This is a pre-post crossover observational study. METHODS: Fifty-one patients were recruited between June 2015 and March 2020. Each patient underwent 2 fluoroscopic guided lumbosacral RFA procedures on 2 separate occasions at the same facet joints, using the CM and MT cannula consecutively. The primary outcome measure was change in pain on the 11-point numeric rating scale (NRS). Secondary outcome measures included change in Pain Disability Quality of Life Questionnaire (PDQQ) score, duration and magnitude of pain relief, local anesthetic use, adverse events, procedural and fluoroscopy exposure time, and radiation dose. RESULTS: There were no statistically significant difference between CM versus MT canula in terms of absolute (4.0 versus 4.3) and relative (52% versus 57%) change in NRS (P = 0.99) and PDQQ (22 versus 22, P = 0.61) at 3 months, or overall pain magnitude (71% versus 72%, P = 0.96) and duration of relief (8.7 months versus 8.4 months, P = 0.68). The procedures using the MT cannula were completed faster (37.6 minutes versus 31.1 minutes, P < 0.001) and required less local anesthetic (15.8 mL versus 11.0 mL, P < 0.001) and radiation dose (41.5 mGy versus 30.2 mGy, P = 0.05). No adverse events were observed with either cannula. LIMITATIONS: This was an observational study at a single center with the proceduralist not blinded to the intervention. CONCLUSION: This study demonstrated that the outcomes in terms of pain, disability, quality of life, adverse events, and fluoroscopy exposure time were equivalent between the 2 cannulae. However, RFA using the MT cannula was faster to perform and involved less local anesthetic and radiation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".