Ultrasound vs. fluoroscopic guidance in genicular nerve radiofrequency thermocoagulation for chronic knee pain: which one is the future?
Bibliographic record
Abstract
OBJECTIVE: Fluoroscopic guiding is commonly utilized for interventional pain management procedures. However, ultrasonography has started to be used more widely in interventional pain procedures. It has become even more popular with its advantages. The clinician who performs the pain procedure and the patient are not exposed to radiation. Vascular structures can be directly visualized. Ultrasonography is more accessible and portable than fluoroscopy. For all these reasons, its use will increase. So, in this study, we aimed to compare the efficacy of the genicular nerve radiofrequency thermocoagulation application under ultrasound guidance and fluoroscopy guidance. PATIENTS AND METHODS: Patients with stage 2 and 3 osteoarthritis, according to the Kellgren-Lawrence classification, were included in our study (n=180). Seventy percent of patients were women. Sixty patients received medical treatment only. Genicular nerve radiofrequency thermocoagulation was performed with fluoroscopy in sixty patients and with ultrasonography guidance in sixty other patients. Visual Analogue Scale at 1 month (VAS1) and Western Ontario and McMaster Universities Arthritis (WOMAC1) were recorded before the procedure, while VAS2 and WOMAC2 were recorded at 3 months. RESULTS: In the ultrasound and fluoroscopy group, a statistically significant difference was found between VAS1 and VAS2, WOMAC1 and WOMAC2 (p<0.05). VAS1 of the patients in the fluoroscopy group was 6.65±0.93, and it was 5.88±0.92 in the ultrasonography group, which was similar (p<0.0001). VAS2 was 2.26±1.16 in the ultrasonography group and 3.83±1.66 in the fluoroscopy group (p<0.0001). The reduction rate in pain severity in patients undergoing the procedure under ultrasonography guidance was more marked than that in the fluoroscopy group (p<0.0001). CONCLUSIONS: For the radiofrequency thermocoagulation of the genicular nerve, both imaging approaches are available. Ultrasonography guidance appears to be better than fluoroscopy guidance in this technique because of the lower radiation dose and the ability to detect the target location and neighboring tissues more precisely under ultrasonography guidance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".