Fluoroscopy-guided high-intensity focused ultrasound neurotomy of the lumbar zygapophyseal joints: a prospective, open-label study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to investigate safety and effectiveness of a fluoroscopy-guided high-intensity focused ultrasound (HIFU) system for thermal ablation of the lumbar medial branch nerves. METHODS: This dual center prospective cohort study enrolled 30 participants with lumbar zygapophyseal joint syndrome. Each participant previously had a positive response to either a single diagnostic analgesic block or radiofrequency ablation (RFA). The primary effectiveness outcome was individual responder rate, defined as a reduction of two points or more on the pain intensity numerical rating scale without an increase in opioid intake, or a reduction in opioid intake without an increase in pain at 6 months after the intervention. The primary safety outcome was procedure-related or device-related adverse events (AEs). Secondary outcome variables included MRI evidence of tissue ablation, Oswestry Disability Index, 12-Item Short Form Health Survey, Brief Pain Inventory, and Patient Global Impression of Change. RESULTS: The individual responder rate was 89.7% at 2 days, 89.7% at 7 days, 72.4% at 14 days, 82.1% at 30 days, 59.3% at 90 days and 82.6% at 180 days. The average Numeric Rating Scale for pain severity decreased from 7.1 at baseline to 3.0 (N=29) after 2 days, 3.0 (N=29) after 7 days, 3.1 (N=29) after 14 days, 3.2 (N=28) after 30 days, 4.3 (N=27) after 90 days, and 3.3 (N=23) after 180 days. All participants tolerated the procedure well with no significant side effects or complications. CONCLUSIONS: Fluoroscopy-guided HIFU neurotomy achieved clinical responses comparable with RFA, and there were no significant device-related or procedure-related AEs. TRIAL REGISTRATION NUMBER: NCT04129034.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".