A Comparison of Genicular Nerve Blockade With Corticosteroids Using Either Classical Anatomical Targets vs Revised Targets for Pain and Function in Knee Osteoarthritis: A Double-Blind, Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: Compare the effectiveness of genicular nerve blockade (GNB) using classical anatomical targets (CT) versus revised targets (RT) in patients suffering from chronic knee osteoarthritis pain. DESIGN: Double-blinded randomized controlled trial. SETTING: Pain medicine center of a teaching hospital. METHODS: We randomly assigned 55 patients with chronic knee osteoarthritis pain to receive a GNB (using a fluid mixture of 2 mL: lidocaine 1% + 20 mg triamcinolone) with either classical targets (CT-group, n = 28) or revised targets (RT-group, n = 27). Numeric rating pain scale (NRS), Oxford knee score (OKS), Western Ontario and McMaster Universities osteoarthritis index score (WOMAC), Quantitative analgesic questionnaire (QAQ) and global perceived effects were assessed at baseline, and at 1-hour, 24-hours, 1, 4, and 12 weeks post-intervention. RESULTS: The RT-group showed greater reduction in NRS mean score at 1-hour post-intervention (2.4 ± 2.1 vs 0.4 ± 0.9, 95% confidence interval (CI) [.0-.8] vs [1.6-3.2], P < .001). The proportion of patients achieving more than 50% knee pain reduction was higher in the RT-group at each follow up interval, yet these differences were statistically significant only at 1-hour post intervention (82.1% [95% CI = 63.1-93.9] vs 100% [95% CI = 97.2-100] P = .02). Both protocols resulted in significant pain reduction and joint function improvement up to 12 weeks post-intervention. CONCLUSIONS: The revised technique allowed more pain relief as well as greater proportion of successful responders at 1-hour post intervention. The large volume injected during therapeutic GNB could have compensated the lack of precision of the classical anatomical targets, mitigating differences in outcomes between both techniques.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 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".