Diz Osteoartriti Ağrısının Tedavisinde Ultrason Kılavuzluğunda Genikuler Sinir Alkol Nörolizi
Bibliographic record
Abstract
Objective: Chemical neurolysis of genicular nerves is an increasingly common procedure for knee osteoarthritis (KOA) pain. This study aimed to evaluate the efficacy of alcohol neurolysis of the genicular nerves in KOA pain. Methods: Patients with KOA underwent superior medial, superior lateral and inferior medial genicular nerves alcohol neurolysis after ≥ 50% pain relief following diagnostic genicular nerve blocks. Numeric rating scale (NRS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were evaluated at baseline, 1 and 3 months after the procedure. Our primary outcome was pain relief, as revealed by the change in NRS scores. Secondary outcomes were changes in WOMAC score and the incidence of procedure-related adverse events. Results: Fifty-one patients who met the inclusion criteria were included. The median baseline NRS score was 8, and the 1st and 3rd month scores were 3. The median WOMAC score at the baseline was 68. It was 30.25 at month 1 and 30 at month 3. The reduction in NRS and WOMAC scores was significant at both times compared with baseline (p<0.001). Genicular alcohol neurolysis provided 50% or more pain relief in 64.7% of the patients at the 3rd month follow-up. Paresthesia was observed in five (9.8%) patients and hypoesthesia in two (3.9%) patients, but these adverse events resolved within one month without treatment. Conclusion: Genicular nerve alcohol neurolysis may be a good alternative to more expensive methods, such as radiofrequency, with low cost, and high efficacy. Further studies are needed to determine the ideal alcohol dose. Keywords: Osteoarthritis, knee, denervation, paresthesia, hypoesthesia, ultrasonography
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.008 | 0.002 |
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".