Chemical Ablation of Genicular Nerve with Phenol for Pain Relief in Patients with Knee Osteoarthritis: A Prospective Study
Bibliographic record
Abstract
BACKGROUND: Radiofrequency ablation of the genicular nerve is performed for knee osteoarthritis (KOA) when conservative treatment is not effective. Chemical ablation may be an alternative, but its effectiveness and safety have not been examined. The objective of this prospective open-label cohort study is to evaluate the effectiveness and safety of ultrasound-guided chemical neurolysis for genicular nerves with phenol to treat patients with chronic pain from KOA. METHODS: Forty-three patients with KOA with pain intensity score (Numeric Rating Scale, NRS) ≥ 4, and duration of pain of more than 6 months were considered for enrollment. Ultrasound-guided diagnostic blocks of genicular nerves (superomedial, inferomedial, and superolateral) with 1.5 mL of 0.25% bupivacaine at each site were performed. Those who reported more than 50% reduction in NRS went on to undergo chemical neurolysis, using 1.5 mL 7% glycerated phenol in each genicular nerve. NRS and Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores were assessed before intervention and at 2 weeks and 1, 2, 3, and 6 months following the intervention. RESULTS: NRS and WOMAC scores improved at all time points. Mean pain intensity improved from 7.2 (95% confidence interval [CI]: 6.8 to 7.7) at baseline to 4.2 (95%CI: 3.5 to 5.0) at 6-month follow-up (P < 0.001). Composite WOMAC score improved from 48.7 (95%CI: 43.3 to 54.2) at baseline to 20.7 (95%CI: 16.6 to 24.7) at 6-month follow-up (P < 0.001). Adverse events did not persist beyond 1 month and included local pain, hypoesthesia, swelling, and bruise. CONCLUSION: Chemical neurolysis of genicular nerves with phenol provided efficacious analgesia and functional improvement for at least 6 months in most patients with a low incidence of adverse effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".