Anterior nerves of the knee (ANK) block: A novel motor sparing fascial plane block for analgesia of the knee: Observational cohort study
Bibliographic record
Abstract
Knee osteoarthritis is a widespread disorder that may contribute to severe chronic pain. Multiple nerve blocks are implemented for analgesia of the knee, which have some restrictions, including the need for multiple injections, making the procedure complicated. We aimed to introduce a novel ultrasound-guided nerve block technique for analgesia of the knee. The study presents a description of the anterior nerves of the knee block and its application to individuals with knee osteoarthritis. Local anesthetic was injected (20 mL of 0.25% bupivacaine) within the fascia between the rectus femoris and vastus muscles in 42 patients with severe knee pain. The pain charts of the patients were reviewed and numerical rating pain scores (NRS) before and 1st hour, 1st month after the block were evaluated. First-month Western Ontario and McMaster Universities Arthritis Index (WOMAC) was also reviewed. The block was also performed in a fresh embalmed cadaver with methylene blue to identify the distribution of the injected dye. The mean age of patients was 65.3 ± 7.8 years. The mean NRS before block performance was 8.0 ± 1.2. The NRS score at 1 hour and 1 month after the block, decreased to 1.5 ± 1 and 4.4 ± 1.2, respectively. The decrease was statistically and clinically significant (P = .000). Mean WOMAC score was 71.6 ± 14.5 before the block which decreased to 42.7 ± 14.9 one month after the block (P = .000). No muscle weakness, motor block, or block-related complications were observed. Methylene blue spread in the cadaver was between the rectus femoris and vastus muscles, covering the nerves that innervate the anterior region of the knee. The novel anterior nerves of the knee block provided sufficient analgesia at the first hour and first month, and improved 1-month WOMAC scores in patients with chronic pain at the anterior of knee.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".