Genicular Nerve Radiofrequency Ablation and Dual Subsartorial Block for Chronic Knee Pain Post Total Knee Replacement: A Case Report
Bibliographic record
Abstract
Introduction. Chronic pain defines as pain persisting for three months or longer, chronic post-surgical pain can affect all dimensions of health-related quality of life, and is associated with functional limitations. treatment of chronic pain after total knee replacement is challenging, and evaluation of combined treatments and individually targeted treatments matched to patient characteristic. Genicular nerve block radiofrequency ablation is a safe and effective therapeutic procedure for pain associated with chronic pain due to knee osteoarthritis, and the evolution of newer regional analgesia techniques aids in reducing postoperative pain Dual Subsartorial Block (DSB) as a procedure specific, post total knee replacemet. historically there has been a reliance on using a pain-spesific assessment tools Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Case Presentation. A 55-year old woman admitted she had pain on bilateral knee, the knee pain had affected her daily living, she was diagnosed with chronic knee pain post TKR because of osteoarthritis genu bilateral, the patient was planning genicular nerve radiofrequency ablation and dual subsartorial block, from the examination we found that numeric rating scale was 6 (moderate pain) with WOMAC score 76, before the procedure the patients are examined through radiology for any deformity in the knee. The genicular nerve radiofrequency ablation under ultrasound guidance on bonylandmark, resulting anesthesia of the anterior compartment of the knee, and dual subsartorial block that cover almost all the innervations of pain generating component of the anterior and posterior knee joint involved in TKR surgery. After the procedure we reevaluated the pain score using NRS was 2 (mild pain), and with WOMAC Score 19. Conclusion. Treatment of chronic pain post total knee replacemet was challenging, targeted treatment may ameliorate the pain and prevent long term disability.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".