Genicular nerve and fracture site chemical neurolysis for distal femoral fracture: a case report
Bibliographic record
Abstract
BACKGROUND: Distal femur fractures account for approximately 3%-6% of all femoral fractures. Non-operative management may be an attractive option for the elderly with significant perioperative mortality risk. Adequate pain control is a major barrier to non-operative fracture management. Chemical neurolysis has been described for analgesic management of proximal hip fractures, however no description of interventional management of distal femur fracture exists in literature. We describe a case of phenol chemical neurolysis of genicular nerves in addition to injection at the site of fracture to provide effective analgesia for distal femur fracture. CASE PRESENTATION: A patient in their 90s with a witnessed mechanical fall sustained an intra-articular displaced fracture of the distal right femur shaft with extension into the distal femoral condyle. The patient elected to undergo non-surgical management given the high perioperative mortality risk. Acute pain service was involved and multimodal oral analgesics including opioids were insufficient in managing the patient's pain. The addition of femoral nerve catheter local anesthetic infusion did not sufficiently improve analgesia. Phenol chemical neurolysis of the superolateral, superomedial, inferomedial genicular nerves and of the fracture site was offered and performed. Resting pain decreased from Numerical Rating Scale 5/10 to 0/10 on postprocedure day 1. This was sustained at the 2-month timepoint. CONCLUSIONS: We report the successful use of phenol neurolysis of genicular nerves and the fracture site in an elderly patient with a conservatively managed distal femur fracture. These interventions resulted in improved analgesia and achieved prolonged duration of effect.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".