Femoral nerve decompression and sartorius-to-quadriceps nerve transfers for partial femoral nerve injury: a cadaveric study and early case series
Bibliographic record
Abstract
OBJECTIVE: Partial femoral nerve injuries cause significant disability with ambulation. Due to their more proximal and superficial location, sartorius branches are often spared in femoral nerve injuries. In this article, the authors report the benefits of femoral nerve decompression, demonstrate the feasibility of sartorius-to-quadriceps nerve transfers in a cadaveric study, describe the surgical technique, and report clinical results. METHODS: Four fresh-frozen cadaveric lower limbs were dissected for anatomical analysis of the sartorius nerve. In addition, a retrospective review of patients with partial femoral nerve injuries treated with femoral nerve decompression and sartorius-to-quadriceps nerve transfers was conducted. Pre- and postoperative knee extension Medical Research Council (MRC) grades and pain scores (visual analog scale) were collected. RESULTS: Up to 6 superficial femoral branches innervate the sartorius muscle just distal to the inguinal ligament. Each branch yielded an average of 672 nerve fibers (range 99-1850). Six patients underwent femoral nerve decompression and sartorius-to-quadriceps nerve transfers. Four patients also had concomitant obturator-to-quadriceps nerve transfers. At final follow-up (average 13.4 months), all patients achieved MRC grade 4-/5 or greater knee extension. The average preoperative pain score was 5.2, which decreased to 2.2 postoperatively (p = 0.03). CONCLUSIONS: Femoral nerve decompression and nerve transfer using sartorius branches are a viable tool for restoring function in partial femoral nerve injuries. Sartorius branches serve as ideal donors in quadriceps nerve transfers because they are expendable, are close to their recipients, and have an adequate supply of nerve fibers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".