Sensory and pain outcomes of neurotized skin-grafted free gracilis muscle flaps for lower extremity reconstruction
Bibliographic record
Abstract
BACKGROUND: Skin-grafted free gracilis muscle flaps are commonly used for lower extremity reconstruction. However, the loss of sensory function may lead to increased patient morbidity. This study prospectively analyzed the sensory and neuropathic pain outcomes of neurotized skin-grafted free gracilis muscle flaps used for the reconstruction of lower extremity defects. METHODS: Patients undergoing lower extremity reconstructions between 2020 and 2022 with neurotized skin-grafted free gracilis muscle flaps were prospectively enrolled. Sensation was assessed at 3, 6 and 12 months postoperatively using monofilaments, two-point discrimination, a vibration device, and cold and warm metal rods. Sensations were tested in the center and periphery of the flaps, as well as in the surrounding skin. The contralateral side served as the control. Patients completed the McGill pain questionnaire to evaluate patient-reported neuropathic pain. RESULTS: Ten patients were included. At 12 months postoperatively, monofilament values improved by 44.5% compared to that of the control site, two-point discrimination, cold detection, warmth detection, and vibration detection improved by 36.2%, 48%, 50%, and 88.2%, respectively, at the reconstructed site compared to those at the control site. All sensory tests were significantly better than 3 and 6 months values (p < 0.05), but remained significantly poorer than the control site (p < 0.05). Sensation in the central flap areas were similar to peripheral flap areas throughout the follow-up period (p > 0.05). The surrounding skin reached values similar to the control site at 12 months (p > 0.05). Moreover, 50% of patients reported neuropathic pain at 3 months postoperatively, 40% at 6 months, and 0% at 12 months (p < 0.05). CONCLUSION: Mechanical detection, vibration detection, temperature detection, and two-point discrimination significantly improved over time but without reaching normal sensory function at 12 months postoperatively. Neuropathic pain resolved at 12 months.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".