Free functioning gracilis transplantation for reconstruction of elbow and hand functions in late obstetric brachial plexus palsy
Bibliographic record
Abstract
BACKGROUND: In late obstetric brachial plexus palsy (OBPP), restoration of elbow and hand functions is a difficult challenge. The use of free functioning muscle transplantation in late OBPP was very scarcely reported. In this study, we present our experience on the use of free functioning gracilis transfer for restoration of elbow and hand functions in late cases of OBPP. PATIENTS AND METHODS: Eighteen patients with late OBPP underwent free gracilis transfer for reconstruction of elbow and/or hand functions. The procedure was indicated when there was no evidence of reinnervation on EMG and in the absence of local donors. Average age at surgery was 102.5 months. Patients were evaluated using the British Medical Research Council (MRC) grading system and the Toronto Active Movement Scale. Hand function was evaluated by the Raimondi scoring system. RESULTS: The average follow-up was 65.8 ± 41.7 months. Contraction of the transferred gracilis started at an average of 4.5 ± 1.03 months. Average range of elbow flexion significantly improved from 30 ± 55.7 to 104 ± 31.6 degrees (P <0.001). Elbow flexion power significantly increased with an average of 3.8 grades (P = 0.000147). Passive elbow range of motion significantly decreased from an average of 147 to 117 degrees (P = 0.003). Active finger flexion significantly improved from 5 ± 8.3 to 63 ± 39.9 degrees (P < 0.001). Finger flexion power significantly increased with an average 2.7 grades (P < 0.001). Only 17% achieved useful hand (grade 3) on Raimondi hand score. Triceps reconstruction resulted in an average of M4 power and 45 degrees elbow extension. CONCLUSION: Free gracilis transfer may be a useful option for reconstruction of elbow and/or hand functions in late OBPP.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".