Direct Repair of Ruptured Nerve Stump to Middle Trunk for Restoration of Extrinsic Finger Extension in Total Brachial Plexus Injuries
Bibliographic record
Abstract
BACKGROUND: Attempts to restore independent hand function in total brachial plexus injuries (TBPIs) have often failed due to inconsistent results of finger extension reconstruction. An innovative technique is described to achieve this effect by direct neurorrhaphy of residual (ruptured) roots with the middle trunk. METHODS: Direct coaptation of the ruptured roots to the middle trunk and, simultaneously, transferring the anterior division of the middle trunk to the posterior division of the lower trunk was performed in 64 patients with TBPI. The return of extension of the elbow, wrist, and fingers was monitored. RESULTS: Excellent and good muscle strength of finger extension were noted in 45.3% of cases. The patients were divided into group A (>32 years) and group B (≤32 years) according to receiver operating characteristic curve analysis. The difference of excellent and good rates of finger and wrist extension muscle strengths between the 2 groups was statistically significant (χ 2 = 4.635, P = 0.031; χ 2 = 6.615, P = 0.010). CONCLUSIONS: Direct neurorrhaphy of ruptured nerve root stumps with the middle trunk could achieve satisfactory results for finger extension in TBPI for patients ≤32 years old. Long nerve defects (4 to 6.5 cm) could be overcome by freeing the nerve and adducting the arm against the trunk. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".