Early Passive Mobilization after Digital Nerve Repair and Grafting in a Fresh Cadaver
Bibliographic record
Abstract
In the clinical management of combined tendon and nerve injuries, there are competing treatment strategies. Isolated tendon injuries should be rapidly mobilized after repair to prevent adhesion formation, whereas isolated nerve repairs are usually immobilized to prevent disruption and to allow axon regrowth. Recommendations in the published literature for the management of combined tendon and nerve injuries are vague and advise up to 3 weeks of immobilization. The goals of this study were to determine which length of nerve gap resulted in rupture of a repair following postoperative mobilization with the modified Duran protocol and with unrestricted motion and to determine whether nerve grafts are at risk of rupture after mobilization. A total of 100 digital nerves from 10 cadaver hands were tested with the modified Duran and the unsplinted protocols. Each digital nerve on each hand was sequentially resected and repaired at five progressively larger gap lengths after testing with both protocols. The mean nerve gaps at which disruption occurred were significantly different between the splinted (9.7 +/- 0.8 mm, n = 100) and unsplinted (7.3 +/- 1.9 mm, n = 100) protocols (t test, p < 0.001). One hundred percent of repairs remained intact, with up to 5 mm of resection with the modified Duran protocol (n = 100) and with up to 2.5 mm of resection with the unsplinted protocol (n = 100). All nerve grafts remained intact after mobilization within a dorsal-blocking splint (n = 100). Considering mechanical integrity of the nerve repair only, these data suggest that early mobilization with tendon protocols may be considered after a nerve injury to avoid the detrimental tendon sequelae that result from immobilization. The adequacy of functional recovery of mobilized nerves is yet to be determined.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".