SCOPING: A Pilot Study Exploring the Role of A Series of Clinical Observational Parameters as Indicators of Nerve Regeneration
Bibliographic record
Abstract
Background: Following the repair of a mixed peripheral nerve, functional recovery requires successful nerve regeneration across the repair site and, eventually, reinnervation of distal targets. Reliably determining a failing nerve repair so that revision may be performed before irreversible muscle atrophy remains a challenge in peripheral nerve surgery. This study aimed to ascertain whether any commonly used clinical examination tests during surveillance after nerve repair can detect a failing repair and prompt earlier salvage intervention. Methods: A prospective observational cohort study was performed to evaluate commonly used clinical determinants of neuron regeneration that may provide early surrogate recovery measures. Sequential cutaneous thermography was used to identify temperature differences between denervated and normal skin in the hand operated on, with the contralateral hand as a control. Results: Six out of nine patients completed between 6 and 18 months of follow-up. Tinel sign progression was observed in all subjects. Tinel progression rate was associated with motor and sensory Medical Research Council grade. The delta temperature was calculated to document the size and direction of any temperature differentials in the hand detected by thermography, but we did not have sufficient data to calculate any correlations with motor and sensory Medical Research Council grade. Conclusions: Specifically, the progression of Tinel sign is associated with recovery measured by progression of the British Medical Research Council motor and sensory grades. The use of thermographic imaging demonstrates that there is a difference in temperature between an injured and noninjured nerve. Future studies could investigate to what extent thermographic imaging predicts final nerve repair outcomes.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".