TMRpni: Combining Two Peripheral Nerve Management Techniques
Bibliographic record
Abstract
Amputee patients suffer high rates of chronic neuropathic pain, residual limb dysfunction, and disability. Recently, targeted muscle reinnervation (TMR) and regenerative peripheral nerve interface (RPNI) are 2 techniques that have been advocated for such patients, given their ability to maximize intuitive prosthetic function while also minimizing neuropathic pain, such as residual and phantom limb pain. However, there remains room to further improve outcomes for our residual limb patients and patients suffering from symptomatic end neuromas. "TMRpni" is a nerve management technique that leverages beneficial elements described for both TMR and RPNI. TMRpni involves coaptation of a sensory or mixed sensory/motor nerve to a nearby motor nerve branch (ie, a nerve transfer), as performed in traditional TMR surgeries. Additionally, the typically mismatched nerve coaptation is wrapped with an autologous free muscle graft that is akin to an RPNI. The authors herein describe the "TMRpni" technique and illustrate a case where this technique was employed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".