Prospective cohort study of electrodiagnostic abnormality characterization in pronator quadratus associated with end-to-side nerve transfers for ulnar neuropathy at the elbow
Bibliographic record
Abstract
Abstract Ulnar neuropathy at the elbow (UNE) is a common compressive neuropathy that affects the median nerve. Conservative management for mild-to-moderate UNE is an important first step, but generally, develops a plateau in benefit. A specific technique, referred to as a supercharged ‘end-to-side’ (SETS) nerve transfer can successfully restore pinch, fine motor dexterity and grip strength. A pre-surgical workup flow for UNE patients has been developed, which includes electrodiagnostic (EDX) studies completed to assess the recipient ulnar nerve and the donor median nerve to pronator quadratus (PQ). There is little evidence that the assessment of the PQ muscle is necessary in a non-traumatic setting. A prospective cohort study of patients who present with clinical and/or EDX evidence of ulnar compressive neuropathy, with clinical evidence of motor dysfunction, was assessed for health PQ donor in routine pre-operative workup. We aim to provide justification that SETS for UNE should not be delayed to acquire PQ EDX studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".