Understanding surgical decision-making in patients with traumatic upper extremity peripheral nerve injury: A retrospective cohort study
Bibliographic record
Abstract
PURPOSE: Careful patient selection and optimal surgical timing are essential to the success of nerve transfers. It is important to understand what factors contribute to this decision-making. The purpose of this study was to describe the characteristics of patients referred to interdisciplinary peripheral nerve clinics with traumatic upper extremity injuries and compare those who went on to nerve transfer surgery with those who did not. METHODS: Patient and injury characteristics, preoperative physical examination and electrodiagnostic findings, and patient-reported outcome measures were examined. Inclusion criteria were subjects ≥18 years of age presenting to an interdisciplinary peripheral nerve clinic with traumatic upper extremity peripheral nerve injuries. Subjects were stratified into surgical and non-surgical groups for comparison. RESULTS: Eighty-three subjects met the inclusion criteria, and 36 subjects received nerve transfer surgery. More male subjects went on to have surgery than female subjects. The surgical group demonstrated a significantly higher ratio of weak and denervated muscle groups than the non-surgical group (p < 0.05). No other statistically significant differences were identified between operative and non-operatively managed subjects. CONCLUSION: Subjects that received nerve transfer surgery demonstrated a significantly higher ratio of weak and denervated muscles than those managed non-surgically, and males were disproportionately represented in the surgical group. These findings suggest that anticipated motor recovery is the most important factor driving surgical decision-making and that male subjects may be more likely to proceed with surgery. Understanding which patients undergo nerve transfer surgery allows clinicians to interrogate their decision-making, address patient-related barriers to surgery, and better understand surgical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".