Peripheral Nerve Injury Associated With Shoulder Trauma: A Retrospective Study and Review of the Literature
Bibliographic record
Abstract
PURPOSE: To determine the incidence of peripheral nerve injury in patients referred to an electrodiagnostic laboratory with a history of shoulder trauma. The characteristics of those presenting with the triad of shoulder dislocation, peripheral nerve injury, and rotator cuff tear were further examined. METHODS: We conducted a retrospective chart review of all patients referred to our electrodiagnostic laboratory over a 17-month period. Requisitions, clinical histories, physical findings, electrophysiological results, and radiologic investigations were reviewed. Inclusion for analysis was a clinical history of shoulder trauma and electrophysiological evidence of nerve injury. RESULTS: Of 1844 patients studied, 48 had nerve injury associated with trauma to the shoulder. Twenty presented with brachial plexopathies; 17 isolated mononeuropathies (axillary nerve was most common, 47%); and 11 multiple nerve involvement. Of the multiple nerves involved, the axillary was most commonly affected (45% axillary and musculocutaneous; 36% axillary and suprascapular). Fifteen (31%) patients had a history of shoulder dislocation, whereas 5 (10.4%) demonstrated the triad of dislocation, nerve injury, and rotator cuff tear. CONCLUSIONS: Peripheral nerve injury is an important consideration in patients with shoulder trauma. For patients presenting with nerve injury post-shoulder dislocation, it is important to consider a potential concomitant rotator cuff tear as an ongoing source of pain or weakness. Similarly, a patient with a rotator cuff tear following dislocation may have an associated peripheral nerve lesion.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".