Shoulder Rotation Function Following the Sup-ER Protocol in Children with Brachial Plexus Injuries
Bibliographic record
Abstract
Background : Our group previously developed an upper extremity repositioning (Sup-ER) protocol for brachial plexus birth injuries (BPBIs) that may improve supination and external rotation (ER) at 2 years of age. Questions were raised about the potential for the protocol to cause internal rotation (IR) deficits. The goal of this study was to explore the longer-term outcomes of the Sup-ER protocol and investigate IR/ER function. Methods : This prospective cross-sectional cohort study examined 16 children older than 4 years of age with significant enough BPBI to be treated with the Sup-ER protocol. Total shoulder and elbow function were assessed, including passive and active ranges of motion and strength of IR and ER. Results : Range of motion (ROM) for most active movements was decreased in the affected compared to unaffected arm. Notably, IR passive ROM was similar in the affected (78.7°) and unaffected arm (82.8°). External rotation strength of the affected arm was weaker (42.8 N) compared to the unaffected arm (57.9 N). IR strength had a greater deficit in the affected (43.2 N) arm compared to the unaffected arm (72.2 N), but both ER and IR showed less deficit than described in the literature. Conclusions : Despite differences in ranges of motion between the affected and unaffected arms, ROMs for the affected arm were comparable to the functional limits as reported in the literature. The Sup-ER protocol shows potential to optimize long-term shoulder rotation function in children with BPBI without compromising IR.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".