An Early Shoulder Repositioning Program in Birth-Related Brachial Plexus Injury: A Pilot Study of the Sup-ER Protocol
Bibliographic record
Abstract
BACKGROUND: Birth-related brachial plexus injury (BRBPI) occurs in 1.2/1,000 births in British Columbia. Even in children with "good" recovery, external rotation (ER) and supination (Sup) are often weaker, and permanent skeletal imbalance ensues. A preventive early infant shoulder passive repositioning program was created using primarily a novel custom splint holding the affected arm in full ER and Sup: the Sup-ER splint. The details of the splint and the shoulder repositioning program evolved with experience over several years. This study reviews the first 4 years. METHODS: A retrospective review of BCCH patients managed with the Sup-ER protocol from 2008 to 2011 compared their recovery scores to matched historical controls selected from our database by two independent reviewers. RESULTS: The protocol was initiated in 18 children during the study period. Six were excluded due to the following: insufficient data points, non-compliance, late splint initiation, and loss to follow-up. Of the 12 matches, the Sup-ER group final score at 2 years was better than controls by 1.18 active movement scale (AMS) points (p = 0.036) in Sup and 0.96 AMS points in ER (but not statistically significant (p = 0.13)). Unexpectedly, but importantly, during the study period, zero subjects were assessed to have the active functional criteria to indicate brachial plexus reconstruction, where previously we operated on 13 %. CONCLUSIONS: Early application of passive shoulder repositioning into Sup and ER may improve outcomes in function of the arm in infants with BRBPI. A North American multi-site randomized control trial has been approved and has started recruitment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".