Shoulder Function following Primary Axillary Nerve Reconstruction in Obstetrical Brachial Plexus Patients
Bibliographic record
Abstract
BACKGROUND: In obstetrical brachial plexus palsy, suprascapular nerve reinnervation is a priority. For the most favorable outcomes in shoulder function, it is the authors' policy to also reconstruct the axillary nerve with intraplexus donors to the posterior cord (early cases) or directly with intraplexus or extraplexus motor donors (late cases). METHODS: Between 1979 and 2003, 80 consecutive patients (82 brachial plexuses) underwent plexus exploration and nerve reconstruction for obstetrical palsy. Axillary nerve reconstruction was performed in 60 plexuses, and evaluation of the results was carried out for 55 patients (56 plexuses) with adequate follow-up (mean follow-up, 6.5 years). RESULTS: Overall, there were good and excellent results (>/=M3+) in 49 of 56 plexuses (87.5 percent) for the deltoid muscle, and the average postoperative muscle grade for the deltoid was 3.89 +/- 0.79. The average shoulder abduction increased from 35 +/- 31 degrees preoperatively to 109 +/- 35 degrees postoperatively (average gain, 74 degrees), and the average external rotation increased from -13 +/- 28 degrees preoperatively to 47 +/- 18 degrees postoperatively (average gain, 60 degrees). The timing of surgery and the type of paralysis significantly influenced the final outcome. CONCLUSIONS: Reconstruction of the axillary nerve should always be performed to maximize the final outcome of shoulder function in obstetrical brachial plexus patients. The best results were seen in early cases (</=3 months), where the posterior cord was reconstructed from intraplexus donors. In late cases, reconstruction of the axillary nerve directly from the intercostal nerves could be a reliable option.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".