Subbrachial approach to humeral shaft fractures: new surgical technique and retrospective case series study
Bibliographic record
Abstract
BACKGROUND: There are few surgical approaches for treating humeral shaft fractures. Here we present our results using a subbrachial approach. METHODS: We conducted a retrospective case series involving patients who had surgery for a humeral shaft fracture between January 1994 and January 2008. We divided patients into 4 groups based on the surgical approach (anterior, anterolateral, posterior, subbrachial). In all patients, an AO 4.5 mm dynamic compression plate was used. RESULTS: During our study period, 280 patients aged 30-36 years underwent surgery for a humeral shaft fracture. The average duration of surgery was shortest using the subbrachial approach (40 min). The average loss of muscle strength was 40% for the anterolateral, 48% for the posterior, 42% for the anterior and 20% for the subbrachial approaches. The average loss of tension in the brachialis muscle after 4 months was 61% for the anterolateral, 48% for the anterior and 11% for the subbrachial approaches. Sixteen patients in the anterolateral and anterior groups and 6 patients in the posterior group experienced intraoperative lesions of the radial nerve. No postoperative complications were observed in the subbrachial group. CONCLUSION: The subbrachial approach is practical and effective. The average duration of the surgery is shortened by half, loss of the muscle strength is minimal, and patients can resume everyday activities within 4 months. No patients in the subbrachial group experienced injuries to the radial or musculocutaneous nerves.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".