Scapular fractures: A regional and rural perspective
Bibliographic record
Abstract
INTRODUCTION: Scapular fractures (SFs) have historically been associated with severe trauma and multiple injuries. Recent studies have demonstrated improved outcomes. However, SFs have never been studied from a strictly rural or Australian perspective. OBJECTIVE: The study's objective was to assess whether associations still exist between a fractured scapula and trauma scores, mortality rates, and other commonly associated injuries in a regional Australian trauma centre. DESIGN: The study design examined prospectively collected data from a regional hospital between the years 2012 to 2021 presenting to the emergency department with traumatic SFs. Primary outcomes of interest were mortality rate, method of injury, ISS scores, and associated injuries. FINDINGS: One hundred and five patients had a SF. The median age was 49 with 93 (89%) being male. Most fractures were located in the body of the scapula (80%). The primary mechanism of injury was motorbike accidents (36%), falls (24%), and motor vehicle accidents (22%). Two patients died from their injuries (1.9%). Thirty-four percent demonstrated mild trauma scores, with 36% moderate, 28% severe, and 1.9% critical. Commonly observed associated injuries included chest wall fractures, vertebral fractures, thoracic injuries, brain injury, and abdominal trauma. DISCUSSION: A minority of SFs were associated with severe or critical trauma, and overall, patients who sustained a SF had a low mortality rate. These findings suggest that patients from regional areas have similar outcomes to those from more urban centres in other parts of the world. CONCLUSION: Given these results, a re-examination of whether SFs are a reliable marker of severe trauma should be considered.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".