Epidemiological Review of Relation between Gender and Traumatic Injuries in Hospitals in Iran
Bibliographic record
Abstract
BACKGROUND: Orthopedic injury including fractures of limbs, hip or spine or the injuries of soft tissue, muscles, ligaments and tendons lesions are the most common traumatic injuries these days, and impose a significant material and spiritual cost to the communities every year. The aim of this study is to evaluate the relation between injuries and the mechanism of injuries and gender. METHODS: In these studies 2480 patients with mean age of 29.9±17.8 referred to Shafa Yahyaeian Hospital in Tehran, Iran were participated. Some information of patients has been recorded during April-October in 2013. Information includes demographic characteristics, the exact mechanism of injury, radiographic imaging, CT scan, MRI were recorded. The statistical analysis performed on data with t-test, Mann-Whitney and Chi-Square tests. RESULTS: From 685 patients with lower extremity fractures, 500 (73%) were male and 185 (27%) female. Also from 332 patients with soft tissue injuries, the males were 281 (84.5%) and 51 (15.5%) female. In this study no significant relation between gender and upper and lower extremity injuries were not seen (P=0.69). The most common mechanism of trauma in male patients were fall from standing position 34.8%, direct trauma 24.6%, motorcycle crash 10% and fall from height 7.9%. Also the most common mechanism of trauma in female patients was fall from standing position 54.2%, direct trauma 15.8% and falling from stairs 7.5%. There were no significant relation between sex and trauma mechanism in this study (P=0.00). CONCLUSIONS: According to the results the frequency of fractures and soft tissue injuries were higher in male than female. The main mechanisms of injury in both groups were fall from the standing position.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".