A Comprehensive Analysis of Dispatching of Traumatic Brain Injuries in the Fifth Period at the RAJAIE Hospital in Ghachsaran
Bibliographic record
Abstract
INTRODUCTION: Increasing car accidents in young group and head-stroke mechanisms in developing countryis are the main cause of brain lesions and injuries related to trauma, so that traumatic severe brain lesions and injuries and uncontrollable hemorrhage are the major cause of mortality and morbidity due to trauma. Statistical analysis and factors along with main injuries can give us useful information in the field of injury management, patient dispatching management, proper scheduling, and patients dispatching to appropriate centers. MATERIALS & METHODS: This research is a retrospective descriptive study with trend method in which data such as age, sex, mechanism of injury, severity of injuries, the kind of lesion, dispatching indications, patient accepting hospital, dispatching physician were extracted and analyzed by SPSS software in a five-year period from 2009-2013 using the files of patients referred to emergency department of Shahid Rajayi hospital of Gachsaran due to brain trauma. RESULTS: From total 760 patients, 455 People (9.67%) were male, and 215 (1.32%) were female. The highest rate of dispatching has been related to the year 2012 with 213 (3.18%) People. The most prevalent age group was 20 to 45 years old with 308 people dispatched. The most common type of traumatic mechanisms was due to bikes and cars injuries (79.7%) and then other various factors such as: falling from height (16.9%) and dispute and contention (3.4%). 66.9 percents of these injuries were slight. There was significant relationship between distribution of lesions severity resulted from trauma and the kind of injury mechanism (p<0.0001). CONCLUSION: according to the fact that brain trauma injuries are more prevalent in patients within young age group and these injuries may be duplicated due to patients transmission and dispatching on a long and high-risk way, so some measures should be taken to provide required medical facilities and equipments and human forces for urban area hospitals, in order to reduce injuries due to brain trauma which involves mostly the young people who consist the most active potential forces of are our society.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".