Helmet Use, Mortality, Motorsycle, Severity Score, Trauma Centers, Trauma (Including Fractures)
Conditions
Keywords
motorsycle, thorax, trauma, severity score, mortality
Brief summary
This study aimed to test the hypothesis that a practical, bedside-applicable tool could be developed to help identify patients at high risk of mortality following motorcycle accidents more quickly and facilitate treatment by enabling faster clinical decision-making.
Detailed description
Injuries resulting from motorcycle accidents are one of the leading causes of death worldwide, and rates are increasing. This increase is attributed to the disproportionate vulnerability of riders at the moment of impact, inadequate protective barriers during collisions, motorcycles' ability to reach high speeds and biomechanical exposure. The thoracic cage is the anatomical region most commonly affected in motorcycle accident-related injuries. This study aimed to test the hypothesis that a practical, bedside-applicable tool could be developed to help identify patients at high risk of mortality following motorcycle accidents more quickly and facilitate treatment by enabling faster clinical decision-making.
Interventions
OTHERTraining set
Training set for model development
OTHERTest set
Independent test set for validation
Sponsors
Antalya Health Sciences University
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* patients aged 18 years or over * motorcycle accident (a rider or a passenger) * radiologically or clinically confirmed chest injury * fully documented in the medical records.
Exclusion criteria
* penetrating chest trauma * patients under the age of 18 * isolated non-chest trauma * incomplete documentation
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| In-hospital mortality | 30 days after ICU admission |
Secondary
| Measure | Time frame |
|---|---|
| Develop and validate the model | 30 days after ICU admission |
| Assess the model's discriminatory performance, calibration and classification accuracy | 30 days after ICU admission |
| Classify patients into clinically meaningful risk categories | 30 days after ICU admission |
| Assess the independent contribution of helmet use and chest injury patterns to mortality prediction | 30 days after ICU admission |
Countries
Turkey (Türkiye)
Contacts
PRINCIPAL_INVESTIGATORNilay Cavusoglu Yalcın
University of Health Sciences, Antalya Training and Research Hospital
Outcome results
None listed