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.
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.
Study Type
OBSERVATIONAL
Enrollment
1,250
Training set for model development
Independent test set for validation
University of Health Sciences, Antalya Training and Research Hospital
Antalya, Turkey (Türkiye)
RECRUITINGIn-hospital mortality
Time frame: 30 days after ICU admission
Develop and validate the model
Time frame: 30 days after ICU admission
Assess the model's discriminatory performance, calibration and classification accuracy
Time frame: 30 days after ICU admission
Classify patients into clinically meaningful risk categories
Time frame: 30 days after ICU admission
Assess the independent contribution of helmet use and chest injury patterns to mortality prediction
Time frame: 30 days after ICU admission
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