Construction and verification of a simple scoring system for severity of injuries

Background Accurate assessment and classification for the severity of injuries is a prerequisite and foundation for implementing timely and scientific treatment.

Objective To provide some monitoring indicators and measurement methods for the severity of injuries for uses in battlefield and on-site first aid.

Methods A total of 44 642 cases with trauma injuries were collected from 8 medical centers affiliated to Chinese PLA General Hospital from 2014 to 2018, and multiple logistic regression analysis was used to construct an injury severity scoring model, including 10 indicators: age, admission condition, temperature, pulse, breathing, systolic blood pressure, number of comorbidities, injury sites, injury types, and injury causes. The Liu method, Youden index method, and nearest (0, 1) method were used to determine the cut-off scores of trauma severity.

Results The severity score of injury was the sum of the risk scores of each variable, ranging from -15 to 98 points, and the verification of discrimination and calibration degree of the model was good. The cut-off score for grading injuries into mild and severe was 32, with <32 classified as mild and ≥32 as severe.

Conclusion The injury severity score can be used for assessment of the severity and prediction of casualty outcomes in battlefield and on-site environments, which can be used as a reference for resource allocation.