Novel score for predicting early emergency endovascular therapy in trauma care using logistic LASSO regression.

ABSTRACT

Aim: To support decision-making for early interventional radiology, this study aimed to derive and validate a novel and simple scoring system for predicting the necessity of interventional radiology therapies in trauma patients. Methods: This retrospective study used data derived from the medical records of patients with severe traumatic injuries treated at a tertiary-level emergency institution. The score was derived from 168 patients treated between April 2015 and October 2016 and validated using data from 68 patients treated between November 2016 and July 2017. Logistic "least absolute shrinkage and selection operator (LASSO)" regression was used to select predictors. In order to compose the score, odds ratios derived from the logistic model were simplified to integer score coefficients. The score was evaluated using the area under the receiver operating characteristic curve. The best cut-off point for the score was determined using Youden's index, and sensitivity and specificity were calculated. Results: The derived score comprised three predictors (systolic blood pressure, positive findings in abdominal ultrasound assessment, and pelvic fracture) and ranged from 0 to 30. On validation, the area under the receiver operating characteristic curve for the score was 0.86 (95% confidence interval, 0.64-1.00). The sensitivity and specificity were 80% and 89%, respectively, with a cut-off point of 3. Conclusion: This simple score, requiring variables obtainable immediately after hospital arrival, could aid in facilitating early interventional radiology team activation.