Abstract
Identifying patients in need of a life-saving intervention (LSI) during a mass casualty event is a priority. We hypothesized that real-time, instantaneous sample entropy (SampEn) could predict the need for LSI in the Boston Marathon bombing victims.
Severely injured Boston Marathon bombing victims (n = 10) had sample entropy (SampEn) recorded upon presentation using a continuous 200-beat rolling average in real time. Treating clinicians were blinded to real-time results. The correlation between SampEn, injury severity, number, and type of LSI was examined.
Victims were males (60%) with a mean age of 39.1 years. Injuries involved lower extremities (50.0%), head and neck (24.2%), or upper extremities (9.7%). Sample entropy negatively correlated with Injury Severity Score (r = −0.70; P = .023), number of injuries (r = −0.70; P = .026), and the number and need for LSI (r = −0.82; P = .004). Sample entropy was reduced under a variety of conditions.SampEn (mean ± SD)PAmputation, n = 50.7 ± 0.3No amputation, n = 51.9 ± 0.8.027Transfusion, n = 50.7 ± 0.3No transfusion, n = 51.9 ± 0.8.027Intubation, n = 60.8 ± 0.3No intubation, n = 42.1 ± 0.7.027Vasopressors, n = 70.8 ± 0.3No vasopressors, n = 32.4 ± 0.3.004
Sample entropy strongly correlates with injury severity and predicts LSI after blast injuries sustained in the Boston Marathon bombings. Sample entropy may be a useful triage tool after blast injury.
