Novel prehospital monitor with injury acuity alarm to identify trauma patients who require lifesaving intervention

Abstract

Background: A miniature wireless vital signs monitor (MWVSM, www.athena.gtx.com) has been designed according to US Special Operations Command specifications for field monitoring of combat casualties. It incorporates an injury acuity algorithm termed the Murphy Factor (MF), which is calculated from whatever vital signs are available at the moment and changes in the last 30 seconds. We tested the hypothesis that MF can identify civilian trauma patients during prehospital transport who will require a lifesaving intervention (LSI) upon hospital admission.

Methods: From December 2011 to June 2013, a prospective trial was conducted in collaboration with prehospital providers. The MWVSM detects skin temperature, pulse oximetry (SpO2), heart rate (HR), pulse wave transit time, and MF. LSIs included: intubation, tube thoracostomy, central line insertion, blood product transfusion, and operative intervention. Prehospital MWVSM data were compared with simultaneous vital signs (SaO2, systolic blood pressure (SBP), and HR) from a conventional vital signs monitor. Sensitivity, specificity, negative predictive value, positive predictive value, and area under the receiving operating characteristic curves were calculated.

Results: Ninety-six trauma patients experienced predominantly blunt trauma (n = 80, 84%), were mostly male (n = 79, 82%), and had a mean ± SD age of 48 ± 19 years and an Injury Severity Score (ISS) of 10 (17). Those who received an LSI (n = 48) had similar demographics but higher ISS (18 vs. 5) and mortality (23% vs. 0%) (all p < 0.05). The most common LSIs were intubation (n = 24, 25%), blood product transfusion (n = 19, 20%), and emergency surgery (n = 19, 20%). Compared with HR > 100 beats/min, SBP < 90 mm Hg, SaO2 < 95% alone or in combination, MF > 3 during the entire transport time had the largest area under the receiving operating characteristic curves (0.620, p = 0.081). MF greater than 3 had a specificity of 81%, sensitivity of 39%, positive predictive value of 68%, and negative predictive value of 57% for the need for LSI.

Conclusion: A single numeric value has the potential to summarize overall patient status and identify prehospital trauma patients who need an LSI. Prehospital monitoring combined with algorithms that include trends over time could improve prehospital care for both civilian and military trauma.

Level of evidence: Prospective observational, level II.