With the increasing availability of vehicle telemetry technology, there is great potential for Advanced Automatic Collision Notification (AACN) systems to improve trauma outcomes by detecting patients at-risk for severe injury and facilitating early transport to trauma centers.

National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data from 1999-2013 were used to construct a logistic regression model (injury severity prediction [ISP] model) predicting the probability that one or more occupants in planar, non-rollover motor vehicle collisions (MVCs) would have Injury Severity Score (ISS) 15+ injuries. Variables included principal direction of force (PDOF), change in velocity (Delta-V), multiple impacts, presence of any older occupant (≥55 years old), presence of any female occupant, presence of right-sided passenger, belt use, and vehicle type. The model was validated using medical records and 2008-2011 crash data from AACN-enabled Michigan (USA) vehicles identified from OnStar (OnStar Corporation; General Motors; Detroit, Michigan USA) records. To compare the ISP to previously established protocols, a literature search was performed to determine the sensitivity and specificity of first responder identification of ISS 15+ for MVC occupants.

The study population included 924 occupants in 836 crash events. The ISP model had a sensitivity of 72.7% (95% Confidence Interval [CI] 41%-91%) and specificity of 93% (95% CI 92%-95%) for identifying ISS 15+ occupants injured in planar MVCs. The current standard 2006 Field Triage Decision Scheme (FTDS) was 56%-66% sensitive and 75%-88% specific in identifying ISS 15+ patients.

The ISP algorithm comparably is more sensitive and more specific than current field triage in identifying MVC patients at-risk for ISS 15+ injuries. This real-world field study shows telemetry data transmitted before dispatch of emergency medical systems can be helpful to quickly identify patients who require urgent transfer to trauma centers.

Prehospital ultrasound (PHUS) assessments by physicians and non-physicians are performed on medical and trauma patients with increasing frequency. Prehospital ultrasound has been shown to be of benefit by supporting interventions.

Which patients may benefit from PHUS has not been clearly identified.

A multi-variable logistic regression analysis was performed on a previously created retrospective dataset of five years of physician- and non-physician-performed ultrasound scans in a Canadian critical care Helicopter Emergency Medical Service (HEMS). For separate medical and trauma patient groups, the a-priori outcome assessed was patient characteristics associated with the outcome variable of “PHUS-supported intervention.”

Both models were assessed (Likelihood Ratio, Score, and Wald) as a good fit. For medical patients, the characteristics of heart rate (HR) and shock index (SI) were found to be most significant for an intervention being supported by PHUS. An extremely low HR was found to be the most significant (OR=15.86 [95% confidence interval (CI), 1.46-171.73]; P=.02). The higher the SI, the more likely that an intervention was supported by PHUS (SI 0.9 to<1.3: OR=9.15 [95% CI, 1.36-61.69]; P=.02; and SI 1.3+: OR=8.37 [95% CI, 0.69-101.66]; P=.09). For trauma patients, the characteristics of Prehospital Index (PHI) and SI were found to be most significant for PHUS support. The greatest effect was PHI, where increasing ORs were seen with increasing PHI (PHI 14-19: OR=13.36 [95% CI, 1.92-92.81]; P=.008; and PHI 20-24: OR=53.10 [95% CI, 4.83-583.86]; P=.001). Shock index was found to be similar, though, with lower impact and significance (SI 0.9 to<1.3: OR=9.11 [95% CI, 1.31-63.32]; P=.025; and SI 1.3+: OR=35.75 [95% CI, 2.51-509.81]; P=.008).

In a critical care HEMS, markers of higher patient acuity in both medical and trauma patients were associated with occurrences when an intervention was supported by PHUS. Prospective study with in-hospital follow-up is required to confirm these hypothesis-generating results.

O’DochartaighD, DoumaM, AlexiuC, RyanS, MacKenzieM. Utilization Criteria for Prehospital Ultrasound in a Canadian Critical Care Helicopter Emergency Medical Service: Determining Who Might Benefit. Prehosp Disaster Med. 2017;32(5):536–540.

To determine the sensitivity of the Prehospital Index (PHI) in identifying patients with severe blood loss, a one-year review was conducted at a regional trauma facility.

The study population consisted of 217 consecutive trauma admissions (ages 3 to 88 years). Patients were managed using standard resuscitation techniques; blood transfusions were ordered at the discretion of attending physicians and did not follow any preplanned protocol. Medical records were examined to determine total blood requiremets for each patient during the first 12 hours of hospitalization, the emergency department (ED) disposition, and final outcome of treatment. The following clinical variables were analyzed (unpaired t-test) to determine their value as predictors of blood loss: age, gender, mechanism of injury, initial vital signs, revised trauma score, PHI, and injury severityscore.

Forty-two percent (92 patients) received transfusions during the first 12 hours of hospitalization. The best predictor of blood loss was the Prehospital Index. Of the total group, 45% had a PHI >3; 77% (75/98) of these patients required transfusion and received an average of 7.1 units of packed cells. Fifty-five percent (119/217) had a PHI ≤3; 86% (102/119) of these patients did not require transfusion.

The data suggest that patients with PHI scores >3 require close hemodynamic monitoring to rule out significant blood loss and may warrant immediate cross-matching on arrival to the ED.