Vital signs (VS) data collected in prehospital care and recorded in trauma registries are often missing or unreliable as it is difficult to record dynamic changes while performing resuscitation and stabilization. The purpose of this study was to test the hypothesis that analysis of continuous vital signs improves data quality, and predicts life-saving interventions (LSI) better than use of retrospectively compiled Trauma Registry (TR) data.
After Institutional Review Board approval, six emergency medical services helicopters were equipped with a Vital Signs Data Recorder (VSDR) to capture continuous VS from the patient onto a handheld personal digital assistant (PDA). Prehospital LSIs (fluid bolus, cardiopul-monary resuscitation, drugs, intubation, etc.) and those performed within two hours after arrival in the trauma resuscitation unit were considered outcome variables. The VSDR and TR data were compared using Bland-Altman method. A multivariate analysis was performed to determine which VS variable best predicted LSIs using the values in the TR and the VSDR.
Prehospital VSDR data were collected from 177 patients. There was a significant difference between the highest and lowest heart rate, systolic blood pressure (SBP), and oxygen saturation between the VSDR and the TR data (p <0.001).The VSDR highest heart rate and lowest oxygen saturation recorded predicted LSIs while none of the TR vital signs did so in a multivariate model. The SBP was not an independent predictor of LSI.
The VSDR data increased the odds of predicting LSIs compared to the TR data. Using continuous vital signs in prehospital care may lead to the development of better trauma prognostic models.