Michael D April1, Tyson E Becker2, Andrew D Fisher3, Jason F Naylor4, Steven G Schauer5. 1. 2nd Stryker Brigade Combat Team, 4th Infantry Division, Fort Carson, CO, USA; Uniformed Services University of the Health Sciences, Bethesda, MD, USA. Electronic address: michael.d.april@post.harvard.edu. 2. Uniformed Services University of the Health Sciences, Bethesda, MD, USA; Brooke Army Medical Center, JBSA Fort Sam Houston, TX, USA. 3. Texas Medical Command, Texas Army National Guard, Austin, TX, USA; Texas A&M College of Medicine, Temple, TX, USA; Prehospital Research in Military and Expeditionary Environments, San Antonio, TX, USA. 4. Madigan Army Medical Center, JBLM Fort Lewis, Washington, USA. 5. Uniformed Services University of the Health Sciences, Bethesda, MD, USA; Brooke Army Medical Center, JBSA Fort Sam Houston, TX, USA; US Army Institute of Surgical Research, JBSA Fort Sam Houston, TX, USA; 59(th) Medical Wing, JBSA Lackland, TX, USA.
Abstract
INTRODUCTION: Identifying patients at imminent risk of death is a paramount priority in combat casualty care. This study measures the vital sign values predictive of mortality among combat casualties in Iraq and Afghanistan. METHODS: We used data from the Department of Defense Trauma Registry from January 2007 to August 2016. We used the highest documented heart rate and the lowest documented systolic pressure in the emergency department for each casualty. We constructed receiver operator curves (ROCs) to assess the accuracy of these variables for predicting survival to hospital discharge. RESULTS: There were 38,769 encounters of which our dataset included 15,540 (40.1%). The median age of these patients was 25 years and 97.5% were male. The most common mechanisms of injury were explosives (n = 9481, 61.0%) followed by gunshot wounds (n = 2393, 15.3%). The survival rate to hospital discharge was 97.5%. The median heart rate was 94 beats per minute (bpm) with area under the ROC of 0.631 with an optimal threshold to predict mortality of 110 bpm (sensitivity 52.2%, specificity 79.2%). The median systolic blood pressure was 128 mmHg with area under the ROC of 0.790 with an optimal threshold to predict mortality of 112 mmHg (sensitivity 68.5%, specificity 81.5%). CONCLUSIONS: Casualties with a systolic blood pressure <112 mmHg, are at high risk of mortality, a value significantly higher than the traditional 90 mmHg threshold. Our dataset highlights the need for better methods to guide resuscitation as vital sign measurements have limited accuracy in predicting mortality. Published by Elsevier Inc.
INTRODUCTION: Identifying patients at imminent risk of death is a paramount priority in combat casualty care. This study measures the vital sign values predictive of mortality among combat casualties in Iraq and Afghanistan. METHODS: We used data from the Department of Defense Trauma Registry from January 2007 to August 2016. We used the highest documented heart rate and the lowest documented systolic pressure in the emergency department for each casualty. We constructed receiver operator curves (ROCs) to assess the accuracy of these variables for predicting survival to hospital discharge. RESULTS: There were 38,769 encounters of which our dataset included 15,540 (40.1%). The median age of these patients was 25 years and 97.5% were male. The most common mechanisms of injury were explosives (n = 9481, 61.0%) followed by gunshot wounds (n = 2393, 15.3%). The survival rate to hospital discharge was 97.5%. The median heart rate was 94 beats per minute (bpm) with area under the ROC of 0.631 with an optimal threshold to predict mortality of 110 bpm (sensitivity 52.2%, specificity 79.2%). The median systolic blood pressure was 128 mmHg with area under the ROC of 0.790 with an optimal threshold to predict mortality of 112 mmHg (sensitivity 68.5%, specificity 81.5%). CONCLUSIONS: Casualties with a systolic blood pressure <112 mmHg, are at high risk of mortality, a value significantly higher than the traditional 90 mmHg threshold. Our dataset highlights the need for better methods to guide resuscitation as vital sign measurements have limited accuracy in predicting mortality. Published by Elsevier Inc.
Authors: Victor A Convertino; Steven G Schauer; Erik K Weitzel; Sylvain Cardin; Mark E Stackle; Michael J Talley; Michael N Sawka; Omer T Inan Journal: Sensors (Basel) Date: 2020-11-10 Impact factor: 3.576