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Point-of-Care Urinary Biomarker Testing for Risk Prediction in Critically Injured Combat Casualties
Carl A Beyer1, David M Burmeister2, Belinda I Gómez2
1Clinical Investigation Facility, David Grant US Air Force Medical Center, Travis Air Force Base, CA; Department of Surgery, University of California Davis Medical Center, Sacramento, CA.
Background:
Risk prediction is important during combat operations because resources are limited and triage decisions must be rapid and accurate. We evaluated 2 point-of-care urinary biomarker tests for risk prediction in combat casualties.
Study Design:
This was an observational cohort study of critically injured military personnel admitted to Craig Joint Theater Hospital in Afghanistan from October 2012 to December 2013. We collected urine within 3 hours of admission and measured urinary biomarkers with NephroCheck and a neutrophil gelatinase-associated lipocalin dipstick (NGALds) to evaluate their ability to predict a combined end point of need for renal replacement therapy or death. Odds ratios (ORs) were calculated and receiver operator characteristic curves were generated for both tests.
Results:
A total of 89 patients were included for analysis. The median Injury Severity Score was 18 and the combined end point occurred in 12 (13.5%) patients. NephroCheck was not associated with the combined end point (OR 1.56; 95% CI 0.81 to 3.03; p = 0.19) and the area under the curve of the receiver operator characteristic curve was 0.65. The NGALds was highly associated with the combined end point (OR 4.93; 95% CI 2.18 to 11.14; p < 0.001) and the area under the curve of the receiver operator characteristic curve was 0.84. The NGALds remained significantly associated with the combined end point in a logistic regression model that included Injury Severity Score as a covariate (OR 4.10; 95% CI 1.74 to 9.67; p = 0.001).
Conclusions:
Measurement of urinary biomarkers with an NGALds, but not NephroCheck, predicts poor outcomes in combat casualties. An NGALds is a simple urine dipstick that could be deployed to combat zones to prioritize aeromedical evacuation, help with triage decisions, and predict resource use.
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