Do Trauma Severity Scores Successfully Predict Hypersusceptibility to Infections in Trauma Patients?
*Marianna Almpani1, *Amy Tsurumi1, *Thomas Peponis2, *Yashoda V. Dhole2, *Laura F. Goodfield2, Ronald G. Tompkins2, *Laurence G. Rahme1
1Massachusetts General Hospital/Harvard Medical School/Shriners Hospital for Children, Boston, Boston, MA; 2Massachusetts General Hospital/Harvard Medical School, Boston, MA
Objective: Determine whether commonly employed injury severity scores can successfully predict hypersusceptibility to multiple independent infection episodes (MIIEs) in trauma patients.
Design: Secondary retrospective analysis of data from the “Infection and the host response to injury” ("Glue Grant") prospective longitudinal cohort study. Multivariate logistic regression was performed to measure the odds ratio of five commonly employed trauma severity scores [Denver, Marshall, Acute Physiology and Chronic Health Evaluation II (APACHE II), Injury Severity Score (ISS) and New Injury Severity Score (NISS)] in predicting hypersusceptibility to MIIEs. The latter was defined as 2 or more independent infection episodes during the recovery period.
Setting: Four Level 1 trauma centers in the United States.
Patients: 1665 trauma patients older than 16 years.
Main Outcome Measures: The correlation between trauma severity scores and hypersusceptibility to MIIEs.
Results: 20.8% of the population was found to be hypersusceptible to MIIEs. Denver and Marshall scores were highly predictive of the MIIE status. For every unit increase of either the Denver or the Marshall score, there was a 15% increase in the odds of MIIEs occurrence. APACHE II, ISS and NISS were not independent predictors of MIIEs.
Conclusions: Denver and Marshall scores can reliably predict which trauma patients are prone to multiple independent infections during their hospital stay, before any signs of infection become apparent. Early identification of such individuals would potentially allow rapid, personalized, preventative measures, thus improving patient outcomes and reducing healthcare costs.