Department of Defense Trauma Registry Infectious Disease Module Impact on Clinical Practice.

BACKGROUND: The Joint Trauma System (JTS) is a DoD Center of Excellence for Military Health System trauma care delivery and the DoD's reference body for trauma care in accordance with National Defense Authorization Act for Fiscal Year 2017. Through the JTS, evidence-based clinical practice guidelines (CPGs) have been developed and subsequently refined to standardize and improve combat casualty care. Data are amassed through a single, centralized DoD Trauma Registry to support process improvement measures with specialty modules established as the registry evolved. Herein, we review the implementation of the JTS DoD Trauma Registry specialty Infectious Disease Module and the development of infection-related CPGs and summarize published findings on the subsequent impact of the Infectious Disease Module on combat casualty care clinical practice and guidelines. METHODS: The DoD Trauma Registry Infectious Disease Module was developed in collaboration with the Infectious Disease Clinical Research Program (IDCRP) Trauma Infectious Disease Outcomes Study (TIDOS). Infection-related information (e.g., syndromes, antibiotic management, and microbiology) were collected from military personnel wounded during deployment June 1, 2009 through December 31, 2014 and medevac'd to Landstuhl Regional Medical Center in Germany before transitioning to participating military hospitals in the USA. RESULTS: To support process improvements and reduce variation in practice patterns, data collected through the Infectious Disease Module have been utilized in TIDOS analyses focused on assessing compliance with post-trauma antibiotic prophylaxis recommendations detailed in JTS CPGs. Analyses examined compliance over three time periods: 6 months, one-year, and 5 years. The five-year analysis demonstrated significantly improved adherence to recommendations following the dissemination of the 2011 JTS CPG, particularly with open fractures (34% compliance compared to 73% in 2013-2014). Due to conflicting recommendations regarding use of expanded Gram-negative coverage with open fractures, infectious outcomes among patients with open fractures who received cefazolin or expanded Gram-negative coverage (cefazolin plus fluoroquinolones and/or aminoglycosides) were also examined in a TIDOS analysis. The lack of a difference in the proportion of osteomyelitis (8% in both groups) and the significantly greater recovery of Gram-negative organisms resistant to aminoglycosides or fluoroquinolones among patients who received expanded Gram-negative coverage supported JTS recommendations regarding the use of cefazolin with open fractures. Following recognition of the outbreak of invasive fungal wound infections (IFIs) among blast casualties injured in Afghanistan, the ID Module was refined to capture data (e.g., fungal culture and histopathology findings, wound necrosis, and antifungal management) needed for the TIDOS team to lead the DoD outbreak investigation. These data captured through the Infectious Disease Module provided support for the development of a JTS CPG for the prevention and management of IFIs, which was later refined based on subsequent TIDOS IFI analyses. CONCLUSIONS: To improve combat casualty care outcomes and mitigate high-consequence infections in future conflicts, particularly in the event of prolonged field care, expansion, refinement, and a mechanism for sustainability of the DoD Trauma Registry Infectious Disease Module is needed to include real-time surveillance of infectious disease trends and outcomes.

Population Dynamics of Evolutionary Change: Demographic Parameters as Indicators of Fitness

I evaluated demographic parameters as indicators of fitness by calculating the net reproductive rate (R0), exponential rate of change (r), lifetime reproductive success (LRS), and Malthusian parameter (m) for nine genotypes and four phenotypes (two alleles at each of two independent loci) of an age-structured population. The given starting conditions included age-specific survival rates of males and females and age-specific fecundity of females for each genotype (to simplify the problem I presumed no differences in survivorship or fecundity of genotypes with the same phenotype) and the same age structure for each genotype. The prevailing genotype had the greatest m, but it did not have the greatest r, R0 , or LRS, or even the greatest survivorship of either juveniles or adults, or the greatest fecundity. This result indicates that m is the only correct measure of fitness (i.e., as a predictor of which genotype should prevail from among a group of genotypes) and that comparisons of r, R0 , LRS, juvenile or adult survival rates, or fecundity may be misleading indicators of which genotype should prevail (i.e., be most "fit") over time (i.e., be selected for).