Evolving beyond the vicious triad: Differential mediation of traumatic coagulopathy by injury, shock, and resuscitation.

BACKGROUND: A subset of trauma patients with critical injury present with coagulopathy, portending markedly worse outcomes. Clinical practice is evolving to treat the classical risk factors of hypothermia, hemodilution, and acidosis; however, coagulopathy persists even in the absence of these factors. We sought to determine the relative importance of injury- and shock-specific factors compared with resuscitation-associated factors in coagulopathy after trauma. METHODS: Comprehensive demographic data, laboratory data, and outcomes data were prospectively collected from seven trauma centers over 8 years (November 2003 to August 2011) as part of the Inflammation and the Host Response to Injury Large-Scale Collaborative Program. A total of 1,537 critically injured patients with blunt trauma and hemorrhagic shock were analyzed to evaluate predictors of admission coagulopathy (international normalized ratio [INR] ≥ 1.3), multiorgan failure, and mortality. RESULTS: Of 1,537 patients, 578 (37.6%) had admission INR of 1.3 or greater. Coagulopathic patients had more severe injury, more severe base deficit and lactate levels, as well as lower admission temperature, lower pH, and higher prehospital crystalloid volume (all p < 0.001). Coagulopathic patients required more blood products and mechanical ventilation and had higher rates of nosocomial infection, multiorgan failure, and mortality (all p < 0.02). Injury severity, temperature, and acidosis (all p < 0.02) independently predicted coagulopathy in multivariate analysis, with a significant interaction between lactate and prehospital crystalloid. In Cox regression models, however, coagulopathy itself remained an independent predictor of both multiorgan failure and mortality (p < 0.02) even when adjusted for injury severity, shock, and elements of the vicious triad. CONCLUSION: Most patients with coagulopathy after trauma have mixed risk factors; however, coagulopathy has deleterious effects independent of injury severity, shock, and the vicious triad. Better understanding of the biochemical mechanisms of acute traumatic coagulopathy may facilitate biochemically targeted resuscitation strategies and improve outcomes. LEVEL OF EVIDENCE: Prognostic and epidemiologic study, level II.

Semiparametric Estimation of the Impacts of Longitudinal Interventions on Adolescent Obesity using Targeted Maximum-Likelihood: Accessible Estimation with the ltmle Package.

While child and adolescent obesity is a serious public health concern, few studies have utilized parameters based on the causal inference literature to examine the potential impacts of early intervention. The purpose of this analysis was to estimate the causal effects of early interventions to improve physical activity and diet during adolescence on body mass index (BMI), a measure of adiposity, using improved techniques. The most widespread statistical method in studies of child and adolescent obesity is multi-variable regression, with the parameter of interest being the coefficient on the variable of interest. This approach does not appropriately adjust for time-dependent confounding, and the modeling assumptions may not always be met. An alternative parameter to estimate is one motivated by the causal inference literature, which can be interpreted as the mean change in the outcome under interventions to set the exposure of interest. The underlying data-generating distribution, upon which the estimator is based, can be estimated via a parametric or semi-parametric approach. Using data from the National Heart, Lung, and Blood Institute Growth and Health Study, a 10-year prospective cohort study of adolescent girls, we estimated the longitudinal impact of physical activity and diet interventions on 10-year BMI z-scores via a parameter motivated by the causal inference literature, using both parametric and semi-parametric estimation approaches. The parameters of interest were estimated with a recently released R package, ltmle, for estimating means based upon general longitudinal treatment regimes. We found that early, sustained intervention on total calories had a greater impact than a physical activity intervention or non-sustained interventions. Multivariable linear regression yielded inflated effect estimates compared to estimates based on targeted maximum-likelihood estimation and data-adaptive super learning. Our analysis demonstrates that sophisticated, optimal semiparametric estimation of longitudinal treatment-specific means via ltmle provides an incredibly powerful, yet easy-to-use tool, removing impediments for putting theory into practice.