Multicenter Major Trauma Transfusion Study Research Articles

Recurrent event frailty models reduced time-varying and other biases in evaluating transfusion protocols for traumatic hemorrhage

ObjectiveTransfusion research seeks to improve survival for severely injured and hemorrhaging patients using optimal plasma and platelet ratios over red blood cells (RBCs). However, most published studies comparing different ratios are plagued with serious bias and ignore time-varying effects. We applied joint recurrent event frailty models to increase validity and clinical utility. Study Design and SettingUsing the PRospective Observational Multicenter Major Trauma Transfusion study data, our joint random-effects models estimated the association of (1) clinical covariates with transfusion rate intensities and (2) varying plasma:RBC and platelet:RBC ratios with survival over the 24 hours after hospital admission. Along with survival time, baseline patient vital signs, laboratory values, and longitudinal data on types and volumes of transfusions were included. ResultsBaseline systolic blood pressure, heart rate, pH, and hemoglobin were significantly associated with RBC transfusion rates. Increased transfusion rates (per hour) of plasma (P = 0.05), platelets (P < 0.001), or RBCs were associated with increased 24-hour mortality. Higher ratios of plasma:RBC (P = 0.107) and platelet:RBC (P < 0.001) were associated with reduced mortality in a time-varying pattern (P < 0.001). ConclusionsThe proposed joint analysis of transfusion rates and ratios offers a more valid statistical approach to evaluate survival effects in the presence of informative censoring by early death.

Statistical Machines for Trauma Hospital Outcomes Research: Application to the PRospective, Observational, Multi-Center Major Trauma Transfusion (PROMMTT) Study.

Improving the treatment of trauma, a leading cause of death worldwide, is of great clinical and public health interest. This analysis introduces flexible statistical methods for estimating center-level effects on individual outcomes in the context of highly variable patient populations, such as those of the PRospective, Observational, Multi-center Major Trauma Transfusion study. Ten US level I trauma centers enrolled a total of 1,245 trauma patients who survived at least 30 minutes after admission and received at least one unit of red blood cells. Outcomes included death, multiple organ failure, substantial bleeding, and transfusion of blood products. The centers involved were classified as either large or small-volume based on the number of massive transfusion patients enrolled during the study period. We focused on estimation of parameters inspired by causal inference, specifically estimated impacts on patient outcomes related to the volume of the trauma hospital that treated them. We defined this association as the change in mean outcomes of interest that would be observed if, contrary to fact, subjects from large-volume sites were treated at small-volume sites (the effect of treatment among the treated). We estimated this parameter using three different methods, some of which use data-adaptive machine learning tools to derive the outcome models, minimizing residual confounding by reducing model misspecification. Differences between unadjusted and adjusted estimators sometimes differed dramatically, demonstrating the need to account for differences in patient characteristics in clinic comparisons. In addition, the estimators based on robust adjustment methods showed potential impacts of hospital volume. For instance, we estimated a survival benefit for patients who were treated at large-volume sites, which was not apparent in simpler, unadjusted comparisons. By removing arbitrary modeling decisions from the estimation process and concentrating on parameters that have more direct policy implications, these potentially automated approaches allow methodological standardization across similar comparativeness effectiveness studies.

A joint latent class analysis for adjusting survival bias with application to a trauma transfusion study.

There is no clear classification rule to rapidly identify trauma patients who are severely hemorrhaging and may need substantial blood transfusions. Massive transfusion (MT), defined as the transfusion of at least 10 units of red blood cells within 24h of hospital admission, has served as a conventional surrogate that has been used to develop early predictive algorithms and establish criteria for ordering an MT protocol from the blood bank. However, the conventional MT rule is a poor proxy, because it is likely to misclassify many severely hemorrhaging trauma patients as they could die before receiving the 10th red blood cells transfusion. In this article, we propose to use a latent class model to obtain a more accurate and complete metric in the presence of early death. Our new approach incorporates baseline patient information from the time of hospital admission, by combining respective models for survival time and usage of blood products transfused within the framework of latent class analysis. To account for statistical challenges, caused by induced dependent censoring inherent in 24-h sums of transfusions, we propose to estimate an improved standard via a pseudo-likelihood function using an expectation-maximization algorithm with the inverse weighting principle. We evaluated the performance of our new standard in simulation studies and compared with the conventional MT definition using actual patient data from the Prospective Observational Multicenter Major Trauma Transfusion study. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating the ratio of multivariate recurrent event rates with application to a blood transfusion study.

In comparative effectiveness studies of multicomponent, sequential interventions like blood product transfusion (plasma, platelets, red blood cells) for trauma and critical care patients, the timing and dynamics of treatment relative to the fragility of a patient's condition is often overlooked and underappreciated. While many hospitals have established massive transfusion protocols to ensure that physiologically optimal combinations of blood products are rapidly available, the period of time required to achieve a specified massive transfusion standard (e.g. a 1:1 or 1:2 ratio of plasma or platelets:red blood cells) has been ignored. To account for the time-varying characteristics of transfusions, we use semiparametric rate models for multivariate recurrent events to estimate blood product ratios. We use latent variables to account for multiple sources of informative censoring (early surgical or endovascular hemorrhage control procedures or death). The major advantage is that the distributions of latent variables and the dependence structure between the multivariate recurrent events and informative censoring need not be specified. Thus, our approach is robust to complex model assumptions. We establish asymptotic properties and evaluate finite sample performance through simulations, and apply the method to data from the PRospective Observational Multicenter Major Trauma Transfusion study.

An abdominal computed tomography may be safe in selected hypotensive trauma patients with positive Focused Assessment with Sonography in Trauma examination

BackgroundPositive Focused Assessment with Sonography in Trauma examination and hypotension often indicate urgent surgery. An abdomen/pelvis computed tomography (apCT) may allow less invasive management but the delay may be associated with adverse outcomes. MethodsPatients in the Prospective Observational Multicenter Major Trauma Transfusion study with hypotension and a positive Focused Assessment with Sonography in Trauma (HF+) examination who underwent a CT (apCT+) were compared with those who did not. ResultsOf the 92 HF+ identified, 32 (35%) underwent apCT during initial evaluation and apCT was associated with decreased odds of an emergency operation (odds ratio .11, 95% confidence interval .001 to .116) and increased odds of angiographic intervention (odds ratio 14.3, 95% confidence interval 1.5 to 135). There was no significant difference in 30-day mortality or need for dialysis. ConclusionsAn apCT in HF+ patients is associated with reduced odds of emergency surgery, but not mortality. Select HF+ patients can safely undergo apCT to obtain clinically useful information.