Steven S. Henley

Early blood product and crystalloid volume resuscitation: Risk association with multiple organ dysfunction after severe blunt traumatic injury

BACKGROUND Elements of volume resuscitation from hemorrhagic shock, such as amount of blood product and crystalloid administration, have been shown to be associated with multiple organ dysfunction (MOD). However, it is unknown whether these are causative factors or merely markers of an underlying requirement for large-volume resuscitation. We sought to further delineate the relevance of the major individual components of early volume resuscitation to onset of MOD after severe blunt traumatic injury. METHODS We performed a secondary analysis of a large, multicenter prospective observational cohort of severely injured blunt trauma patients, the NIGMS Trauma Glue Grant, to assess the relevance of individual components of resuscitation administered in the first 12 hours of resuscitation including packed red blood cells (PRBC), fresh frozen plasma (FFP), and isotonic crystalloid, to the onset of MOD within the first 28 days after injury. Deaths within 48 hours of injury were excluded. We used a two tiered, exhaustive logistic regression model search technique to adjust for potential confounders from clinically relevant MOD covariates, including indicators of shock severity, injury severity, comorbidities, age, and gender. RESULTS The study cohort consisted of 1,366 severely injured blunt trauma patients (median new Injury Severity Score = 34). Incidence of 28-day Marshall MOD was 19.6%. Transfusion of ≥10 Units of PRBC in the first 12 hours (odds ratio, 2.06; 95% confidence interval 1.44-2.94), but not FFP (≥8 U) or large volume crystalloid administration (≥12 L), was independently associated with onset of 28-day Marshall MOD. PRBC:FFP ratio in the first 12 hours was not significantly associated with MOD. CONCLUSIONS When controlling for all major components of acute volume resuscitation, massive-transfusion volumes of PRBCs within the first 12 hours of resuscitation are modestly associated with MOD, whereas FFP and large volume crystalloid administration are not independently associated with MOD. Previous reported associations of blood products and large-volume crystalloid with MOD may be reflecting overall resuscitation requirements and burden of injury rather than independent causation.

Comparing clinical predictors of deep venous thrombosis versus pulmonary embolus after severe injury: A new paradigm for posttraumatic venous thromboembolism?

BACKGROUND: The traditional paradigm is that deep venous thrombosis (DVT) and pulmonary embolus (PE) are different temporal phases of a single disease process, most often labeled as the composite end point venous thromboembolism (VTE). However, we theorize that after severe blunt injury, DVT and PE may represent independent thrombotic entities rather than different stages of a single pathophysiologic process and therefore exhibit different clinical risk factor profiles. METHODS: We examined a large, multicenter prospective cohort of severely injured blunt trauma patients to compare clinical risk factors for DVT and PE, including indicators of injury severity, shock, resuscitation parameters, comorbidities, and VTE prophylaxis. Independent risk factors for each outcome were determined by cross‐validated logistic regression modeling using advanced exhaustive model search procedures. RESULTS: The study cohort consisted of 1,822 severely injured blunt trauma patients (median Injury Severity Score [ISS], 33; median base deficit, ‐9.5). Incidence of DVT and PE were 5.1% and 3.9%, respectively. Only 9 (5.7%) of 73 patients with a PE were also diagnosed with DVT. Independent risk factors associated with DVT include prophylaxis initiation within 48 hours (odds ratio [OR], 0.57; 95% confidence interval [CI], 0.36–0.90) and thoracic Abbreviated Injury Scale (AIS) score of 3 or greater (OR, 1.82; 95% CI, 1.12–2.95), while independent risk factors for PE were serum lactate of greater than 5 (OR, 2.33; 95% CI, 1.43–3.79) and male sex (OR, 2.12; 95% CI, 1.17–3.84). Both DVT and PE exhibited differing risk factor profiles from the classic composite end point of VTE. CONCLUSION: DVT and PE exhibit differing risk factor profiles following severe injury. Clinical risk factors for diagnosis of DVT after severe blunt trauma include the inability to initiate prompt pharmacologic prophylaxis and severe thoracic injury, which may represent overall injury burden. In contrast, risk factors for PE are male sex and physiologic evidence of severe shock. We hypothesize that postinjury DVT and PE may represent a broad spectrum of pathologic thrombotic processes as opposed to the current conventional wisdom of peripheral thrombosis and subsequent embolus. LEVEL OF EVIDENCE: Prognostic study, level III.

New Directions in Information Matrix Testing: Eigenspectrum Tests

Model specification tests are essential tools for evaluating the appropriateness of probability models for estimation and inference. White (Econometrica, 50: 1–25, 1982) proposed that model misspecification could be detected by testing the null hypothesis that the Fisher information matrix (IM) Equality holds by comparing linear functions of the Hessian to outer product gradient (OPG) inverse covariance matrix estimators. Unfortunately, a number of researchers have reported difficulties in obtaining reliable inferences using White’s (Econometrica, 50: 1–25, 1982) original information matrix test (IMT). In this chapter, we extend White (Econometrica, 50: 1–25, 1982) to present a new generalized information matrix test (GIMT) theory and develop a new Adjusted Classical GIMT and five new Eigenspectrum GIMTs that compare nonlinear functions of the Hessian and OPG covariance matrix estimators. We then evaluate the level and power of these new GIMTs using simulation studies on realistic epidemiological data and find that they exhibit appealing performance on sample sizes typically encountered in practice. Our results suggest that these new GIMTs are important tools for detecting and assessing model misspecification, and thus will have broad applications for model-based decision making in the social, behavioral, engineering, financial, medical, and public health sciences.

Measuring use and cost of care for patients with mood disorders: the utilization and cost inventory.

Background:Researchers conducting cost-outcome studies must account for all materially relevant care that subjects receive from their care providers. However, access to provider records is often limited. This article describes and tests the Utilization and Cost Inventory (UAC-I), a structured patient interview designed to measure costs of care when access to provider records is limited. Methods:UAC-I was tested on 212 consenting adult veterans with mood disorder attending a VA medical center. Counts (inpatient days and outpatient encounters) and costs (dollars) computed from survey responses were compared with estimates from medical records and an alternative structured questionnaire. Results:The agreement between inpatient costs computed from provider records and from UAC-I responses, assessed using the intraclass correlation coefficient (ICC), was 0.66, 95% confidence interval (CI), 0.30–0.84; the bias was −3.7%, 95% CI, −48 to 41. The ICC for the service data (inpatient days) was 0.97, 95% CI, 0.95–0.99; the bias was <1%, 95% CI, −14 to 15. The ICC for outpatient costs computed from provider records and from UAC-I responses was 0.53 95% CI, 0.38–0.65; the bias was <1%, 95% CI, −27 to 27. The ICC for outpatient encounters was 0.74, 95% CI, 0.65–0.80; the bias was <1%, 95% CI, −16 to 18. Conclusions:These results indicate that it may be feasible for cost-outcome studies to compare patient groups for inpatient and outpatient costs computed from patient self-reports.

A systematic approach to subgroup analyses in a smoking cessation trial

Abstract Background: Traditional approaches to subgroup analyses that test each moderating factor as a separate hypothesis can lead to erroneous conclusions due to the problems of multiple comparisons, model misspecification, and multicollinearity. Objective: To demonstrate a novel, systematic approach to subgroup analyses that avoids these pitfalls. Methods: A Best Approximating Model (BAM) approach that identifies multiple moderators and estimates their simultaneous impact on treatment effect sizes was applied to a randomized, controlled, 11-week, double-blind efficacy trial on smoking cessation of adult smokers with attention-deficit/hyperactivity disorder (ADHD), randomized to either OROS-methylphenidate (n = 127) or placebo (n = 128), and treated with nicotine patch. Binary outcomes measures were prolonged smoking abstinence and point prevalence smoking abstinence. Results: Although the original clinical trial data analysis showed no treatment effect on smoking cessation, the BAM analysis showed significant subgroup effects for the primary outcome of prolonged smoking abstinence: (1) lifetime history of substance use disorders (adjusted odds ratio [AOR] 0.27; 95% confidence interval [CI] 0.10–0.74), and (2) more severe ADHD symptoms (baseline score >36; AOR 2.64; 95% CI 1.17–5.96). A significant subgroup effect was also shown for the secondary outcome of point prevalence smoking abstinence – age 18 to 29 years (AOR 0.23; 95% CI 0.07–0.76). Conclusions: The BAM analysis resulted in different conclusions about subgroup effects compared to a hypothesis-driven approach. By examining moderator independence and avoiding multiple testing, BAMs have the potential to better identify and explain how treatment effects vary across subgroups in heterogeneous patient populations, thus providing better guidance to more effectively match individual patients with specific treatments.

A Data Accounting System for Clinical Investigators

Clinical investigators often preprocess, process, and analyze their data without benefit of formally organized research centers to oversee data management. This article outlines a practical three-file structure to help guide these investigators track and document their data through processing and analyses. The proposed process can be implemented without additional training or specialized software. Thus, it is particularly well suited for research projects with small budgets or limited access to viable research/data coordinating centers.

Response to letter regarding “A systematic approach to subgroup analyses in a smoking cessation trial”

Sir: We appreciate the questions and are thankful for the opportunity to further clarify our approach. In Westover et al. (1), the pool of expert-specified recoded 50 covariates (including possible...