Background

Severe injury initiates a complex physiologic response encompassing multiple systems and varies phenotypically between patients. Trauma-induced coagulopathy may be an early warning of a poorly coordinated response at the molecular level, including a deleterious immunologic response and worsening of shock states. The onset of trauma-induced coagulopathy (TIC) may be subtle however. In previous work, we identified an early warning sign of coagulopathy from the admission thromboelastogram, called the MAR ratio. We hypothesized that a low MAR ratio would be associated with specific derangements in the inflammatory response.

Methods

In this prospective, observational study, 88 blunt trauma patients admitted to the intensive care unit (ICU) were identified. Concentrations of inflammatory mediators were recorded serially over the course of a week and the MAR ratio was calculated from the admission thromboelastogram. Correlation analysis was used to assess the relationship between MAR and inflammatory mediators. Dynamic network analysis was used to assess coordination of immunologic response.

Results

Seventy-nine percent of patients were male and mean age was 37 years (SD 12). The mean ISS was 30.2 (SD 12) and mortality was 7.2%. CRITICAL patients (MAR ratio ≤14.2) had statistically higher shock volumes at three time points in the first day compared to NORMAL patients (MAR ratio >14.2). CRITICAL patients had significant differences in IL-6 (P=0.0065), IL-8 (P=0.0115), IL-10 (P=0.0316) and MCP-1 (P=0.0039) concentrations compared to NORMAL. Differences in degree of expression and discoordination of immune response continued in CRITICAL patients throughout the first day.

Conclusions

The admission MAR ratio may be the earliest warning signal of a pathologic inflammatory response associated with hypoperfusion and TIC. A low MAR ratio is an early indication of complicated dysfunction of multiple molecular processes following trauma.

Introduction

Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent.

Methods

The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have.

Results

Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation.

Discussion

Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal.

Introduction

Pragmatic trials in comparative effectiveness research assess the effects of different treatment, therapeutic, or healthcare options in clinical practice. They are characterized by broad eligibility criteria and large sample sizes, which can lead to an unmanageable number of participants, increasing the risk of bias and affecting the integrity of the trial. We describe the development of a sampling strategy tool and its use in the PREPARE trial to circumvent the challenge of unmanageable work flow.

Methods

Given the broad eligibility criteria and high fracture volume at participating clinical sites in the PREPARE trial, a pragmatic sampling strategy was needed. Using data from PREPARE, descriptive statistics were used to describe the use of the sampling strategy across clinical sites. A Chi-square test was performed to explore whether use of the sampling strategy was associated with a reduction in the number of missed eligible patients.

Results

7 of 20 clinical sites (35%) elected to adopt a sampling strategy. There were 1539 patients excluded due to the use of the sampling strategy, which represents 30% of all excluded patients and 20% of all patients screened for participation. Use of the sampling strategy was associated with lower odds of missed eligible patients (297/4545 (6.5%) versus 341/3200 (10.7%) p < 0.001).

Conclusions

Implementing a sampling strategy in the PREPARE trial has helped to limit the number of missed eligible patients. This sampling strategy represents a simple, easy to use tool for managing work flow at clinical sites and maintaining the integrity of a large trial.