Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article

CT Prediction Model for Major Arterial Injury after Blunt Pelvic Ring Disruption.

Purpose To develop and test a computed tomography (CT)-based predictive model for major arterial injury after blunt pelvic ring disruptions that incorporates semiautomated pelvic hematoma volume quantification. Materials and Methods A multivariable logistic regression model was developed in patients with blunt pelvic ring disruptions who underwent arterial phase abdominopelvic CT before angiography from 2008 to 2013. Arterial injury at angiography requiring transarterial embolization (TAE) served as the outcome. Areas under the receiver operating characteristic (ROC) curve (AUCs) for the model and for two trauma radiologists were compared in a validation cohort of 36 patients from 2013 to 2015 by using the Hanley-McNeil method. Hematoma volume cutoffs for predicting the need for TAE and probability cutoffs for the secondary outcome of mortality not resulting from closed head injuries were determined by using ROC analysis. Correlation between hematoma volume and transfusion was assessed by using the Pearson coefficient. Results Independent predictor variables included hematoma volume, intravenous contrast material extravasation, atherosclerosis, rotational instability, and obturator ring fracture. In the validation cohort, the model (AUC, 0.78) had similar performance to reviewers (AUC, 0.69-0.72; P = .40-.80). A hematoma volume cutoff of 433 mL had a positive predictive value of 87%-100% for predicting major arterial injury requiring TAE. Hematoma volumes correlated with units of packed red blood cells transfused (r = 0.34-0.57; P = .0002-.0003). Predicted probabilities of 0.64 or less had a negative predictive value of 100% for excluding mortality not resulting from closed head injuries. Conclusion A logistic regression model incorporating semiautomated hematoma volume segmentation produced objective probability estimates of major arterial injury. Hematoma volumes correlated with 48-hour transfusion requirement, and low predicted probabilities excluded mortality from causes other than closed head injury

Building a Clinical Research Network in Trauma Orthopaedics: The Major Extremity Trauma Research Consortium (METRC)

OBJECTIVESLessons learned from battle have been fundamental to advancing the care of injuries that occur in civilian life. Equally important is the need to further refine these advances in civilian practice, so they are available during future conflicts. The Major Extremity Trauma Research Consortium (METRC) was established to address these needs.METHODSMETRC is a network of 22 core level I civilian trauma centers and 4 core military treatment centers-with the ability to expand patient recruitment to more than 30 additional satellite trauma centers for the purpose of conducting multicenter research studies relevant to the treatment and outcomes of orthopaedic trauma sustained in the military. Early measures of success of the Consortium pertain to building of an infrastructure to support the network, managing the regulatory process, and enrolling and following patients in multiple studies.RESULTSMETRC has been successful in maintaining the engagement of several leading, high volume, level I trauma centers that form the core of METRC; together they operatively manage 15,432 major fractures annually. METRC is currently funded to conduct 18 prospective studies that address 6 priority areas. The design and implementation of these studies are managed through a single coordinating center. As of December 1, 2015, a total of 4560 participants have been enrolled.CONCLUSIONSSuccess of METRC to date confirms the potential for civilian and military trauma centers to collaborate on critical research issues and leverage the strength that comes from engaging patients and providers from across multiple centers

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

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