Background

Understanding soft tissue injury patterns associated with greater tuberosity (GT) fractures may help clinicians provide guidance to patients.

Hypothesis

Evaluating magnetic resonance imaging (MRI) findings in patients with suspected isolated GT fractures will help elucidate the role of MRI in the diagnosis and treatment of these patients.

Study design

Case series; Level of evidence, 4.

Methods

We performed a retrospective review of medical records from 2010 to 2014 for patients presenting with acute isolated GT fractures and MRI. Uncomplicated and delayed recovery groups were established according to the need for delayed procedural intervention or persistent symptoms past last recorded follow-up. Multivariate regression analysis was used to analyze the relationships between MRI findings and delayed recovery.

Results

A total of 32 patients met the inclusion criteria (mean age, 47 years [range, 24-88 years]; mean follow-up, 30 weeks [range, 33 days-4 years]). There was no significant difference in the estimation of fracture displacement as measured on radiography and compared with MRI (radiography, 2.8 mm; MRI, 3.5 mm; P = .16). There was a high incidence of full-thickness rotator cuff tears (9%), partial-thickness rotator cuff tears (72%), partial biceps tendon tears (41%), and labral tears (50%). Presence of biceps pathology or partial-thickness rotator cuff tear was predictive of delayed recovery in a multivariate model.

Conclusion

There is a high incidence of soft tissue injury found by MRI following GT fracture. MRI did not appreciably change the measure of displacement of the fracture fragment. In the multivariate analysis, presence of a partial-thickness rotator cuff tear or biceps tendon injury was associated with delayed recovery.

Background

There are few recent data examining the epidemiology of severe upper-extremity trauma in non-military patients. We used the National Trauma Data Bank (NTDB) to investigate the epidemiology and descriptive characteristics of upper-extremity amputations in U.S. trauma centers.

Methods

We queried the 2009 to 2012 NTDB research datasets for patients undergoing major upper-extremity amputation and extracted characteristics of the patient population, injury distribution, and treating facilities. In addition, multivariable regression models were fit to identify correlates of reoperation, major in-hospital complications, duration of hospitalization, and in-hospital mortality.

Results

A total of 1,386 patients underwent a major upper-extremity amputation secondary to a trauma-related upper-extremity injury, representing 46 per 100,000 NTDB trauma admissions from 2009 to 2012. The most frequent definitive procedures performed were amputations through the humerus (35%), forearm (30%), and hand (14%). The average duration of hospitalization for all amputees was 17 days. Thirty-one percent of patients underwent at least 1 reoperation. The rate of reoperation was significantly higher at university-associated hospitals compared with nonteaching or community hospitals (p < 0.0001). Patients who had at least 1 reoperation stayed in the hospital approximately 7 days longer than patients who did not undergo reoperation. The Injury Severity Score, hospital teaching status, concomitant neurovascular injury, and occurrence of a complication were significantly associated with reoperation.

Conclusions

The present study provides an updated report on the epidemiology and characteristics of trauma-related major upper-extremity amputation in the U.S. civilian population. Additional work is necessary to assess the long-term outcomes following attempted upper-extremity salvage. The population-level data provided by the present study may help to inform the design and implementation of future studies on the optimum treatment for this survivable but life-altering injury.

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.