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

Statin Use Associates with a Lower Incidence of Acute Kidney Injury after Major Elective Surgery

Statins abrogate ischemic renal injury in animal studies but whether they are renoprotective in humans is unknown. We conducted a population-based retrospective cohort study that included 213,347 older patients who underwent major elective surgery in the province of Ontario, Canada from 1995 to 2008. During the first 14 postoperative days, 1.9% (4020 patients), developed acute kidney injury and 0.5% (1173 patients), required acute dialysis. The 30-day mortality rate was 2.8% (5974 patients). Prior to surgery, 32% of patients were taking a statin. After statistical adjustment for patient and surgical characteristics, statin use associated with 16% lower odds of acute kidney injury (OR, 0.84; 95% CI, 0.79 to 0.90), 17% lower odds of acute dialysis (OR, 0.83; 95% CI, 0.72 to 0.95), and 21% lower odds of mortality (OR, 0.79; 95% CI, 0.74 to 0.85). Propensity score matching produced similar results. These data suggest that statins may protect against renal complications after major elective surgery and reduce perioperative mortality

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