Objective: The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. Data sources: We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. Methods: We show sample size calculations for a twointervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratifi ed design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratifi ed design). Results: The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratifi ed design further reduces the sample size requirement compared with the unstratifi ed design. Conclusions: The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.
|Number of pages||7|
|Journal||Critical Care and Resuscitation|
|Publication status||Published - 1 Jun 2018|