Arnup Sarah J, McKenzie Joanne E, Pilcher David, Bellomo Rinaldo, Forbes Andrew B
School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Centre for Outcome and Resource Evaluation, Australian and New Zealand Intensive Care Society, Melbourne, VIC, Australia.
Crit Care Resusc. 2018 Jun;20(2):117-123.
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.
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.
We show sample size calculations for a two-intervention, 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 (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design).
The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design.
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.
整群随机交叉（CRXO）设计为开展随机对照试验以评估重症监护环境中的低风险干预措施提供了契机。我们的目的是提供一份关于如何进行CRXO试验样本量计算的教程，重点讲解计算所需各要素的含义，并应用于重症监护试验。
我们使用澳大利亚和新西兰重症监护学会成人患者数据库临床登记处的全因院内死亡率来说明样本量计算。
我们展示了一项针对两种干预措施、两个12个月周期的横断面CRXO试验的样本量计算。我们提供公式及其使用示例，以确定在样本量计算所需要素在所有重症监护病房中保持恒定的试验（非分层设计）以及在样本量计算所需要素存在明显不同组（层）的重症监护病房（分层设计）中，检测两种干预措施之间具有指定检验效能水平的风险比（RR）所需的重症监护病房数量。
与平行组整群随机设计相比，CRXO设计在示例案例中显著降低了样本量要求。与非分层设计相比，分层设计进一步降低了样本量要求。
CRXO设计能够评估常规使用的干预措施，这些措施可在重症监护环境中为患者护理带来虽小但重要的改善。
