1. Early In-Bed Cycle Ergometry With Critically Ill, Mechanically Ventilated Patients: Statistical Analysis Plan for CYCLE (Critical Care Cycling to Improve Lower Extremity Strength), an International, Multicenter, Randomized Clinical Trial
- Author
-
Diane Heels-Ansdell, Laurel Kelly, Heather K O'Grady, Christopher Farley, Julie C Reid, Sue Berney, Amy M Pastva, Karen EA Burns, Frédérick D'Aragon, Margaret S Herridge, Andrew Seely, Jill Rudkowski, Bram Rochwerg, Alison Fox-Robichaud, Ian Ball, Francois Lamontagne, Erick H Duan, Jennifer Tsang, Patrick M Archambault, Avelino C Verceles, John Muscedere, Sangeeta Mehta, Shane W English, Tim Karachi, Karim Serri, Brenda Reeve, Lehana Thabane, Deborah Cook, and Michelle E Kho
- Subjects
Medicine ,Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
BackgroundSurvivors of critical illness are at risk of developing physical dysfunction following intensive care unit (ICU) discharge. ICU-based rehabilitation interventions, such as early in-bed cycle ergometry, may improve patients’ short-term physical function. ObjectiveBefore unblinding and trial database lock, we describe a prespecified statistical analysis plan (SAP) for the CYCLE (Critical Care Cycling to Improve Lower Extremity Strength) randomized controlled trial (RCT). MethodsCYCLE is a 360-patient, international, multicenter, open-label, parallel-group RCT (1:1 ratio) with blinded primary outcome assessment at 3 days post-ICU discharge. The principal investigator and statisticians of CYCLE prepared this SAP with approval from the steering committee and coinvestigators. The SAP defines the primary and secondary outcomes (including adverse events) and describes the planned primary, secondary, and subgroup analyses. The primary outcome of the CYCLE trial is the Physical Function Intensive Care Unit Test-scored (PFIT-s) at 3 days post-ICU discharge. The PFIT-s is a reliable and valid performance-based measure. We plan to use a frequentist statistical framework for all analyses. We will conduct a linear regression to evaluate the primary outcome, incorporating randomization as an independent variable and adjusting for age (≥65 years versus
- Published
- 2024
- Full Text
- View/download PDF