Reappraisal of Ventilator-Free Days in Critical Care Research.

Pubmed ID: 31034248

Pubmed Central ID: PMC6812447

Journal: American journal of respiratory and critical care medicine

Publication Date: Oct. 1, 2019

Affiliation: Department of Pediatrics, University of Utah, Salt Lake City, Utah.

MeSH Terms: Humans, Data Interpretation, Statistical, Regression Analysis, Research Design, Respiration, Artificial, Critical Care, Outcome Assessment, Health Care, Airway Extubation, Data Analysis, Respiratory Distress Syndrome

Grants: K23 HL136688, K99 HL141678, L40 HL134039

Authors: Schoenfeld DA, Yehya N, Harhay MO, Curley MAQ, Reeder RW

Cite As: Yehya N, Harhay MO, Curley MAQ, Schoenfeld DA, Reeder RW. Reappraisal of Ventilator-Free Days in Critical Care Research. Am J Respir Crit Care Med 2019 Oct 1;200(7):828-836.



Ventilator-free days (VFDs) are a commonly reported composite outcome measure in acute respiratory distress syndrome trials. VFDs combine survival and duration of ventilation in a manner that summarizes the "net effect" of an intervention on these two outcomes. However, this combining of outcome measures makes VFDs difficult to understand and analyze, which contributes to imprecise interpretations. We discuss the strengths and limitations of VFDs and other "failure-free day" composites, and we provide a framework for when and how to use these outcome measures. We also provide a comprehensive discussion of the different analytic methods for analyzing and interpreting VFDs, including Student's <i>t</i> tests and rank-sum tests, as well as competing risk regressions treating extubation as the primary outcome and death as the competing risk. Using simulations, we illustrate how the statistical test with optimal power depends on the relative contributions of mortality and ventilator duration on the composite effect size. Finally, we recommend a simple analysis and reporting framework using the competing risk approach, which provides clear information on the effect size of an intervention, a statistical test and measure of confidence with the ability to adjust for baseline factors and allow interim monitoring for trials. We emphasize that any approach to analyzing a composite outcome, including other "failure-free day" constructs, should also be accompanied by an examination of the components.