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Study Protocol for the Use of Propofol in Adult Intensive Care Unit Patients: A Secondary Analysis of an Extensive International Database

MCML Authors

Abstract

Background and aims:<br>There are conflicting data regarding the use of propofol in the intensive care unit. The present study aims to explore the propofol dose-response relationship in the context of associations with clinical outcomes. Here we present the data collection and analysis procedures.<br>Methods and analysis:<br>The International Nutrition Survey (www.criticalcarenutrition.com) contains data from 785 medical, surgical, or trauma intensive care units. This survey also includes data on daily mechanical ventilation and propofol use, along with the associated propofol-related energy intake. Of the 21,100 adult patients, we will analyze those who spent at least 48 hours in the intensive care unit. Data collection will include patient characteristics, propofol parameters, use of mechanical ventilation, severity of illness at intensive care unit admission, and time to discharge alive or in-hospital death. In addition to the duration of propofol therapy (days), propofol-associated fat intake will be used as a surrogate for propofol dose. Statistical analyses will use multistate models and piece-wise exponential additive mixed models to examine associations between propofol use (including associated fat intake) and outcomes, while adjusting for numerous confounders and accounting for mechanical ventilation.<br>Ethics and dissemination:<br>Institutional ethics approval was granted by the Health Sciences Research Ethics Board at Queen’s University, Kingston, Ontario (file number 6004791). Informed patient consent was not required due to the nature of this study. Procedures were conducted in accordance with the ethical standards of the institutional or regional committee for human experimentation and the Helsinki Declaration of 1975.

article HSK+26

critcaresci

38. Feb. 2026.

Authors

W. H. Hartl • C. Stoppe • Y. Kotani • G. Landoni • A. G. Day • J. Piller • M. Neuberger • A. Bender

Links

DOI

Research Areas

 A1 | Statistical Foundations & Explainability

 C4 | Computational Social Sciences

BibTeXKey: HSK+26

#p-bischl #p-kuechenhoff
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