Premium
Agents intervening against delirium in the intensive care unit trial—Protocol for a secondary Bayesian analysis
Author(s) -
AndersenRanberg Nina,
Poulsen Lone M.,
Perner Anders,
Hästbacka Johanna,
Morgan Matthew P. G.,
Citerio Giuseppe,
OxenbøllCollet Marie,
Weber SvenOlaf,
Andreasen Anne Sofie,
Bestle Morten H.,
Uslu Bülent,
Pedersen Helle B. S.,
Nielsen Louise G.,
Damgaard Kjeld,
Jensen Troels B.,
Sommer Trine,
Dey Nilanjan,
Mathiesen Ole,
Granholm Anders
Publication year - 2022
Publication title -
acta anaesthesiologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 107
eISSN - 1399-6576
pISSN - 0001-5172
DOI - 10.1111/aas.14091
Subject(s) - medicine , delirium , credible interval , intensive care unit , logistic regression , intensive care medicine , frequentist inference , intensive care , bayesian probability , emergency medicine , confidence interval , bayesian inference , statistics , mathematics
Background Delirium is highly prevalent in the intensive care unit (ICU) and is associated with high morbidity and mortality. The antipsychotic haloperidol is the most frequently used agent to treat delirium although this is not supported by solid evidence. The agents intervening against delirium in the intensive care unit (AID‐ICU) trial investigates the effects of haloperidol versus placebo for the treatment of delirium in adult ICU patients. Methods This protocol describes the secondary, pre‐planned Bayesian analyses of the primary and secondary outcomes up to day 90 of the AID‐ICU trial. We will use Bayesian linear regression models for all count outcomes and Bayesian logistic regression models for all dichotomous outcomes. We will adjust for stratification variables (site and delirium subtype) and use weakly informative priors supplemented with sensitivity analyses using sceptical priors. We will present results as absolute differences (mean differences and risk differences) and relative differences (ratios of means and relative risks). Posteriors will be summarised using median values as point estimates and percentile‐based 95% credibility intervals. Probabilities of any benefit/harm, clinically important benefit/harm and clinically unimportant differences will be presented for all outcomes. Discussion The results of this secondary, pre‐planned Bayesian analysis will complement the primary frequentist analysis of the AID‐ICU trial and facilitate a nuanced and probabilistic interpretation of the trial results.