{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T00:32:35Z","timestamp":1747182755512,"version":"3.40.5"},"reference-count":43,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T00:00:00Z","timestamp":1614211200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acta Anaesthesiol Scand"],"published-print":{"date-parts":[[2021,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Coronavirus disease 2019 (COVID\u201019) can lead to severe hypoxic respiratory failure and death. Corticosteroids decrease mortality in severely or critically ill patients with COVID\u201019. However, the optimal dose remains unresolved. The ongoing randomised COVID STEROID 2 trial investigates the effects of higher vs lower doses of dexamethasone (12 vs 6\u00a0mg intravenously daily for up to 10\u00a0days) in 1,000 adult patients with COVID\u201019 and severe hypoxia.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This protocol outlines the rationale and statistical methods for a secondary, pre\u2010planned Bayesian analysis of the primary outcome (days alive without life support at day 28) and all secondary outcomes registered up to day 90. We will use hurdle\u2010negative binomial models to estimate the mean number of days alive without life support in each group and present results as mean differences and incidence rate ratios with 95% credibility intervals (CrIs). Additional count outcomes will be analysed similarly and binary outcomes will be analysed using logistic regression models with results presented as probabilities, relative risks and risk differences with 95% CrIs. We will present probabilities of any benefit\/harm, clinically important benefit\/harm and probabilities of effects smaller than pre\u2010defined clinically minimally important differences for all outcomes analysed. Analyses will be adjusted for stratification variables and conducted using weakly informative priors supplemented by sensitivity analyses using sceptic priors.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>This secondary, pre\u2010planned Bayesian analysis will supplement the primary, conventional analysis and may help clinicians, researchers and policymakers interpret the results of the COVID STEROID 2 trial while avoiding arbitrarily dichotomised interpretations of the results.<\/jats:p><\/jats:sec><jats:sec><jats:title>Trial registration<\/jats:title><jats:p>ClinicalTrials.gov: NCT04509973; EudraCT: 2020\u2010003363\u201025.<\/jats:p><\/jats:sec>","DOI":"10.1111\/aas.13793","type":"journal-article","created":{"date-parts":[[2021,2,14]],"date-time":"2021-02-14T18:06:56Z","timestamp":1613326016000},"page":"702-710","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Higher vs Lower Doses of Dexamethasone in Patients with COVID\u201019 and Severe Hypoxia (COVID STEROID 2) trial: Protocol for a secondary Bayesian analysis"],"prefix":"10.1111","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5799-7655","authenticated-orcid":false,"given":"Anders","family":"Granholm","sequence":"first","affiliation":[{"name":"Department of Intensive Care, Rigshospitalet University of Copenhagen Denmark"},{"name":"Collaboration for Research in Intensive Care (CRIC) Copenhagen Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1127-9599","authenticated-orcid":false,"given":"Marie Warrer","family":"Munch","sequence":"additional","affiliation":[{"name":"Department of Intensive Care, Rigshospitalet University of Copenhagen Denmark"},{"name":"Collaboration for Research in Intensive Care (CRIC) Copenhagen Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheila 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