ABSTRACT
BACKGROUND: Supplemental oxygen therapy is central to the treatment of acute hypoxaemic respiratory failure, a condition which remains a major driver for morbidity and mortality in intensive care. Despite several large randomised clinical trials comparing a higher versus a lower oxygenation target for these patients, significant differences in study design impede analysis of aggregate data and final clinical recommendations. METHODS: This paper presents the protocol for conducting an individual patient data meta-analysis where full individual patient data according to the intention-to-treat principle will be pooled from the HOT-ICU and HOT-COVID trials in a one-step procedure. The two trials are near-identical in design. We plan to use a hierarchical general linear mixed model that accounts for data clustering at a trial and site level. The primary outcome will be 90-day all-cause mortality while the secondary outcome will be days alive without life-support at 90 days. Further, we outline 14 clinically relevant predefined subgroups which we will analyse for heterogeneity in the intervention effects and interactions, and we present a plan for assessing the credibility of the subgroup analyses. CONCLUSION: The presented individual patient data meta-analysis will synthesise individual level patient data from two of the largest randomised clinical trials on targeted oxygen therapy in intensive care. The results will provide a re-analysis of the intervention effects on the pooled intention-to-treat populations and facilitate subgroup analyses with an increased power to detect clinically important effect modifications.