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Updated: May 12, 2026

A Model to Simulate Clinically Relevant Hypoxia in Humans
Published on: December 22, 2016
Oxygen therapy in early warning scores: a systematic review and meta-analysis
Charlotte H Harrison1, Phoebe Tupper2, Stephen Gerry3
1Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK charlotte.harrison@ndcn.ox.ac.uk.
Background:
Early warning systems (EWS) used across the world typically assign a fixed number of points to patients receiving supplemental oxygen, regardless of amount. This ordinal binary approach may fail to recognise deteriorating patients who have an increasing oxygen requirement with otherwise stable observations. It is unclear whether weighting oxygen beyond binary scoring improves recognition of deterioration.
Aims:
We aimed to describe all general adult EWS that grade oxygen beyond binary scoring (part 1). Where reported, we summarised the performance of graded oxygen EWS in comparison to binary scoring (part 2).
Methods:
We systematically reviewed the literature, searching Embase, MEDLINE, CINAHL, Cochrane Central and Web of Science. We included studies of vital-sign-only EWS, for adult inpatients, which included grades of oxygen therapy above binary weighting ('graded oxygen weighting'). We summarised methods of including graded oxygen therapy. We performed a random-effects meta-analysis of the effects of graded oxygen weighting inclusion in comparison to binary weighting. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool.
Results:
15 studies reported the development of 16 EWS with graded oxygen weighting, classified by flow rate, delivery device and/or fraction of inspired oxygen. Four studies compared graded oxygen EWS to binary oxygen EWS. Meta-analysis showed a significant improvement in the performance of graded oxygen EWS over binary oxygen EWS (logit(AUROC)=0.19; 95% CI 0.094 to 0.285; p=0.002). 15/16 models were at high risk of bias.
Conclusions:
16 EWS with graded oxygen weighting were identified. Graded oxygen models had improved recognition of deterioration. Future work should explore the optimal method of oxygen classification and how this could be integrated into future EWS.
Prospero Registration Number:
CRD42024443362.
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