Introduction Sepsis is a life-threatening condition in intensive care units (ICUs), where any delay in diagnosis and treatment can lead to organ dysfunction, prolonged hospital stay and increased mortality. Early identification of sepsis prior to its clinical manifestation may enable timely intervention and improve outcomes.
This review aims to identify, synthesise and categorise predictor variables assessed in adult ICU patients prior to sepsis diagnosis. Methods/design This protocol, in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guideline, will involve a comprehensive search of PubMed/Medline, Scopus, Embase, Web of Science, IEEE Xplore and Cochrane Library for English-language studies from database inception.
The search is planned to be conducted between March 2026 and June 2026. We will include prospective, retrospective, cohort, case - control and cross-sectional studies, and both randomised and non-randomised designs.
Additionally, we will consider secondary analysis of electronic health records, clinical registries and routinely acquired clinical data that determine risk factors and predictive variables that will help in the early identification of sepsis using machine learning, artificial intelligence, computational or statistical methods.
BMJ Open published a clinical update in Research Highlights on 16 Jun 2026.
The item focuses on Predictive variables for early detection of sepsis in adults admitted to intensive care units: protocol for a systematic review.
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