Automated digital technologies for supporting sepsis prediction in children: a scoping review protocol

Area of Science:

• Pediatric Sepsis Research
• Digital Health Technologies
• Clinical Decision Support Systems

Background:

• Limited reviews exist on digital sepsis prediction for children, unlike adults.
• A knowledge gap persists in automated technology development for pediatric sepsis prediction.
• This review addresses the need for evidence on digital tools for early sepsis detection in children.

Purpose of the Study:

• To critically analyze evidence on the design and performance of automated digital technologies for pediatric sepsis prediction.
• To identify factors influencing the clinical integration of these technologies.
• To advance the development and implementation of pediatric sepsis prediction tools.

Main Methods:

• Scoping review following Arksey and O'Malley's framework.
• Searches across multiple databases (ACM, CINAHL, Embase, Google Scholar, IEEE, PubMed, Scopus, Web of Science).
• Inclusion of studies on children aged >90 days to <21 years; thematic analysis of extracted data.

Main Results:

• The review will identify current evidence on digital pediatric sepsis prediction technologies.
• It will detail the design characteristics and performance metrics of these technologies.
• Factors influencing clinical integration will be elucidated.

Conclusions:

• This review will provide a comprehensive overview of the current landscape of digital pediatric sepsis prediction.
• Findings will inform the future development and clinical integration of these vital technologies.
• The study aims to improve timely and accurate sepsis detection in children.