Evidence map›Paper›PMID 40074245›Full record

ArticleBMJ paediatrics open2025

Identification of distinct clinical profiles of sepsis risk in paediatric emergency department patients using Bayesian profile regression.

Patricia Gilholm, Sainath Raman, Adam Irwin, Paula Lister, Amanda Harley, Luregn J Schlapbach, Kristen S Gibbons

Abstract readMulticenter Study
In one paragraph

Article in BMJ paediatrics open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Patricia GilholmChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, South Brisbane, Queensland, Australia p.gilholm@uq.edu.au.ORCID http://orcid.org/0000-0001-8135-1520
Sainath RamanChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, South Brisbane, Queensland, Australia.
Adam IrwinQueensland Children's Hospital, South Brisbane, Queensland, Australia.ORCID http://orcid.org/0000-0001-8974-6789
Paula ListerPaediatric Critical Care Unit, Sunshine Coast University Hospital, Sunshine Coast, Queensland, Australia.
Amanda HarleyQueensland Children's Hospital, South Brisbane, Queensland, Australia.
Luregn J SchlapbachChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, South Brisbane, Queensland, Australia.
Kristen S GibbonsChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, South Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis affects 25 million children and neonates annually, causing significant mortality and morbidity. Early identification and treatment are crucial for improving outcomes. Identifying children at risk is challenging due to clinical heterogeneity and overlap with other conditions. Current evaluations of sepsis criteria adopt a variable-centred approach, evaluating each criterion independently. The objective of this study was to explore associations between patterns of sepsis screening criteria and sepsis risk in children screened in the emergency department (ED) to identify distinct profiles that describe the clinical heterogeneity of suspected sepsis.

methodsThis secondary analysis involved 3473 children screened for sepsis across 12 EDs in Queensland, Australia. Bayesian profile regression was used to construct data-driven clinical profiles derived from sepsis screening criteria and their association with suspected sepsis, defined as senior medical officer diagnosis and antibiotic administration in the ED. Posterior risk probabilities (Prs) with 95% credible intervals (CIs) were calculated for each profile. Profiles were internally validated by assessing their association with sepsis, septic shock, organ dysfunction and infection sources, in both adjusted and unadjusted models.

resultsSeven distinct clinical profiles were identified. Two profiles were labelled as high risk of suspected sepsis (profile 1, n=22: Pr 0.73, 95% CI 0.55, 0.89; profile 2, n=150: Pr 0.69, 95% CI 0.59, 0.80), four as moderate risk and one as low risk. High-risk profiles were characterised by severe illness indicators and elevated lactate levels. Moderate-risk profiles included criteria such as altered behaviour, young age (<3 months) and respiratory distress. High-risk profiles had strong associations with all clinical outcomes.

conclusionsSeven clinical profiles were identified that varied in their risk of suspected sepsis and associated outcomes. Validation of these profiles in diverse populations and identification of which profiles are likely to benefit from certain interventions is needed.

Indexed as

Emergency Service, HospitalSepsisAdolescentBayes TheoremChildChild, PreschoolFemaleHumansInfantInfant, NewbornMaleMass ScreeningQueenslandRisk AssessmentRisk FactorsChild HealthStatistics

Identifiers

PMID40074245
PMCPMC11906992

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.