Clinical prediction models to diagnose neonatal sepsis in low-income and middle-income countries

A scoping review

Bibliographic Data

ID21879448
AuthorsSamuel R Neal (0000-0001-6832-9839, Edinburgh College), Sarah Sturrock (0000-0002-7968-0189, St George's, University of London), Sarah S Sturrock (St George’s University of London, London, UK), David Musorowegomo (University of Zimbabwe), Hannah Gannon (0000-0002-5726-2752, University College London), Michele Zaman (0000-0003-1944-1351, Queen's University), Mario Cortina-Borja (UCL GOS Institute of Child Health, London, UK), Mario Cortina‐borja (0000-0003-0627-2624, University College London), Kirsty Le Doare (0000-0002-5104-085X, St George's, University of London), Michelle Heys (0000-0002-1458-505X, University College London), Gwendoline Chimhini (0000-0002-7280-3801, University of Zimbabwe), Felicity Fitzgerald (0000-0001-9594-3228, Imperial College London)
Year2025
Volume10
Issue4
Pagese017582
Publication date2025-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2024-017582
PMID40204466
OpenAlexW4409287624
LanguageEN
Citations received1
References cited88

INTRODUCTION: Neonatal sepsis causes significant morbidity and mortality worldwide but is difficult to diagnose clinically. Clinical prediction models (CPMs) could improve diagnostic accuracy, facilitating earlier treatment for cases and avoiding antibiotic overuse. Neonates in low-income and middle-income countries (LMICs) are disproportionately affected by sepsis, yet no review has comprehensively synthesised evidence for CPMs validated in this setting. METHODS: We performed a scoping review of CPMs to diagnose neonatal sepsis using Ovid MEDLINE, Ovid Embase, Scopus, Web of Science, Global Index Medicus and the Cochrane Library. The most recent searches were performed on 16 June 2024. We included studies published in English or Spanish that validated a new or existing CPM for neonatal sepsis in any healthcare setting in an LMIC. Studies were excluded if they validated a prognostic model or where data for neonates could not be separated from a larger paediatric population. Studies were selected by two independent reviewers and summarised by narrative synthesis. RESULTS: From 4598 unique records, we included 82 studies validating 44 distinct models in 24 252 neonates. Most studies were set in neonatal intensive or special care units (n=64, 78%) in middle-income countries (n=81, 99%) and included neonates already suspected of sepsis (n=58, 71%). Only four studies (5%) were set in the WHO African region, and only one study included data from a low-income country. Two-thirds of CPMs (n=30) required laboratory parameters, and three-quarters (n=34) were only validated in one study. CONCLUSION: Our review highlights several literature gaps, particularly a paucity of studies validating models in the lowest-income countries where neonatal sepsis is most prevalent, and models for the undifferentiated neonatal population that do not rely on laboratory tests. Furthermore, heterogeneity in study populations, definitions of sepsis and reporting of models inhibits meaningful comparison between studies and may hinder progress towards useful diagnostic tools

Cochrane Library · Developing country · Environmental health · Health care · Intensive care · Intensive care medicine · Low and middle income countries · MEDLINE · Meta-analysis · Middle income country · Neonatal sepsis · Population · Scopus · Sepsis · Medicine · Neonatal and Maternal Infections · Neonatal Respiratory Health Research · Sepsis Diagnosis and Treatment · Emergency Medicine · Internal Medicine · Pediatrics

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