Context: Accurate identification of possible sepsis in young infants is needed to effectively manage and reduce sepsis-related morbidity and mortality.
Objective: Synthesize evidence on the diagnostic accuracy of clinical sign algorithms to identify young infants (aged 0-59 days) with suspected sepsis.
Data sources: MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL Registry of Trials.
Study selection: Studies reporting diagnostic accuracy measures of algorithms including infant clinical signs to identify young infants with suspected sepsis.
Data extraction: We used Cochrane methods for study screening, data extraction, risk of bias assessment, and determining certainty of evidence using Grading of Recommendations Assessment Development and Evaluation.
Results: We included 19 studies (12 Integrated Management of Childhood Illness [IMCI] and 7 non-IMCI studies). The current World Health Organization (WHO) 7-sign IMCI algorithm had a sensitivity of 79% (95% CI 77%-82%) and specificity of 77% (95% CI 76%-78%) for identifying sick infants aged 0-59 days requiring hospitalization/antibiotics (1 study, N = 8889). Any IMCI algorithm had a pooled sensitivity of 84% (95% CI 75%-90%) and specificity of 80% (95% CI 64%-90%) for identifying suspected sepsis (11 studies, N = 15523). When restricting the reference standard to laboratory-supported sepsis, any IMCI algorithm had a pooled sensitivity of 86% (95% CI 82%-90%) and lower specificity of 61% (95% CI 49%-72%) (6 studies, N = 14278).
Limitations: Heterogeneity of algorithms and reference standards limited the evidence.
Conclusions: IMCI algorithms had acceptable sensitivity for identifying young infants with suspected sepsis. Specificity was lower using a reference standard of laboratory-supported sepsis diagnosis.