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Updated: Jun 18, 2025
A Neonatal Imaging Model of Gram-Negative Bacterial Sepsis
Published on: August 12, 2020
Diagnostic Accuracy of Clinical Sign Algorithms to Identify Sepsis in Young Infants Aged 0 to 59 Days: A Systematic
Alastair Fung1, Yasir Shafiq2,3,4,5, Sophie Driker4
1Division of Paediatric Medicine, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Insights
Clinical sign algorithms, including the Integrated Management of Childhood Illness (IMCI) approach, show acceptable sensitivity for identifying sepsis in young infants. However, specificity decreases when laboratory-supported sepsis is the diagnostic standard.
Area of Science:
- Pediatrics
- Infectious Diseases
- Diagnostic Accuracy
Background:
- Early and accurate sepsis identification in neonates is critical for reducing morbidity and mortality.
- Clinical signs are key indicators for suspected sepsis in infants.
Purpose of the Study:
- To synthesize evidence on the diagnostic accuracy of clinical sign algorithms for identifying sepsis in young infants (0-59 days).
- Evaluate the effectiveness of Integrated Management of Childhood Illness (IMCI) algorithms.
Main Methods:
- Systematic review and meta-analysis of studies reporting diagnostic accuracy measures.
- Searched multiple databases including MEDLINE, Embase, CINAHL, Global Index Medicus, and Cochrane CENTRAL.
- Utilized Cochrane methods for data extraction and Grading of Recommendations Assessment, Development and Evaluation (GRADE) for certainty of evidence.
Main Results:
- Included 19 studies (12 IMCI, 7 non-IMCI).
- The WHO 7-sign IMCI algorithm showed 79% sensitivity and 77% specificity for hospitalization/antibiotics in sick infants.
- Pooled analysis of any IMCI algorithm demonstrated 84% sensitivity and 80% specificity for suspected sepsis.
- When using laboratory-supported sepsis, IMCI algorithms had 86% sensitivity but only 61% specificity.
Conclusions:
- IMCI algorithms demonstrate acceptable sensitivity for detecting suspected sepsis in young infants.
- Lower specificity was observed when laboratory-confirmed sepsis was the reference standard.
- Heterogeneity in algorithms and reference standards presents limitations to the current evidence base.
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.
