ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021
Biomarkers to Distinguish Bacterial From Viral Pediatric Clinical Pneumonia in a Malaria-Endemic Setting.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- A multicenter prospective observational multi-omics study protocol to identify biomarkers for severe dengue: COMBAT study clinical protocol.BMC infectious diseases · 2026Observational
- Article
- Artificial intelligence in the diagnosis and prognosis of pediatric bacterial pneumonia: current advances and challenges.Current opinion in pediatrics · 2026Review
- Blood-based inflammatory parameters and machine learning models for mortality prediction in critically ill pediatric pneumonia: a retrospective cohort study.Translational pediatrics · 2026Article
- Diagnostic testing and antibiotic stewardship for pneumonia in children worldwide: current developments and next steps.Current opinion in pediatrics · 2025Review
- Development of a host-signature-based machine learning model to diagnose bacterial and viral infections in febrile children.Frontiers in pediatrics · 2025Article
- A novel biomarker of COVID-19: MMP8 emerged by integrated bulk RNAseq and single-cell sequencing.Scientific reports · 2024Article
- Single-cell transcriptome analysis of the mouse lungs during the injury and recovery periods after lipopolysaccharide administration.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2024Article
- Signature Proteins in Small Extracellular Vesicles of Granulocytes and CD4International journal of molecular sciences · 2024Article
- Circulating markers of neutrophil activation and lung injury in pediatric pneumonia in low-resource settings.Pathogens and global health · 2023Article
- Prognostic accuracy of biomarkers of immune and endothelial activation in Mozambican children hospitalized with pneumonia.PLOS global public health · 2023Article
- Host Respiratory Transcriptome Signature Associated with Poor Outcome in Children with Influenza-Staphylococcus aureus Pneumonia.The Journal of infectious diseases · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
backgroundDifferential etiologies of pediatric acute febrile respiratory illness pose challenges for all populations globally, but especially in malaria-endemic settings because the pathogens responsible overlap in clinical presentation and frequently occur together. Rapid identification of bacterial pneumonia with high-quality diagnostic tools would enable appropriate, point-of-care antibiotic treatment. Current diagnostics are insufficient, and the discovery and development of new tools is needed. We report a unique biomarker signature identified in blood samples to accomplish this.
methodsBlood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based, high-dynamic-range, quantitative assay (~1200 proteins). We identified new biomarkers using a training set of samples from patients with established bacterial, viral, or malarial pneumonia. Proteins with significantly variable abundance across etiologies (false discovery rate <0.01) formed the basis for predictive diagnostic models derived from machine learning techniques (Random Forest, Elastic Net). Validation on a dedicated test set of samples was performed.
resultsSignificantly different abundances between bacterial and viral infections (219 proteins) and bacterial infections and mixed (viral and malaria) infections (151 proteins) were found. Predictive models achieved >90% sensitivity and >80% specificity, regardless of number of pathogen classes. Bacterial pneumonia was strongly associated with neutrophil markers-in particular, degranulation including HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI.
conclusionsBlood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.