ArticleVirology journal2024
Application of peripheral blood routine parameters in the diagnosis of influenza and Mycoplasma pneumoniae.
Article in Virology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Complete Blood Count-Derived Inflammatory Markers in Pediatric Lower Respiratory Tract Infection: A Narrative Review.Pathogens (Basel, Switzerland) · 2026Review
- A diagnostic model for discrimination between Pneumocystis jirovecii pneumonia and colonization based on multiple parameters.Scientific reports · 2026Article
- Clinical Analysis of Neonatal Influenza in the Neonatal Intensive Care Unit: A Retrospective Study.Immunity, inflammation and disease · 2026Article
- Designing a broad-spectrum multi-epitope vaccine against influenza A andFrontiers in public health · 2026Article
- Exploring Clinical Characteristics and Risk Factors ofJournal of inflammation research · 2026Article
- Early diagnosis and prognostic prediction of secondary bloodstream infections caused byFrontiers in cellular and infection microbiology · 2025Article
- Proteomic characteristics of bronchoalveolar lavage fluid in children with mild and severeFrontiers in microbiology · 2025Article
- The diagnostic value of lymphocyte profiling for infectious mononucleosis and mycoplasma pneumoniae pneumonia.Frontiers in pediatrics · 2025Article
- Biomarkers associated with the diagnosis and prognosis ofFrontiers in cellular and infection microbiology · 2025Review
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Authors and funding
10 authors.
Funding
Abstract
objectivesInfluenza and Mycoplasma pneumoniae infections often present concurrent and overlapping symptoms in clinical manifestations, making it crucial to accurately differentiate between the two in clinical practice. Therefore, this study aims to explore the potential of using peripheral blood routine parameters to effectively distinguish between influenza and Mycoplasma pneumoniae infections.
methodsThis study selected 209 influenza patients (IV group) and 214 Mycoplasma pneumoniae patients (MP group) from September 2023 to January 2024 at Nansha Division, the First Affiliated Hospital of Sun Yat-sen University. We conducted a routine blood-related index test on all research subjects to develop a diagnostic model. For normally distributed parameters, we used the T-test, and for non-normally distributed parameters, we used the Wilcoxon test.
resultsBased on an area under the curve (AUC) threshold of ≥ 0.7, we selected indices such as Lym# (lymphocyte count), Eos# (eosinophil percentage), Mon% (monocyte percentage), PLT (platelet count), HFC# (high fluorescent cell count), and PLR (platelet to lymphocyte ratio) to construct the model. Based on these indicators, we constructed a diagnostic algorithm named IV@MP using the random forest method.
conclusionsThe diagnostic algorithm demonstrated excellent diagnostic performance and was validated in a new population, with an AUC of 0.845. In addition, we developed a web tool to facilitate the diagnosis of influenza and Mycoplasma pneumoniae infections. The results of this study provide an effective tool for clinical practice, enabling physicians to accurately diagnose and differentiate between influenza and Mycoplasma pneumoniae infection, thereby offering patients more precise treatment plans.
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