Complete Blood Count and C-reactive Protein in Influenza Positive Children versus Influenza Negative Children Admitted at a Tertiary Care Centre: A Retrospective Observational Study
Published: April 1, 2026 | DOI: https://doi.org/10.7860/JCDR/2026/85335.22996
Rishika Anandan, Vimalraj Vijayakumar, Sugapriya Paranjothi, R Karthick Prasaad, Balaji Chinnasami, Subash Sundar
1. Junior Resident, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
2. Assistant Professor, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
3. Assistant Professor, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
4. Senior Resident, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
5. Professor, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
6. Professor, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India.
Correspondence
Dr. Vimalraj Vijayakumar,
Assistant Professor, Department of Paediatrics, SRM Medical College Hospital and Research Centre, Kattankulathur-603203, Tamil Nadu, India.
E-mail: vimalrav@srmist.edu.in
Introduction: Children’s respiratory illnesses are primarily caused by Influenza A and B viruses, which frequently result in severe morbidity. Polymerase Chain Reaction (PCR) testing is still the gold standard for diagnosis, although it can be time-consuming and not always practical in environments with limited resources. Since influenza infections can produce characteristic alterations in haematological parameters and inflammatory markers, evaluating these changes may aid in early diagnosis and management.
Aim: To compare Complete Blood Count (CBC) parameters and C-Reactive Protein (CRP) levels between influenza-positive and influenza-negative children.
Materials and Methods: This retrospective cross-sectional study was conducted at the Department of Paediatrics at SRM Medical College Hospital and Research Centre, Kattankulathur, Tamil Nadu, India, between January 2023 and December 2023. It included 268 children aged 29 days to 5 years admitted with respiratory illness. Demographic, clinical, laboratory and outcome parameters like hospital stay, Oxygen requirement were obtained from medical records. Complete Blood Count (CBC) indices, Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Platelet-To-Neutrophil Ratio (PNR), Lymphocyte multiplied by Platelet (Lym*Plt) and CRP levels were compared between influenza-positive and influenza-negative groups. Data were analysed using Statistical Package for Social Sciences (SPSS) version 26.0. Mann-Whitney U test, Chi-square test and Receiver Operating Characteristic (ROC) curve analysis were applied. A p-value <0.05 was considered statistically significant.
Results: The study showed that the median, Interquartile Range (IQR) age of the participants was 20 months (1 to 60 months). About 161 (60.1%) were male children and 107 (39.9%) were female children. About 100 (37.3%) had influenza A or B infections. About 168 (62.7%) had other associated infections. Median NLR (p-value <0.01) and Absolute Neutrophil Count (ANC) (p-value <0.003) were significantly higher in influenza-positive children compared to influenza-negative children. PNR (p-value <0.04) and lymphocyte count (p-value <0.014) were significantly lower in the influenza-positive group. ROC curve analysis shows that ANC, followed by NLR, PNR, and Lymphocyte, showed better discrimination for Influenza A or B infection.
Conclusion: NLR, ANC, PNR, and lymphocyte counts demonstrated significant correlations with Influenza A and B infections. Infants showed a higher incidence of influenza, with no significant difference between gender. The observed haematological changes showed modest discriminatory ability and may serve as supportive adjunctive markers rather than definitive diagnostic tools. In low-resource settings, accessible parameters may improve diagnostic accuracy, support timely treatment, and enhance outcomes for children with respiratory illnesses.
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