Abstract
OBJECTIVE: Respiratory Tract Infections (RTIs) affect millions globally. This retrospective study evaluates routine hematological parameters for distinguishing bacterial from viral RTIs and develops a novel composite biomarker to enhance diagnostic efficiency, optimize treatment decisions, and improve patient outcomes. METHODS: In the present study, 173 RTI cases (55 bacterial, 118 viral) were enrolled and classified by etiological diagnostic methods (Bacterial culture and identification, or PCR). In addition, 80 healthy controls were also enrolled. Data extraction included SAA, CRP, and blood routine parameters. Biomarkers were assessed individually or in combination using SPSS 26.0 (IBM Corp.) to identify optimal diagnostic models. RESULTS: Predominant pathogens included Gram-negative bacteria (Haemophilus influenzae, Klebsiella pneumoniae) and Gram-positive cocci (Streptococcus pneumoniae) for bacterial infections, and influenza A virus/SARS-CoV-2 for viral infections. Bacterial infections showed significantly elevated median levels versus viral infections, such as White Blood Cell (WBC) count is 8.96 vs. 6.22 × 10(9)/L, Neutrophil (Neu) count is 6.69 vs. 4.55 × 10(9)/L, Monocyte (Mon) count is 0.66 vs. 0.49 × 10(9)/L, C-Reactive Protein (CRP) is 68.89 vs. 20.26 mg/L, Serum Amyloid A (SAA) is 280.75 vs. 81.16 mg/L. The performance analysis of differential diagnosis revealed that SAA is AUC = 0.693 (sensitivity 56.4 %, specificity 84.7 %), CRP is AUC = 0.686 (sensitivity 72.7 %, specificity 67.8 %), and Optimal composite (WBC + Neu + Mon + CRP) is AUC = 0.764 (sensitivity 75.2 %, specificity 89.3 %). CONCLUSION: The combination of biomarkers (WBC + Neu + Mon + CRP) demonstrates moderate ability (AUC = 0.764) in differentiating bacterial from viral RTIs, which plays a vital role in guiding clinical diagnosis and treatment.