A comparative study of volume, scatter, and conductivity parameters of leukocytes in tuberculous and bacterial pneumonias

Background: Differentiating tuberculous from bacterial community-acquired pneumonia (CAP) is challenging due to overlapping clinical features. Cell population data (CPD) from automated hematology analyzers offer a potential point-of-care tool for rapid, cost-effective differentiation based on leukocyte characteristics. Methods: This analytical cross-sectional study was conducted over 12 months (July 2022–June 2023) at a tertiary care center in Uttarakhand, India. Adult patients with clinical and radiological evidence of pneumonia were enrolled after ethical approval and informed consent. Cases were classified as tuberculous or bacterial pneumonia based on sputum microbiology, molecular testing, culture, and treatment response. Hematological parameters, including CPD from the Unicel DxH 800 (Beckman Coulter), were analyzed. Statistical analysis was done using SPSS v22.0. Multiparametric analysis integrated clinical variables, routine haematological indices, and leukocyte VCS parameters. Principal component analysis was used for exploratory dimensionality reduction, followed by multivariable logistic regression with discriminatory performance assessed using receiver operating characteristic analysis. Results: Among 193 patients, 74 had tuberculous and 119 had bacterial pneumonia. Tuberculous cases were younger, predominantly male, and had longer fever and cough. Hematologically, they showed lower hemoglobin, hematocrit, MCV, and MCH, but higher RDW and platelet counts. Eosinopenia and increased monocyte percentages were observed. CPD analysis revealed significant differences in lymphocyte (MN-V-LY, MN-AL2-LY), monocyte (MN-MALS-MO, MN-UMALS-MO, MN-LMALS-MO, MN-LALS-MO, MN-AL2-MO), eosinophil (MN-AL2-EO), and early granular cell (MN-UMALS-EGC, SD-MALS-EGC) parameters. Multivariable logistic regression demonstrated good discriminatory performance for tuberculous pneumonia (sensitivity 78.4%, specificity 75.6%), outperforming individual markers. Principal component analysis showed partial separation between tuberculous and bacterial pneumonia, driven mainly by coordinated changes in monocyte scatter and lymphocyte-related parameters, supporting a multiparametric diagnostic signature rather than a single dominant variable. Conclusion: Tuberculous pneumonia showed distinct hematological and CPD alterations, particularly in monocyte and lymphocyte parameters. These reflect underlying immunological differences but overlap with bacterial patterns limits diagnostic specificity. Monocyte scatter parameters were the most consistently altered in TB cases. Multiparametric analysis suggests that differentiation between tuberculous and bacterial pneumonia arises from coordinated immune-cellular patterns rather than isolated haematological markers. The findings emphasize the dominant contribution of monocyte-related parameters and support the use of integrated diagnostic approaches over single-parameter thresholds.