Cell population data in identifying active tuberculosis and community-acquired pneumonia

Abstract

Objective Leukocyte morphological parameters known as CPD (cell population data) is detected by hematology analyzer UniCel DxH800 with VCS technology. This study aimed to investigate the diagnostic efficacy of morphological changes in CPD parameters in distinguishing active tuberculosis from community-acquired pneumonia. Methods From October 2018 to February 2019, 88 patients with active tuberculosis, 78 patients with community-acquired pneumonia, and 89 healthy controls were enrolled in this study. CPD was obtained using Unicel DxH800 analyzer for all whole blood samples, one-way ANOVA (non-parametric) and area analysis under ROC curve were performed. Results The neutrophil mean conductivity (NMC), monocyte mean volume (MMV), monocyte mean conductivity (MMC), lymphocyte percentage (LY%), and monocyte percentage (MO%) were significantly higher in the active tuberculosis group than in the community-acquired pneumonia group. The white blood cell (WBC) count and neutrophil percentage (NE%) were significantly lower in the active tuberculosis group than in the community-acquired pneumonia group. The analysis of the area under the ROC curve proved that WBC count, neutrophil percentage (NE%), lymphocyte percentage (LY%), and monocyte percentage (MO%) did not achieve a higher area under the curve (AUC: 0.63, 0.71, 0.62, and 0.7, respectively). However, the AUC of NMC, MMV, and MMC in the CPD parameters was 0.951, 0.877, 0.98, respectively, and the simultaneous measurement of the three parameters was 0.99. The sensitivity and specificity were 98.5% and 91.1%, respectively. Conclusion The combined diagnosis of NMC, MMV, and MMC could assist the clinical diagnosis of active tuberculosis and community-acquired pneumonia.

Development and validation of a 3D-convolutional neural network model based on chest CT for differentiating active pulmonary tuberculosis from community-acquired pneumonia

“…The final model (risk factors including night sweats, hemoptysis, weight loss, tuberculosis exposure and upper lobe infiltrate) obtained an AUC of 0.89 (95%CI: 0.85—0.93), which was a better prediction model for pulmonary tuberculosis based on clinical information at present. In laboratory studies, Sun et al [ 22 ] used multiple parameters of cell population data used to characterize white blood cells morphology to identify APTB and CAP. Their results showed that neutrophil mean conductivity, monocyte mean volume and monocyte mean conductivity had high discrimination ability in identifying the two diseases, and AUC could reach 0.99 when used in combination.…”

Blood cell markers and acute phase reactants as a strategy to differentiate between pulmonary tuberculosis and community-acquired pneumonia: a retrospective cohort study

“…Currently, multiple tools are available for the accurate diagnosis of PT or CAP [8][9][10] , however, the availability of these techniques in many places may be limited. The assessment of cell counts and the relationships between different types of blood cells has been proposed to provide useful and easily accessible information for distinguishing between these two conditions 9,11 . An elevated monocyte/lymphocyte ratio (MLR) has been suggested as an indicative marker of tuberculosis, while a low value may indicate bacterial pneumonia 12,13 .…”