Pre-treatment blood cell counts and inflammatory markers predict the radiologic severity of post-tuberculosis lung disease.

BACKGROUND

Patients with pulmonary tuberculosis (TB) achieve microbiological cures following anti-TB treatment; however, post-tuberculosis lung disease (PTLD) persists in some. This study aimed to evaluate whether pre-treatment blood cell count indicators and inflammatory markers could predict the radiologic severity of PTLD.

METHODS

Overall, 169 patients with pulmonary TB diagnosed at Beijing Chest Hospital were prospectively enrolled. Baseline data were recorded and chest computed tomography (CT) images after the completion of anti-TB treatment were scored from 0 to 24 using a validated system. Patients were classified into mild and severe lung damage groups according to the median value of post-treatment chest CT score. Linear regression and logistic regression analyses were performed to assess the association between baseline inflammatory markers and post-treatment radiologic severity.

RESULTS

The overall mean age was 39.34 ± 15.37 years; 72.8% were men and 49.7% had a smoking history. The median CT score at the treatment end was 9 (interquartile range: 6–15). Significant positive correlations were observed between post-treatment CT scores and baseline erythrocyte sedimentation rate (ESR) (β = 0.040), high-sensitivity C-reactive protein (hs-CRP) (β = 0.030), white blood cell (WBC) count (β = 0.269), neutrophil percentage (β = 0.121) and count (β = 0.330), monocyte count (β = 4.169), and neutrophil-to-lymphocyte ratio (NLR) (β = 0.272). Negative correlations were identified with hemoglobin (Hb) (β = -0.070) and lymphocyte percentage (β = -0.138). Multivariable logistic regression confirmed the predictors.

CONCLUSION

Pre-treatment ESR, hs-CRP, WBC count, Hb, neutrophil percentage and count, lymphocyte percentage, monocyte count and NLR are predictive of post-treatment radiologic severity. These findings highlight the potential for using readily available clinical markers to identify high-risk patients and guide personalized management strategies.