Abstract:

Objective: To analyze the clinical features of pulmonary tuberculosis and pulmonary sarcoidosis complicated with granulomatous inflammation of pulmonary tissue, in order to build a differential diagnostic model of the two groups. Methods: A retrospective study was conducted in 121 patients with pulmonary granulomatosis diagnosed by bronchoscopic lung tissue biopsy in the First Affiliated Hospital of Soochow University from January 2016 to December 2022. Among them, there were 34 cases of pulmonary sarcoidosis and 87 cases of tuberculosis. Demographic data, clinical symptoms, chest CT imaging data, histopathology, bronchoscopic data were collected, and the independent predictors of the two groups were screened out by logistic regression analysis. Finally, established the disease diagnosis model, and evaluated the differential diagnosis efficiency of the model. Results: Logistic regression analysis showed that male (OR=5.51, 95%CI: 1.67-18.17), nodule diameter ranged from 1 cm to 3 cm (OR=5.82, 95%CI: 1.47-23.08), segmental bronchial stenosis (OR=6.43, 95%CI: 1.59-25.92), bilateral lung involvement (OR=0.03, 95%CI: 0.00-0.16) were independent predictors of tuberculosis and pulmonary sarcoidosis. Accordingly, the disease diagnosis model was established with the AUC of 0.884 (95%CI: 0.819-0.949). The specificity was 79.4%, and the sensitivity was 86.2%. Conclusion: There are differences in patient gender, lung lesion size, morphology, and other aspects between pulmonary tuberculosis and pulmonary sarcoidosis with granulomatous inflammation of lung tissue. The diagnostic model can be better used for the differential diagnosis of the two groups.

Key words: Sarcoidosis, pulmonary, Tuberculosis, pulmonary, Granuloma, Diagnosis, differential, Models, statistical