Objective. To compare the clinical efficacy and adverse drug reactions of four different schemes in the treatment of pleural tuberculoma. Methods. A total of 120 patients with pleural tuberculoma admitted to the Tuberculosis Department of our hospital from January 2018 to January 2021 were selected as the research subjects. According to different treatment methods, the patients were divided into four groups, with 30 cases in each group. They were as follows: group A received classical HRZE regimen, group B received HRZE+pleural injection, group C received HZE+rifabutin, and group D received HZE+rifabutin+pleural injection. All patients were treated intensively for 3 months and then consolidated treatment for 6 months according to the patient’s condition. The absorption of lesions in the four groups at different time was compared, and the occurrences of adverse drug reactions and treatment outcomes during treatment were recorded. Results. After 3 months of treatment, compared with groups A, B, and C, the number of significantly absorbed cases and effective cases in group D increased, while the number of invalid cases decreased. However, there was no statistical significance in the absorption of lesions between the four groups ( χ 2 = 8.272 , P = 0.507 ). In addition, pairwise comparison showed no significant difference in the absorption of lesions ( P > 0.05 ). After 9 months of treatment, there was no significant difference in the absorption of lesions among the four groups ( χ 2 = 8.795 , P = 0.185 ), but the absorption of lesions in group D was significantly better than that in group A ( P < 0.05 ). During treatment, the incidence of adverse reactions in the four groups was significantly different ( χ 2 = 8.779 , P = 0.032 ). Pairwise comparison showed that the incidence of adverse reactions in groups C and D was significantly lower than that in group A ( P < 0.05 ). The total treatment course of group A was 9-16 months, and 10 cases (33.33%) still had residual lesions or pleural thickening at the end of treatment. The total course of treatment in group B was 9-12 months, and 7 cases (23.33%) still had residual lesions or pleural thickening at the end of the course of treatment. The total treatment course of group C was 9-16 months, and 8 cases (26.67%) still had residual lesions or pleural thickening at the end of treatment. The total course of treatment in group D was 9-12months, and there were still 2 cases of residual lesions (6.67%) at the end of the course. Conclusions. HZE+rifabutin+pleural injection against tuberculosis therapy has a significant clinical efficacy in the treatment of pleural tuberculoma, which can more effectively improve the clinical symptoms of patients, improve the efficacy, and reduce complications, with a good prognosis, worthy of clinical promotion.
Background: Nontuberculous mycobacteria (NTM) grows slowly, the course of disease is longer than that of tuberculosis (TB), and the resistance rate to first-line anti tuberculosis drugs is high, so the overall cure rate is low. Radiomics is a new image processing technology developed in recent years. In this study, CT-based radiomics features are evaluated to differentiatenon NTM pulmonary disease with consolidation characteristics from PTB with similar consolidation characteristics. Methods: A total of 156 patients (75 NTM pulmonary disease and 81 PTB) with the Consolidation were evaluated. 305 regions of interest of CT consolidation were outlined. 80% of consolidations were allocated to the training set and 20% to the validation set using a random number generated by a computer. Three supervised learning classifiers (KNN, SVM and LR models) were used to analyze the features. Results: 63 optimal features were selected by these three methods. The AUC (sensitivity, specificity) for the training and validation cohorts were 0.98 (0.90, 0.94) and 0.97 (0.87, 0.97) for KNN, respectively; 0.99 (0.94, 0.93) and 0.96 (0.80, 0.97) for SVM, respectively; and 0.98 (0.96, 0.97) and 0.95 (0.88, 0.87) for LR, respectively. Precision, Recall and F1-scores determined that KNN performed better at diagnosing early NTM pulmonary disease, with the values of the above three indexes being 0.89 and 0.97 and 0.93, respectively.Conclusion: CT-based radiomics analysis consolidation features can provide effective proof in distinguishing the NTM pulmonary disease from PTB.Among the three classifiers, KNN classifier has the best performance in identifying two diseases.
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