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Chinese Journal of Antituberculosis ›› 2024, Vol. 46 ›› Issue (12): 1459-1468.doi: 10.19982/j.issn.1000-6621.20240326

• Original Articles • Previous Articles     Next Articles

Analysis of characteristics and factors influencing treatment outcome of registered tuberculosis patients in Linping District, Hangzhou City from 2013 to 2022

Chen Liyan1, Zhang Xiaoqiang2, Yu Jianping2, Zheng Xiao2, Zhang Yu3()   

  1. 1Department of Otolaryngology, The First People’s Hospital of Linping District, Zhejiang Province, Hangzhou 311100, China
    2Department of Infection, The First People’s Hospital of Linping District, Zhejiang Province, Hangzhou 311100, China
    3Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
  • Received:2024-08-07 Online:2024-12-10 Published:2024-12-03
  • Contact: Zhang Yu, Email: yzhang@cdc.zj.cn
  • Supported by:
    Zhejiang Province Medicine and Health Science and Technology Program(2024KY902);Zhejiang Province Traditional Chinese Medicine Science and Technology Program Project(2024ZL840);Hangzhou Health Science and Technology Program(B20232013)

Abstract:

Objective: This study aims to analyze the characteristics of pulmonary tuberculosis patients diagnosed and treated in county-level (district-level) designated tuberculosis hospitals in Hangzhou, and to identify factors influencing treatment outcomes. Methods: Data for pulmonary tuberculosis patients diagnosed and treated in Linping District, Hangzhou City from 2013 to 2022 were extracted from the “Tuberculosis Management Information System” subsystem within the “China Disease Prevention and Control Information System,” based on the area of initial diagnosis. A total of 1999 patients were included in this analysis. Patient data on sociodemographic characteristics, diagnostic and treatment information, and treatment outcomes were collected and analyzed. Univariate and multivariate logistic regression models were applied to identify factors influencing adverse treatment outcomes, with further subgroup analyses conducted. Results: Of the 1999 patients, 52.58% (1051/1999) tested positive for pathogens, 41.47% (829/1999) were pathogen-negative, and 5.95% (119/1999) had no pathogen results. Initial treatment was administered to 91.80% (1835/1999) of patients, while 8.20% (164/1999) underwent retreatment. A standard treatment protocol was used for 43.62% (872/1999) of patients, and 31.37% (627/1999) received fixed-dose combination therapy. Additionally, 8.75% (175/1999) of patients had comorbidities other than tuberculosis, and 12.16% (243/1999) had concurrent tuberculosis infections. Treatment success was achieved in 93.00% (1859/1999) of patients, while 7.00% (140/1999) experienced adverse outcomes. Multivariate analysis revealed that tuberculosis patients aged 65 and older, those undergoing retreatment, patients with positive pathogen test results, and those with additional comorbidities had an elevated risk of adverse treatment outcomes (OR(95%CI): 2.320 (1.402-3.838), 4.527 (2.803-7.310), 3.419 (2.073-5.638), and 2.132 (1.275-3.567), respectively). Conversely, female patients and those with non-pathogenic tuberculosis exhibited a reduced risk of adverse outcomes (OR (95%CI): 0.486 (0.293-0.808) and 0.323 (0.116-0.904), respectively). The impact of the treatment regimen on outcomes was found to correlate with age (interaction P=0.002) and to interact with sputum smear results at the end of the second month of treatment (interaction P=0.046). For younger patients (<35 years), the standard treatment regimen was more effective (OR (95%CI): 0.170 (0.059-0.493)), whereas individualized treatment plans yielded poorer outcomes for patients with low treatment adherence (those lacking a sputum smear test at the two-month mark)(OR (95%CI): 0.253 (0.132-0.485)). Conclusion: Treatment outcomes in pulmonary tuberculosis patients are influenced by factors such as age, treatment history, bacteriological findings, and comorbid conditions. Tailored treatment strategies should be implemented based on individual patient characteristics to enhance treatment success rates.

Key words: Tuberculosis, pulmonary, Treatment outcome, Risk factors, Factor analysis, statistical

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