The Incidence, Risk Factors, and Predictive Model of Obstructive Disease in Post-Tuberculosis Patients

Abstract

Wenjun Chang,1 Zheng Li,2 Qianqian Liang,1 Wei Zhao,1 Fengsen Li2 1Department of Fourth Clinical College, Xinjiang Medical University, Urumqi, 830054, People’s Republic of China; 2Department of Respiratory, Unit Xinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine, Urumqi, 830000, People’s Republic of ChinaCorrespondence: Fengsen Li, Department of Respiratory, Unit Xinjiang Uygur Autonomous Region Hospital of Traditional Chinese Medicine, No. 119, Huang He Road, Urumqi, 830000, People’s Republic of China, Tel [phone], Email [email protected]: To assess the incidence and risk factors of tuberculosis-associated obstructive pulmonary disease (TOPD) in individuals with treatment-naive pulmonary tuberculosis (PTB) and develop a predictive model to enhance its management.Methods: The incidence of TOPD among patients with treatment-naive PTB in Xinjiang, China, was followed up for one year. Patient characteristics, such as demographics, medical histories, laboratory test results, lung radiological evidence, and pulmonary function, were collected upon hospital admission and throughout follow-up visits. Risk factors associated with TOPD were evaluated by multivariate logistic regression analysis, and then a predictive model was established using LASSO regression.Results: Of the 159 included patients, 69 (43.4%) developed TOPD during the follow-up period. Multivariate regression analysis identified age, body mass index, ESR, and symptom duration as significant risk factors. Subsequently, a model formula was derived from these factors to predict TOPD. Utilizing a cut-off value of 0.435, the model demonstrated a sensitivity of 89% and a specificity of 83%.Conclusion: In Xinjiang, the prevalence of TOPD appears notably high among treatment-naive PTB patients. Our findings, such as the risk factors and predictive model, may facilitate the early detection and improved interventions for TOPD among patients with PTB, potentially leading to better patient outcomes.Keywords: tuberculosis, tuberculosis-associated obstructive pulmonary disease, risk factor, predictive model, diagnosis

Keywords

• tuberculosis
• tuberculosis-associated obstructive pulmonary disease
• risk factor
• predictive model
• diagnosis