Analysis of influencing factors and construction of prediction model for multidrug-resistant tuberculosis in Nanning area.

OBJECTIVE: This study aims to analyze the characteristics of multidrug-resistantisolates and to identify the factors influencing multidrug resistance in the Nanning area.

METHODS: This study retrospectively analyzed all sputum specimens from pulmonary tuberculosis patients collected at the Fourth People's Hospital of Nanning from January 2021 to June 2022, including a total of 337 strains of. Univariate analysis and binary logistics regression analysis were used to identify factors influencing multidrug resistance. A predictive model was constructed with SPSS software, and the predictive value of the model was evaluated with the Receiver Operating Characteristic (ROC) curve.

RESULTS: The results of binary logistics regression analysis indicated that treatment status and high-risk population were independent factors influencing multidrug resistance (<&#x202f;0.05). According to the logistics regression analysis results, the model was constructed as follows: Logit(P)&#x202f;=&#x202f;-1.874&#x202f;+&#x202f;(1.187X)&#x202f;+&#x202f;(0.837X). ROC analysis showed that the area under the curve (AUC) of the model was 0.936. In the validation group, the AUC was 0.853.

CONCLUSION: This study results provide a basis for precise prevention and control of multidrug-resistant tuberculosis bacteria in Nanning, help reduce the risk of transmission, and ensure public health safety of local and surrounding populations.