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-resistant Mycobacterium tuberculosis isolates 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 Mycobacterium tuberculosis. 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 (p < 0.05). According to the logistics regression analysis results, the model was constructed as follows: Logit(P) = -1.874 + (1.187X1) + (0.837X2). 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.