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. 2024 Sep 27;24(1):1058.
doi: 10.1186/s12879-024-09976-9.

Epidemiological characteristics, diagnosis and treatment effect of rifampicin-resistant pulmonary tuberculosis (RR-PTB) in Guizhou Province

Affiliations

Epidemiological characteristics, diagnosis and treatment effect of rifampicin-resistant pulmonary tuberculosis (RR-PTB) in Guizhou Province

Jian Zhou et al. BMC Infect Dis. .

Abstract

Background: Rifampicin-resistant pulmonary tuberculosis (RR-PTB) presents a significant threat to global public health security. China bears a substantial burden of RR-PTB cases globally, with Guizhou Province experiencing particularly alarming trends, marked by a continual increase in patient numbers. Understanding the population characteristics and treatment modalities for RR-PTB is crucial for mitigating morbidity and mortality associated with this disease.

Methods: We gathered epidemiological, diagnostic, and treatment data of all RR-PTB cases recorded in Guizhou Province from January 1, 2017 to December 31, 2023. Utilizing composition ratios as the analytical metric, we employed Chi-square tests to examine the spatiotemporal distribution patterns of RR-PTB patients and the evolving trends among different patient classifications over the study period.

Results: In our study, 3396 cases of RR-PTB were analyzed, with an average age of 45 years. The number of RR-PTB patients rose significantly from 176 in 2017 to 960 in 2023, peaking notably among individuals aged 23-28 and 44-54, with a rising proportion in the 51-80 age group (P < 0.001). Since 2021, there has been a notable increase in the proportion of female patients. While individuals of Han ethnic group comprised the largest group, their proportion decreased over time (P < 0.001). Conversely, the Miao ethnicity showed an increasing trend (P < 0.05). The majority of patients were farmers, with their proportion showing an upward trajectory (P < 0.001), while students represented 4.33% of the cases. Geographically, most patients were registered in Guiyang and Zunyi, with a declining trend (P < 0.001), yet household addresses primarily clustered in Bijie, Tongren, and Zunyi. The proportion of floating population patients gradually decreased, alongside an increase in newly treated patients and those without prior anti-tuberculosis therapy. Additionally, there was a notable rise in molecular biological diagnostic drug sensitivity (real-time PCR and melting curve analysis) (P < 0.001). However, the cure rate declined, coupled with an increasing proportion of RR-PTB patients lost to follow-up and untreated (P < 0.05).

Conclusions: Enhanced surveillance is crucial for detecting tuberculosis patients aged 23-28 and 44-54 years. The distribution of cases varies among nationalities and occupations, potentially influenced by cultural and environmental factors. Regional patterns in RR-PTB incidence suggest tailored prevention and control strategies are necessary. Despite molecular tests advances, challenges persist with low cure rates and high loss to follow-up. Strengthening long-term management, resource allocation, and social support systems for RR-PTB patients is essential.

Keywords: Diagnosis and treatment; Epidemiology; Rifampicin-resistant pulmonary tuberculosis; Spatio-temporal distribution; Western China.

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Conflict of interest statement

The authors declare no competing interests.

All the authors declared that there was no conflict of interest in the study.

Figures

Fig. 1
Fig. 1
Gender and age distribution of RR-PTB patients. (A) Number of male and female patients, (B) Proportion of male and female patients, (C) Age count, (D) Age group. * indicates that the composition ratio is decreasing and the difference is statistically significant, # indicates that the composition ratio is increasing and the difference is statistically significant
Fig. 2
Fig. 2
Ethnic groups and occupational distribution of RR-PTB patients. (A) Ethnic group, (B) Other minorities, (C) Occupation, (D) Other occupation. * indicates that the composition ratio is decreasing and the difference is statistically significant, # indicates that the composition ratio is increasing and the difference is statistically significant
Fig. 3
Fig. 3
Spatial and temporal distribution of RR-PTB patients. (A) Hotspot map registered address, (B) Proportion of registered address, (C) Hotspot map of household address, (D) Proportion of household address. * indicates that the composition ratio is decreasing and the difference is statistically significant, # indicates that the composition ratio is increasing and the difference is statistically significant
Fig. 4
Fig. 4
Population mobility of RR-PTB patients. (A) Population mobility, (B) Classification of floating population
Fig. 5
Fig. 5
Diagnosis and treatment characteristics of RR-PTB patients. (A) Treatment classification, (B) Treatment history, (C) Drug sensitivity test methods, (D) Treatment outcomes. * indicates that the composition ratio is decreasing and the difference is statistically significant, # indicates that the composition ratio is increasing and the difference is statistically significant

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