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Purpose: To analyze the time trends in the notification rates of registered tuberculosis (TB) and bacteriologically confirmed TB in Shandong Province. And analyze the changes in TB treatment outcomes during 2005-2021. Patients and Methods: The information of TB patients registered in the Shandong Information Center for Disease Control and Prevention (CDC) was collected during 2005-2021. We calculated the notification rates of registered TB and bacteriologically confirmed TB. Moreover, we calculated the year-to-year change rate of TB in treatment outcomes before and after COVID-19. The time trends were analyzed using the joinpoint regression method and illustrated as the annual percentage change (APC) of notification rates. Results: A total of 236,898 cases of TB were diagnosed during 2005-2021, of which 51.11% were bacteriologically confirmed cases. Since 2008, the notification rates of registered TB have declined. The notification rates of bacteriologically confirmed TB had been declining during 2005-2016, then remained stable after 2016. In subgroup, the notification rates of both registered TB and bacteriologically confirmed TB were higher among men, rural residents, and people aged ≥ 60 years. Compared with clinically confirmed TB, bacteriologically confirmed TB has shown higher rates of poor outcomes since 2008 and higher case fatality rate since 2005. The rate of poor outcomes remained stable during 2008-2019. However, after the COVID-19 outbreak, the rate of poor outcomes and case fatality rate of TB has risen significantly. Conclusion: After unremitting efforts to fight against TB, the notification rates of registered TB and bacteriologically confirmed TB declined in Shandong Province. The rate of poor outcomes remained stable during 2008-2019, then rise significantly after the COVID-19 outbreak. In the context of the long-term existence of COVID-19, further efforts should be made in TB diagnosis and treatment among high-risk population, especially with regard to males, rural residents and older adults.
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Growing evidence has found the health protective effects of greenness exposure on tuberculosis (TB) and the impact of ambient air pollutants on TB drug-resistance. However, it remains unclear whether residential greenness is also beneficial to reduce TB drug-resistance, and whether air pollution modify the greenness-TB resistance relationship. We enrolled 5006 newly-diagnosed TB patients from Shandong, China, during 2014 to 2021. Normalized Difference Vegetation Index (NDVI) in 250 m and 500 m buffer around individuals' residential zone was used to assess greenness exposure. All patients were divided by quartiles of NDVI250-m and NDVI500-m (from low to high: Q1, Q2, Q3, Q4) respectively. Six logistic regression models (NDVI, NDVI + PM2.5/PM10/SO2/NO2/O3) were used to estimate the association of NDVI and TB drug-resistance when adjusting different air pollutants or not. All models were adjusted for age, gender, body mass index, complications, smoking, drinking, population density, nighttime light index, road density. Compared with participants in NDVI250-m Q1 and NDVI500-m Q1, other groups had lower rates of MDR-TB, PDR-TB, RFP-resistance, SM-resistance, RFP + SM resistance, INH + RFP + EMB + SM resistance. NDVI500-m reduced the risk of multidrug resistant tuberculosis (MDR-TB) and the adjusted odds ratio (aOR, 95% confidence interval, CI) compared with NDVI500-m Q1 were 0.736 (0.547-0.991) in NDVI + PM10 model, 0.733 (0.544-0.986) in NDVI + PM2.5 model, 0.735(0.546-0.99) in NDVI + SO2 model, 0.736 (0.546-0.991) in NDVI + NO2 model, respectively, P < 0.05. NDVI500-m contributed to a decreased risk of streptomycin (SM)-resistance. The aOR of rifampicin (RFP) + SM resistance were 0.132 (NDVI250-m, Q4 vs Q1, 95% CI: 0.03-0.578), 0.199 (NDVI500-m, Q3 vs. Q1, 95% CI: 0.057-0.688) and 0.264 (NDVI500-m, Q4 vs. Q1, 95% CI: 0.087-0.799). The adjusted ORs (Q2 vs. Q1, 95% CI) of isoniazid (INH) + RFP + ethambutol (EMB) + SM resistance in 500 m buffer were 0.276 (0.119-0.639) in NDVI model, 0.279 (0.11-0.705) in NDVI + PM10 model, 0.281 (0.111-0.713) in NDVI + PM2.5 model, 0.279 (0.11-0.709) in NDVI + SO2 model, 0.296 (0.117-0.754) in NDVI + NO2 model, 0.294 (0.116-0.748) in NDVI + O3 model, respectively. The study showed, for the first time, that residential greenness exposure in 500 m buffer is beneficial for reducing newly-diagnosed DR-TB (including PDR-RB, MDR-TB, MR-TB), and ambient air pollutants may partially mediate this association.
Assuntos
Poluentes Atmosféricos , Poluição do Ar , Exposição Ambiental , Tuberculose Resistente a Múltiplos Medicamentos , Humanos , China , Masculino , Feminino , Adulto , Pessoa de Meia-IdadeRESUMO
Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.