Objective To identify the composition of comorbidities among patients with newly diagnosed pulmonary tuberculosis and assess the impact of comorbidities on the clinical characteristics of patients. Methods This study was conducted in 13 hospitals across 13 counties in Zhejiang province, China. Patient data collected in this study included demographic characteristics, chest radiography results, etiological results, and comorbidities. Descriptive statistics were conducted to describe the composition of comorbidities of all participants. Univariate and multivariate logistic regression analyzes were performed to identify the effects of comorbidities on the clinical features of the participants. Results Of the 8,421 total participants, 27.6% reported cavities in the chest radiography results, 41.9% were Mycobacterium tuberculosis -positive in the etiology test results, and 38.7% (3,258/8,421) had at least one type of comorbidity. The most predominant comorbidity was pleuritis (1,833, 21.8%), followed by diabetes mellitus (763, 9.1%), other extrapulmonary tuberculosis (421, 5%), tracheobronchial tuberculosis (275, 3.3%), and silicosis (160, 1.9%). Participants with diabetes mellitus had the highest rate of chest cavities on X-ray (54.8%), followed by those with silicosis (33.1%). In addition, a higher percentage of the M. tuberculosis -positive etiology (45%) was observed in participants without comorbidities than in participants with comorbidities (37.1%). Compared to patients without comorbidities, patients with diabetes mellitus (adjusted odds ratio [AOR]: 2.88, 95% confidence interval [CI]: 2.42–3.43) were more likely to show cavities in chest X-ray, while patients with pleuritis (AOR: 0.27, 95% CI: 0.23–0.32), other extrapulmonary tuberculosis (AOR: 0.48, 95% CI: 0.36–0.64), and tracheobronchial tuberculosis (AOR: 0.40–0.79) were less likely to show chest cavities in X-ray. In addition, patients with diabetes mellitus (AOR: 2.05, 95% CI: 1.72–2.45), tracheobronchial tuberculosis (AOR: 3.22, 95% CI: 2.4–4.32) were more likely to show Mycobacterium tuberculosis -positive in the etiology, and patients with pleuritis (AOR: 0.25, 95% CI: 0.22–0.29), other extrapulmonary tuberculosis (AOR: 0.61, 95% CI: 0.48–0.76) were less likely to show Mycobacterium tuberculosis -positive in the etiology. Conclusion The prevalence of comorbidities was high in patients newly diagnosed with pulmonary tuberculosis. Thus, integration of screening and personalized management is needed for the control of tuberculosis and its comorbidities.
Background With a progressive increase in the aging process, the challenges posed by pulmonary tuberculosis (PTB) are also increasing for the elderly population. Objective This study aimed to identify the epidemiological distribution of PTB among the elderly, forecast the achievement of the World Health Organization’s 2025 goal in this specific group, and predict further advancement of PTB in the eastern area of China. Methods All notified active PTB cases aged ≥65 years from Zhejiang Province were screened and analyzed. The general epidemiological characteristics were depicted and presented using the ArcGIS software. Further prediction of PTB was performed using R and SPSS software programs. Results Altogether 41,431 cases aged ≥65 years were identified by the surveillance system from 2015 to 2020. After excluding extrapulmonary TB cases, we identified 39,832 PTB cases, including laboratory-confirmed (23,664, 59.41%) and clinically diagnosed (16,168, 40.59%) PTB. The notified PTB incidence indicated an evident downward trend with a reduction of 30%; however, the incidence of bacteriologically positive cases was steady at approximately 60/100,000. Based on the geographical distribution, Quzhou and Jinhua Cities had a higher PTB incidence among the elderly. The delay in PTB diagnosis was identified, and a significantly prolonged treatment course was observed in the elderly. Moreover, a 50% reduction of PTB incidence by the middle of 2024 was predicted using a linear regression model. It was found that using the exponential smoothing model would be better to predict the PTB trend in the elderly than a seasonal autoregressive integrated moving average model. Conclusions More comprehensive and effective interventions such as active PTB screening combined with physical checkup and succinct health education should be implemented and strengthened in the elderly. A more systematic assessment of the PTB epidemic trend in the elderly population should be considered to incorporate more predictive factors.
To understand and analyze the factors relating to patient and diagnostic delays among groups with tuberculous pleurisy (TP), and its spatiotemporal distribution in Zhejiang Province.
Tuberculous pleurisy (TP) presents a serious allergic reaction in the pleura caused by Mycobacterium tuberculosis; however, few studies have described its spatial epidemiological characteristics in eastern China.This study aimed to determine the epidemiological distribution of TP and predict its further development in Zhejiang Province.Data on all notified cases of TP in Zhejiang Province, China, from 2017 to 2021 were collected from the existing tuberculosis information management system. Analyses, including spatial autocorrelation and spatial-temporal scan analysis, were performed to identify hot spots and clusters, respectively. The prediction of TP prevalence was performed using the seasonal autoregressive integrated moving average (SARIMA), Holt-Winters exponential smoothing, and Prophet models using R (The R Foundation) and Python (Python Software Foundation).The average notification rate of TP in Zhejiang Province was 7.06 cases per 100,000 population, peaking in the summer. The male-to-female ratio was 2.18:1. In terms of geographical distribution, clusters of cases were observed in the western part of Zhejiang Province, including parts of Hangzhou, Quzhou, Jinhua, Lishui, Wenzhou, and Taizhou city. Spatial-temporal analysis identified 1 most likely cluster and 4 secondary clusters. The Holt-Winters model outperformed the SARIMA and Prophet models in predicting the trend in TP prevalence.The western region of Zhejiang Province had the highest risk of TP. Comprehensive interventions, such as chest x-ray screening and symptom screening, should be reinforced to improve early identification. Additionally, a more systematic assessment of the prevalence trend of TP should include more predictors.
The spatial delays of pulmonary tuberculosis (PTB) have been less explored. In this study, a total of 151,799 notified PTB cases were included, with median patient and diagnostic delays of 15 [interquartile range (IOR), 4–35] and 2 (IOR, 0–8) days, respectively. The spatial autocorrelation analysis and spatial–temporal scan statistics were used to determine the clusters, indicating that the regions in the southwestern and northeastern parts of Zhejiang Province exhibited high rates of long-term patient delay (LPD, delay ≥ 15 days) and long-term diagnostic delay (LDD, delay ≥ 2 days). Besides, the Mantel test indicated a moderately positive correlation between public awareness of suspicious symptoms and the LPD rate in 2018 (Mantel's r = 0.4, P < 0.05). These findings suggest that PTB delays can reveal deficiencies in public health education and the healthcare system. Also, it is essential to explore methods to shift PTB knowledge towards real changes in attitude and behavior to minimize patient delay. Addressing these issues will be crucial for improving public health outcomes related to PTB in Zhejiang Province.
Up to now, tuberculosis (TB) remains a global public health problem, posing a serious threat to human health. Traditional methods for analyzing time-varying trends, such as age and period, tend to ignore the poor impact of birth cohorts, which is an important factor in the development of TB. The age-period-cohort (APC) model, a statistical method widely used in recent decades in economics, sociology, and epidemiology, can quantitatively estimate the efficacy of different age, period, and birth cohort groups for TB by separating the effects of these three dimensions and controlling for confounding factors among the time variables. The purpose of this paper is to briefly review the model, focus on the application of the existing APC model in the field of TB, and explain its advantages and disadvantages. This study will help to provides a theoretical basis and reference for using the APC model in TB analysis and prediction.
Employing spirophenanthrenes and phenanthrenone as template arenes for annulative π-extension (APEX), we synthesized a series of spiro-fused dibenzo[g,p]chrysenes (DBCs) in high yields. Experimental and theoretical investigations highlight the distinct advantages...
Tuberculosis remains a major public health challenge worldwide. This study aimed to determine the long-term trends in the notification rate of tuberculosis in Zhejiang Province, and to assess the potential independent risks associated with age, time period, and birth cohort. Data on all pulmonary tuberculosis (PTB) cases in Zhejiang Province from 2008 to 2022 were collected from the Tuberculosis Information Management System. Long-term trends in the notification rate and independent risks associated with quantitatively decomposed variables were determined using joinpoint regression model and age-period-cohort model. Between 2008 and 2022, a total of 323,745 PTB cases were notified in Zhejiang Province. Overall, the notification rate declined, with notable turning points in 2010 and 2019. Net drift analysis revealed an average annual decrease of 5.7% (95% CI: -6.8%, -4.6%; P < 0.01), with faster declines among males than females. Age effects showed peaks in notification rates among people aged 15–29 and 65–74. Period effects peaked during 2008–2012 (RR = 1.4; 95% CI: 1.3, 1.5; P < 0.01). Cohort effects indicated decreasing risks in later birth cohorts, with the highest risk observed in the 1928–1932 birth cohort (RR = 11.0, 95% CI: 7.2, 16.8; P < 0.01) and relative protective effects in cohorts born after 1978–1982. Notification rates of PTB declined consistently across various age groups in Zhejiang Province. Young individuals aged 15–29 and older individuals aged 65–74 were identified as high-risk groups requiring active intervention. Additionally, pre-1978 birth cohorts had a relatively higher risk of PTB. These findings provided valuable insights into the age, period, and birth cohort characteristics of patients with PTB in Zhejiang Province, aiding relevant authorities in formulating appropriate policies and implementing targeted preventive control measures.
BACKGROUND Tuberculous pleurisy (TP) presents a serious allergic reaction in the pleura caused by <i>Mycobacterium tuberculosis</i>; however, few studies have described its spatial epidemiological characteristics in eastern China. OBJECTIVE This study aimed to determine the epidemiological distribution of TP and predict its further development in Zhejiang Province. METHODS Data on all notified cases of TP in Zhejiang Province, China, from 2017 to 2021 were collected from the existing tuberculosis information management system. Analyses, including spatial autocorrelation and spatial-temporal scan analysis, were performed to identify hot spots and clusters, respectively. The prediction of TP prevalence was performed using the seasonal autoregressive integrated moving average (SARIMA), Holt-Winters exponential smoothing, and Prophet models using R (The R Foundation) and Python (Python Software Foundation). RESULTS The average notification rate of TP in Zhejiang Province was 7.06 cases per 100,000 population, peaking in the summer. The male-to-female ratio was 2.18:1. In terms of geographical distribution, clusters of cases were observed in the western part of Zhejiang Province, including parts of Hangzhou, Quzhou, Jinhua, Lishui, Wenzhou, and Taizhou city. Spatial-temporal analysis identified 1 most likely cluster and 4 secondary clusters. The Holt-Winters model outperformed the SARIMA and Prophet models in predicting the trend in TP prevalence. CONCLUSIONS The western region of Zhejiang Province had the highest risk of TP. Comprehensive interventions, such as chest x-ray screening and symptom screening, should be reinforced to improve early identification. Additionally, a more systematic assessment of the prevalence trend of TP should include more predictors.
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