A comparative study of chest CT findings regarding the effects of regional dust exposure on patients with COPD living in urban areas and rural areas near cement plants

Impact of Smoking and Chronic Obstructive Pulmonary Disease on All-Cause, Respiratory, and Cardio-Cerebrovascular Mortality

Introduction

Mortality differences in chronic obstructive pulmonary disease (COPD) between nonsmokers and smokers remain unclear. We compared the risk of death associated with smoking and COPD on mortality.

Methods

The study included participants aged ≥40 years who visited pulmonary clinics and were categorised into COPD or non-COPD and smoker or nonsmoker on the basis of spirometry results and cigarette consumption. Mortality rates were compared between groups using statistical analysis for all-cause mortality, respiratory disease-related mortality, and cardiocerebrovascular disease-related mortality.

Results

Among 5811 participants, smokers with COPD had a higher risk of all-cause (adjusted hazard ratio (aHR), 1.69; 95% confidence interval (CI), 1.23-2.33) and respiratory disease-related mortality (aHR, 2.14; 95% CI, 1.20-3.79) than nonsmokers with COPD. Non-smokers with and without COPD had comparable risks of all-cause mortality (aHR, 1.39; 95% CI, 0.98-1.97) and respiratory disease-related mortality (aHR, 1.77; 95% CI, 0.85-3.68). However, nonsmokers with COPD had a higher risk of cardiocerebrovascular disease-related mortality than nonsmokers without COPD (aHR, 2.25; 95% CI, 1.15-4.40).

Conclusion

The study found that smokers with COPD had higher risks of all-cause mortality and respiratory disease-related mortality compared to nonsmokers with and without COPD. Meanwhile, nonsmokers with COPD showed comparable risks of all-cause and respiratory mortality but had a higher risk of cardiocerebrovascular disease-related mortality compared to nonsmokers without COPD.

Deep Learning-Based Computed Tomography Features in Evaluating Early Screening and Risk Factors for Chronic Obstructive Pulmonary Disease

This research aimed to investigate the diagnostic effect of computed tomography (CT) images based on a deep learning double residual convolution neural network (DRCNN) model on chronic obstructive pulmonary disease (COPD) and the related risk factors for COPD. The questionnaire survey was conducted among 980 permanent residents aged ≥ 40 years old. Among them, 84 patients who were diagnosed with COPD and volunteered to participate in the experiment and 25 healthy people were selected as the research subjects, and all of them underwent CT imaging scans. At the same time, an image noise reduction model based on the DRCNN was proposed to process CT images. The results showed that 84 of 980 subjects were diagnosed with COPD, and the overall prevalence of COPD in this epidemiological survey was 8.57%. Multivariate logistic regression model analysis showed that the regression coefficients of COPD with age, family history of COPD, and smoking were 0.557, 0.513, and 0.717, respectively (P < 0.05). The diagnostic sensitivity, specificity, and accuracy of DRCNN-based CT for COPD were greatly superior to those of single CT and the difference was considerable (P < 0.05). In summary, advanced age, family history of COPD, and smoking were independent risk factors for COPD. CT based on the DRCNN model can improve the diagnostic accuracy of simple CT images for COPD and has good performance in the early screening of COPD.

Protective effect of total Saponins from American ginseng against cigarette smoke-induced COPD in mice based on integrated metabolomics and network pharmacology

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease. Aiming at assessing the effect of total saponins from American ginseng on COPD, both the chemical composition and anti-COPD activity of total saponins from wild-simulated American ginseng (TSW) and field-grown American ginseng (TSF) were investigated in this study. Firstly, a HPLC-ELSD chromatographic method was established to simultaneously determine the contents of 22 saponins in TSW and TSF. Secondly, CS-induced COPD mouse model was established to evaluate the activity of TSW and TSF. The results indicated that both TSW and TSF had the protective effect against COPD by alleviating oxidative stress and inflammatory response. TSW showed a stronger effect than TSF. Thirdly, an integrated approach involving metabolomics and network pharmacology was used to construct the "biomarker-reaction-enzyme-target" correlation network aiming at further exploring the observed effects. As the results, 15 biomarkers, 9 targets and 5 pathways were identified to play vital roles in the treatment of TSW and TSF on COPD. Fourthly, based on network pharmacology and the CS-stimulated A549 cell model, ginsenoside Rgl, Rc, oleanolic acid, notoginsenoside R1, Fe, silphioside B were certified to be the material basis for the stronger effect of TSW than TSF. Finally, the molecular docking were performed to visualize the binding modes. Our findings suggested that both TSW and TSF could effectively ameliorate the progression of COPD and might be used for the treatment of COPD.