Objective The purpose of this study was to explore the correlation between peripheral blood eosinophil (EOS) count and smoking history, some inflammatory indicators, lung function, efficacy of ICS, risk of respiratory failure and chronic pulmonary heart disease, risk of acute exacerbation within 1 year, readmission rate and mortality in patients with acute exacerbation of COPD. Methods Retrospective analysis of the baseline clinical data of 816 patients with acute exacerbation of chronic obstructive pulmonary disease in the Department of Respiratory and Critical Care Medicine of the First Affiliated Hospital of Shihezi University from January 1,2019 to December 31,2021. The patients were divided into EOS ≥ 200 cells / μL (High Eosinophi, HE) group and EOS<200 cells / μL (low Eosinophi, LE) group according to whether the peripheral blood EOS was greater than 200 cells / μL at admission. Peripheral venous blood data (including blood eosinophil count, white blood cell count, lymphocyte percentage, neutrophil percentage), blood gas analysis value, lung function index and medication regimen of all patients were collected, and the efficacy of ICS was recorded. The patients were followed up for 1 year to observe the acute exacerbation and readmission rate, and the mortality rate was followed up for 1 year and 2 years. Results Neutrophil count, lymphocyte count and peak expiratory flow (PEF) in HE group were positively correlated with EOS value (P<0.05), and smoking was more likely to increase EOS value. HE group was more sensitive to ICS. The risk of acute exacerbation in HEA group was higher than that in LE group. ICS could reduce the rate of acute exacerbation in HE group. EOS value in LE group was inversely proportional to FEV1 / FVC and MMEF values (P<0.05). The risk of chronic pulmonary heart disease in LE group was higher than that in HE group. The 2-year mortality rate in HE group was higher than that in LE group. Conclusions Peripheral blood EOS count is correlated with some inflammatory indicators, acute exacerbation risk, and lung function. ICS can improve the clinical symptoms and prognosis of patients with higher EOS count.
Objective To analyse the content and structure of the health management policy text for chronic obstructive pulmonary disease (COPD) in China, and to provide a reference for the optimization and improvement of subsequent relevant policies. Methods We searched for relevant policy documents on COPD health management at the national level from January 2017 to December 2023, constructed a two-dimensional analysis framework for policy tools and chronic disease health management processes, coded and classified policy texts, and used content analysis method to analyze policy texts. Results Twenty-four policy texts were included. There were 183 codes for policy tool dimension, with supply based, environmental based, and demand based tools accounting for 43.72%, 47.54%, and 8.74%, respectively. There were 124 codes for the dimension of health management processes, with health information collection and management accounting for 12.10%, risk prediction accounting for 14.52%, intervention and treatment accounting for 66.13%, and follow-up and effectiveness evaluation accounting for 7.26%. Conclusions At present, the proportion of policy tools related to the management of COPD in China needs to be dynamically adjusted. Environmental tools should be appropriately reduced, the internal structure of supply tools should be optimized, the driving effect of demand tools should be comprehensively enhanced, the coupling of COPD health management processes should be strengthened, and the relevant policy system and overall quality should be continuously improved.
Objective To analyze the differences in microbial communities in bronchoalveolar lavage fluid (BALF) from patients with simple pneumonia versus those with chronic obstructive pulmonary disease (COPD) combined with lower respiratory tract infection using metagenomic next-generation sequencing (mNGS). Methods Patients hospitalized for pulmonary infections at the First Affiliated Hospital of Xinjiang Medical University between December 2021 and March 2023 were included. Based on the presence of COPD, the patients were divided into two groups: those with simple pneumonia and those with COPD combined with lower respiratory tract infection. mNGS was employed to detect microbes in BALF, and the microbial community distribution characteristics of the two groups were analyzed. Results A total of 97 patients were included, of whom 80 (81.82%) had positive microbial detection results. The smoking index in COPD group with lower respiratory tract infection was significantly higher than that in the group with simple pneumonia (t= −3.62, P=0.001). Differences in microbial community distributions were observed between the groups. At the genus level, 19 species of microorganisms were detected in the simple pneumoniapulmonary infection group, including 8 bacteria (42.11%), 2 fungi (10.53%), 3 viruses (15.79%), and 6 other types of microorganisms (31.58%). In contrast, 22 types of microbes were detected in COPD group with lower respiratory tract infection, including 10 bacteria (47.62%), 3 fungi (14.29%), 4 viruses (19.05%), and 4 other types of microorganisms (19.05%). Differences were also noted in reads per million (RPM) values; bacterial RPM values at the genus level were significantly higher in the COPD group during non-severe pneumonia compared to the simple pneumonia group (Z=–2.706, P=0.007). In the patients with severe pneumonia, RPM values at the genus and species levels were significantly higher than those in non-severe pneumonia (Z=−2.202, P=0.028; Z=−2.141, P=0.032). In COPD combined with severe pneumonia, bacterial RPM values were significantly higher at the species level compared to non-severe pneumonia (Z=−2.367, P=0.017). ConclusionsThere are differences in the distribution of microbial communities at the genus and species levels in BALF from patients with COPD combined with lower respiratory tract infection compared to those with simple pulmonary pneumonia. Bacteria are the predominant microbial type in both groups, but the dominant bacterial species differ between them. Simple pneumonia are primarily associated with bacterial, viral, and other types of microbial infections, while COPD combined with lower respiratory tract infection is predominantly associated with fungal and bacterial infections. RPM values may serve as an indicator of the severity of pneumonia.
Objective To investigate the phenotyping of COPD by cluster analysis and evaluate the value of this method.Methods 168 COPD patients were enrolled from Beijing Tongren Hospital. Demographic and clinical data, such as, sex, age, body mass index ( BMI) , smoking index, course of disease,exacerbation rate, and comorbidities were collected. Pulmonary function test, emphysema scoring by HRCT,dyspnea by MMRC score, COPD assessment test ( CAT) score, six-minute walk test were performed for each patient during the stable stage. Cluster analysis was conducted using SPSS 13. 0. Results According to the GOLD criteria,5, 75, 75, and 13 patients were classified into GOLD stage 1, 2, 3, and 4, respectively. There was no difference among different stages in sex distribution, BMI, smoking index, hypertension, and cerebral infarction incidence( P gt; 0. 05) , but the differences in age, disease course, dyspnea score, six-minute walk distance, BODE score, CAT score, coronary heart disease, exacerbation rate, and HRCT emphysema visual score were significant( P lt;0. 05) . By cluster analysis,168 patients were finally classified into three groups:younger/mild, older/ severe, and older/moderate. The patients with the same GOLD stage appeared indifferent clusters and the patients belonging to different GOLD stages could be in the same cluster. There were significant differences among three groups in age, BMI, exacerbation rate, dyspnea score, CAT score, and comorbidities. The result showed that HRCT emphysema visual score was also an important index todifferentiate clusters, suggesting that emphysema was an important phenotype of COPD. Conclusions Cluster analysis can classify homogeneous subjects into the same cluster, and heterogeneous subjects into different clusters. The results suggest that COPD phenotyping by cluster analysis is clinically useful and significant.
目的 评价健身气功八段锦对慢性阻塞性肺疾病（COPD）稳定期患者临床疗效及肺功能的影响。 方法 2011年6月－2012年5月将COPD稳定期患者随机分为试验组和对照组各40例。在两组均接受西医基础治疗基础上，试验组同时采用健身气功八段锦肺康复训练：每日下午练习气功八段锦1次，每次30 min，疗程90 d。观察两组患者的临床疗效及肺功能改善情况。 结果 观察期（两组各1例）患者不能坚持而弃之。试验组总疗效、肺功能改善情况优于对照组（P＜0.05）。 结论 通过健身气功八段锦训练可在一定程度上改善COPD稳定期患者的临床疗效及肺功能，值得推广。
Objective The purpose of the current research was to analyze the relevant risk factors for short-term death in patients with chronic obstructive pulmonary disease (COPD) and heart failure (HF), and to build a predictive nomogram. Methods We conducted a retrospective analysis of clinical data from 1 323 COPD and HF comorbidity patients who were admitted to the Affiliated Hospital of Southwest Medical University from January 2018 to January 2022. Samples were divided into survival and death groups based on whether they died during the follow-up. General data and tested index of both groups were analyzed, and the discrepant index was analyzed by single factor and multiple factor Logistic regression analysis. R software was applied to create the nomogram by visualizing the results of the regression analysis. The accuracy of the results was verified by C index, calibration curve, and ROC curve. Results The results from the multiple factor Logistic regression analysis indicated that age (OR=1.085, 95%CI 1.048 to 1.125), duration of smoking (OR=1.247, 95%CI 1.114 to 1.400), duration of COPD (OR=1.078, 95%CI 1.042 to 1.116), comorbidity with respiratory failure (OR=5.564, 95%CI 3.372 to 9.329), level of NT-proBNP (OR=1.000, 95%CI 1.000 to 1.000), level of PCT (OR=1.153, 95%CI 1.083 to 1.237), and level of D-dimer (OR=1.205, 95%CI 1.099 to 1.336) were risk factors for short-term death of COPD and HF comorbidity patients. The level of ALB (OR=0.892, 95%CI 0.843 to 0.942) was a protective factor that was used to build the predictive nomogram with the C index of 0.874, the square under the working characteristics curve of the samples of 0.874, the specify of 82.5%, and the sensitivity of 75.0%. The calibration curve indicated good predictive ability of the model. Conclusion The nomogram diagram built by the current research indicated good predictability of short-term death in COPD and HF comorbidity patients.
Objective To investigate the therapeutic effects of thyroid hormone replacement on critically ill COPD patients with low serum thyroid hormone. Methods Sixty-seven critically ill patients with acute exacerbation of COPD ( AECOPD) , and complicated with respiratory and/ or heart failure and low serum thyroid hormone, admitted from July 2008 to June 2011, were recruited for the study. They were randomly divided into an intervention group ( n = 34) and a control group ( n = 33) . The control group received conventional treatment and the intervention group received conventional treatment plus additional thyroid hormone replacement therapy. Results Compared with the control group, the overall efficacy of the intervention group was not significantly different ( 88. 2% vs. 81. 8% , P gt; 0. 05) , while average effective time was significantly shorter [ ( 9. 6 ±2. 5) d vs. ( 12. 3 ±2. 8) d, P lt; 0. 05] . The post-treatment serum FT3 , FT4 , TT4 , and h-TSH levels were significantly higher in the intervention group than those in the control group, and significantly higher than baseline ( P lt;0. 05) . Conclusions For AECOPD patients complicated with respiratory and/or heart failure and low serum thyroid hormone, thyroid hormone supplement at low dosage will help to improve serumthyroid hormone level, and promote early recovery.