BackgroundCOPD has been identified as an etiology or related disease of bronchiectasis, and bronchiectasis has been classified as a comorbidity of COPD. In this study, we investigated the prevalence of bronchiectasis in different phenotypes of COPD subjects and the correlation between bronchiectasis and different phenotypes, especially emphysema.MethodsCOPD patients were recruited from April 2012 to December 2015. The presence of bronchiectasis and related information were statistically analyzed. COPD subjects were separated into subgroups in two ways: COPD with and without bronchiectasis groups and emphysema-predominant (emphysema index, EI≥9.9%) and non-emphysema-predominant (EI<9.9%) groups.ResultsIn total, 1,739 COPD patients were incorporated into the study, among which 140 cases (8.1%) were accompanied with radiological bronchiectasis. COPD patients with concomitant bronchiectasis presented worse pulmonary function (FEV1% predicted, P<0.001), higher EI (15.0% vs 13.4%, P<0.001), and higher proportion of pulmonary hypertension and cor pulmonale (6.4% vs 2.4%, P=0.005 and 23.6% vs 16.1%, P=0.022) than patients without bronchiectasis. Of all the COPD patients, 787 with EI data were divided into emphysema-predominant (n=369) and non-emphysema-predominant groups (n=418). The proportion of bronchiectasis was 16.5% and 10.3% (P=0.01), respectively. Severity of bronchiectasis increased as the degree of airflow limitation (r=−0.371, P<0.001) and emphysema increased (r=0.226, P=0.021). After adjusting confounding factors, FEV1% predicted (OR, 1.636; 95% CI, 1.219–2.197; P=0.001) and EI (OR, 1.993; 95% CI, 1.199–3.313; P=0.008) were significantly related with the presence of bronchiectasis in COPD patients.ConclusionThe proportion of bronchiectasis is higher in emphysema-predominant COPD subjects. Emphysema measured by EI and FEV1% predicted are independent predictors for bronchiectasis in COPD subjects, while the underlying mechanism deserves further investigation.

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The factors influencing the dissemination of public opinion on social media, the main carrier of public opinion, are diverse, complex and changeable. Existing studies of influential factors of public opinion dissemination focus on the information itself and information sources in the dissemination process, failing to consider the comprehensive influence of multidimensional factors, such as information content, sources and channels. This study takes the identification of multidimensional influential factors of social media information dissemination as the research object and comprehensively sorts out the influencing factors of public opinion. To improve the scientific basis and accuracy of the research, multidimensional factors, including information characteristics, dissemination network structure and user-level attributes, are selected to analyze the effect of influential factors in different dimensions on the dissemination of social media public opinion information using econometric models. Three main conclusions of this paper are as follows: (1) The traditional information characteristics (information content) and information source attributes (user-level factor) are not the only key factors affecting information dissemination, while the information channel (network structure) is worth more consideration. (2) Netizens tend to pay more attention to the psychological and emotional attributes of information when forwarding public opinions. The communication mode in which offline social elites enlighten the public no longer exists; whether a user is a network celebrity or lives in the central area no longer significantly affects public opinion dissemination. (3) The higher the total amount of information users release, the more the information would interfere with the public opinion. This is mainly because users with a higher level of activity may release more invalid information about advertising that has nothing to do with public opinion events.

Presents a unified information systems theory where stochastic information, fuzzy information, rough information, grey information, unascertained information and white and black information are all special cases. A unified concept of information, named blind information, is introduced. Also, relevant mathematical representations of various types of information are presented.

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