New-Onset Atrial Fibrillation Is a Risk Factor of Ischemic Stroke in Chronic Obstructive Pulmonary Disease

Liu, Chi‐Chun; Chen, Yu-Hsuan; Chang, Yin-Han; Chien, Wu-Chien; Lin, Hon-Yi; Cheng, Chen-Li; Cheng, Chun-An

doi:10.3390/healthcare10020381

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…COPD increases the incidence of AF and the risk of subsequent cardiovascular death. Similarly, comorbid AF increases the incidence of ischemic stroke, respiratory failure, and heart failure events in patients with COPD (34)(35)(36)(37). The vicious circle relationship between COPD and AF, and the contradiction of pharmacological treatment, makes it urgent to explore the mechanisms of COPD and AF co-morbidity and to find potential therapeutic targets.…”

Section: Discussionmentioning

confidence: 99%

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation

Sun

Lin

Zhang

et al. 2023

Front. Cardiovasc. Med.

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BackgroundPatients with chronic obstructive pulmonary disease (COPD) often present with atrial fibrillation (AF), but the common pathophysiological mechanisms between the two are unclear. This study aimed to investigate the common biological mechanisms of COPD and AF and to search for important biomarkers through bioinformatic analysis of public RNA sequencing databases.MethodsFour datasets of COPD and AF were downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes common to both diseases were screened by WGCNA analysis, followed by protein-protein interaction network construction and functional enrichment analysis to elucidate the common mechanisms of COPD and AF. Machine learning algorithms were also used to identify key biomarkers. Co-expression analysis, “transcription factor (TF)-mRNA-microRNA (miRNA)” regulatory networks and drug prediction were performed for key biomarkers. Finally, immune cell infiltration analysis was performed to evaluate further the immune cell changes in the COPD dataset and the correlation between key biomarkers and immune cells.ResultsA total of 133 overlapping genes for COPD and AF were obtained, and the enrichment was mainly focused on pathways associated with the inflammatory immune response. A key biomarker, cyclin dependent kinase 8 (CDK8), was identified through screening by machine learning algorithms and validated in the validation dataset. Twenty potential drugs capable of targeting CDK8 were obtained. Immune cell infiltration analysis revealed the presence of multiple immune cell dysregulation in COPD. Correlation analysis showed that CDK8 expression was significantly associated with CD8+ T cells, resting dendritic cell, macrophage M2, and monocytes.ConclusionsThis study highlights the role of the inflammatory immune response in COPD combined with AF. The prominent link between CDK8 and the inflammatory immune response and its characteristic of not affecting the basal expression level of nuclear factor kappa B (NF-kB) make it a possible promising therapeutic target for COPD combined with AF.

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Section: Discussionmentioning

confidence: 99%

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation

Sun

Lin

Zhang

et al. 2023

Front. Cardiovasc. Med.

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Prognosis Factors in Patients with Copd and Atrial Fibrillation – Mini Review

et al. 2023

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Chronic obstructive pulmonary disease (COPD) and atrial fibrillation (AF) are common pathologies in the elderly patient. The simultaneous occurrence of the two conditions influences the quality of life and increases the rate of exacerbations. About two-thirds of patients with atrial fibrillation have dyspnea. Severe dyspnea in the patient with COPD and AF can be difficult to manage, suggesting an exacerbation of the disease, the onset of atrial fibrillation or even a symptom of associated comorbidities, the most common of which being heart failure. The risk of developing AF in COPD increases with the severity of airflow obstruction. Factors such as smoking, aging, dyslipidemia, the presence of diabetes, hypertension or heart failure influence the prognosis of patients with COPD and AF. Furthermore, oxidative stress, hypoxia, systemic inflammation or immunological changes decrease the survival rate and may favor the recurrence of AF. In the evolution of concomitant COPD- FA cases, proinflammatory cytokines such as tumor necrosis factor α (TNF-α), monocyte chemotactic protein (MCP-1), interleukin-6 (IL-6), interleukin-8 (IL- 8) intervene. This paper aims at analyzing data related to the factors that would influence the prognosis of patients with COPD and AF.

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Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study

Hsiao

Cheng

Chen

et al. 2023

JPM

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(1) Background: Intravenous thrombolysis following acute ischemic stroke (AIS) can reduce disability and increase the survival rate. We designed a functional recovery analysis by using semantic visualization to predict the recovery probability in AIS patients receiving intravenous thrombolysis; (2) Methods: We enrolled 131 AIS patients undergoing intravenous thrombolysis from 2011 to 2015 at the Medical Center in northern Taiwan. An additional 54 AIS patients were enrolled from another community hospital. A modified Rankin Score ≤2 after 3 months of follow-up was defined as favorable recovery. We used multivariable logistic regression with forward selection to construct a nomogram; (3) Results: The model included age and the National Institutes of Health Stroke Scale (NIHSS) score as immediate pretreatment parameters. A 5.23% increase in the functional recovery probability occurred for every 1-year reduction in age, and a 13.57% increase in the functional recovery probability occurred for every NIHSS score reduction. The sensitivity, specificity, and accuracy of the model in the validation dataset were 71.79%, 86.67%, and 75.93%, respectively, and the area under the receiver operating characteristic curve (AUC) was 0.867; (4) Conclusions: Semantic visualization-based functional recovery prediction models may help physicians assess the recovery probability before patients undergo emergency intravenous thrombolysis.

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New-Onset Atrial Fibrillation Is a Risk Factor of Ischemic Stroke in Chronic Obstructive Pulmonary Disease

Cited by 3 publications

References 41 publications

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation

Combining bioinformatics and machine learning to identify common mechanisms and biomarkers of chronic obstructive pulmonary disease and atrial fibrillation

Prognosis Factors in Patients with Copd and Atrial Fibrillation – Mini Review

Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study

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