COPD is associated with increased cardiovascular disease risk independent of phenotype

BACKGROUND AND OBJECTIVE

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide that frequently presents with concomitant cardiovascular diseases. Despite the pathological distinction between individual COPD phenotypes such as emphysema and chronic bronchitis, there is a lack of knowledge about the impact of COPD phenotype on cardiovascular disease risk. Thus, this study aimed to utilize a nationally representative sample to investigate cardiovascular disease prevalence in patients with COPD with emphysema and chronic bronchitis phenotypes.

METHODS

Data from 31,560 adults including 2504 individuals with COPD, collected as part of the National Health and Nutrition Examination Survey (1999-2018), were examined.

RESULTS

A significantly increased cardiovascular disease risk, including coronary heart disease, heart failure, myocardial infarction and stroke, was identified in patients with COPD among all disease phenotypes. Particularly, compared to those without COPD, individuals with chronic bronchitis presented with 1.76 (95% CI: 1.41-2.20) times greater odds, individuals with emphysema with 2.31 (95% CI: 1.80-2.96) times greater odds, while those with a concurrent phenotype (combined chronic bronchitis and emphysema) exhibited 2.98 (95% CI: 2.11-4.21) times greater odds of reporting cardiovascular diseases.

CONCLUSION

Our data confirms that patients with COPD present an elevated risk of developing cardiovascular disease among all phenotypes, with the most marked increase being in those with concurrent chronic bronchitis and emphysema phenotypes. These findings emphasize the need for awareness and appropriate cardiovascular screening in COPD.

A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review

BACKGROUND

Lung diseases, both infectious and non-infectious, are the most prevalent cause of mortality overall in the world. Medical research has identified pneumonia, lung cancer, and Corona Virus Disease 2019 (COVID-19) as prominent lung diseases prioritized over others. Imaging modalities, including X-rays, computer tomography (CT) scans, magnetic resonance imaging (MRIs), positron emission tomography (PET) scans, and others, are primarily employed in medical assessments because they provide computed data that can be utilized as input datasets for computer-assisted diagnostic systems. Imaging datasets are used to develop and evaluate machine learning (ML) methods to analyze and predict prominent lung diseases.

OBJECTIVE

This review analyzes ML paradigms, imaging modalities' utilization, and recent developments for prominent lung diseases. Furthermore, the research also explores various datasets available publically that are being used for prominent lung diseases.

METHODS

The well-known databases of academic studies that have been subjected to peer review, namely ScienceDirect, arXiv, IEEE Xplore, MDPI, and many more, were used for the search of relevant articles. Applied keywords and combinations used to search procedures with primary considerations for review, such as pneumonia, lung cancer, COVID-19, various imaging modalities, ML, convolutional neural networks (CNNs), transfer learning, and ensemble learning.

RESULTS

This research finding indicates that X-ray datasets are preferred for detecting pneumonia, while CT scan datasets are predominantly favored for detecting lung cancer. Furthermore, in COVID-19 detection, X-ray datasets are prioritized over CT scan datasets. The analysis reveals that X-rays and CT scans have surpassed all other imaging techniques. It has been observed that using CNNs yields a high degree of accuracy and practicability in identifying prominent lung diseases. Transfer learning and ensemble learning are complementary techniques to CNNs to facilitate analysis. Furthermore, accuracy is the most favored metric for assessment.

Systematic review and meta-analysis of prevalence of undiagnosed major cardiac comorbidities in COPD

Background

It is often stated that heart disease is underdiagnosed in COPD. Evidence for this statement comes from primary studies, but these have not been synthesised to provide a robust estimate of the burden of undiagnosed heart disease.

Methods

A systematic review of studies using active diagnostic techniques to establish the prevalence of undiagnosed major cardiac comorbidities in patients with COPD was carried out. MEDLINE, Embase, Scopus and Web of Science were searched for terms relating to heart failure (specifically, left ventricular systolic dysfunction (LVSD), coronary artery disease (CAD) and atrial fibrillation), relevant diagnostic techniques and COPD. Studies published since 1980, reporting diagnosis rates using recognised diagnostic criteria in representative COPD populations not known to have heart disease were included. Studies were classified by condition diagnosed, diagnostic threshold used and whether participants had stable or exacerbated COPD. Random-effects meta-analysis of prevalence was conducted where appropriate.

Results

In general, prevalence estimates for undiagnosed cardiac comorbidities in COPD had broad confidence intervals, with significant study heterogeneity. Most notably, a prevalence of undiagnosed LVSD of 15.8% (11.1-21.1%) was obtained when defined as left ventricular ejection fraction <50%. Undiagnosed CAD was found in 2.3-18.0% of COPD patients and atrial fibrillation in 1.4% (0.3-3.5%).

Conclusion

Further studies using recent diagnostic advances, and investigating therapeutic interventions for patients with COPD and heart disease are needed.

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

Background

Patients 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.

Methods

Four 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.

Results

A 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.

Conclusions

This 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.

Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data

Background

Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Progression is further exacerbated by the coexistence of cardiovascular disease (CVD). We aim to construct a diagnostic nomogram for predicting the risk of coexisting CVD and a prognostic nomogram for predicting long-term survival in COPD.

Methods

The 540 eligible participants selected from the NHANES 2005-2010 were included in this study. Logistic regression analysis was used to construct a diagnostic nomogram for the diagnosis of coexisting CVD in COPD. Cox regression analyses were used to construct a prognostic nomogram for COPD. A risk stratification system was developed based on the total score generated from the prognostic nomogram. We used C-index and ROC curves to evaluate the discriminant ability of the newly built nomograms. The models were also validated utilizing calibration curves. Survival curves were made using the Kaplan-Meier method and compared by the Log-rank test.

Results

Logistic regression analysis showed that gender, age, neutrophil, RDW, LDH, and HbA1c were independent predictors of coexisting CVD and were included in the diagnostic model. Cox regression analysis indicated that CVD, gender, age, BMI, RDW, albumin, LDH, creatinine, and NLR were independent predictors of COPD prognosis and were incorporated into the prognostic model. The C-index and ROC curves revealed the good discrimination abilities of the models. And the calibration curves implied that the predicted values by the nomograms were in good agreement with the actual observed values. In addition, we found that coexisting with CVD had a worse prognosis compared to those without CVD, and the prognosis of the low-risk group was better than that of the high-risk group in COPD.

Conclusions

The nomograms we developed can help clinicians and patients to identify COPD coexisting CVD early and predict the 5-year and 10-year survival rates of COPD patients, which has some clinical practical values.

Effects of mineralocorticoid receptor antagonists in heart failure with reduced ejection fraction patients with chronic obstructive pulmonary disease in EMPHASIS-HF and RALES

AIMS

Heart failure with reduced ejection fraction (HFrEF) and chronic obstructive pulmonary disease (COPD) individually cause significant morbidity and mortality. Their coexistence is associated with even worse outcomes, partly due to suboptimal heart failure therapy, especially underutilisation of beta-blockers. Our aim was to investigate outcomes in HFrEF patients with and without COPD, and the effects of mineralocorticoid receptor antagonists (MRAs) on outcomes.

METHODS AND RESULTS

We studied the effect of MRA therapy in a post-hoc pooled analysis of 4397 HFrEF patients in the RALES and EMPHASIS-HF trials. The primary endpoint was the composite of heart failure hospitalisation or cardiovascular death. A total of 625 (14.2%) of the 4397 patients had COPD. Patients with COPD were older, more often male, and smokers, but less frequently treated with a beta-blocker. In patients with COPD, event rates (per 100 person-years) for the primary endpoint and for all-cause mortality were 25.2 (95% confidence interval 22.1-28.7) and 17.2 (14.9-19.9), respectively, compared with 19.9 (18.8-21.1) and 12.8 (12.0-13.7) in participants without COPD. The risks of all-cause hospitalisation and sudden death were also higher in patients with COPD. The benefit of MRA, compared with placebo, was consistent in patients with or without COPD for all outcomes, e.g. hazard ratio for the primary outcome 0.66 (0.50-0.85) for COPD and 0.65 (0.58-0.73) for no COPD (interaction p = 0.93). MRA-induced hyperkalaemia was less frequent in patients with COPD.

CONCLUSIONS

In RALES and EMPHASIS-HF, one-in-seven patients with HFrEF had coexisting COPD. HFrEF patients with COPD had worse outcomes than those without. The benefits of MRAs were consistent, regardless of COPD status.

Tongxinluo prevents chronic obstructive pulmonary disease complicated with atherosclerosis by inhibiting ferroptosis and protecting against pulmonary microvascular barrier dysfunction

Cardiovascular comorbidities are pervasive in chronic obstructive pulmonary disease (COPD) and often result in serious adverse cardiovascular events. Tongxinluo (TXL) has been clinically verified to treat atherosclerosis (AS), improve lung function and alleviate dyspnoea. The present study aimed to explore the effect of lung microvascular barrier dysfunction on AS in COPD and the potential pulmonary protective mechanisms of TXL in COPD complicated with AS. COPD complicated with AS was induced in mice by cigarette smoke (CS) exposure and high-fat diet (HFD) feeding. The mice were treated with atorvastatin (ATO), TXL or combination therapy (ATO+TXL) for 20 weeks. Pulmonary function, lung pathology, serum lipid levels, atherosclerotic plaque area and indicators of barrier function, oxidative stress and ferroptosis in lung tissue were evaluated. In vitro, human pulmonary microvascular endothelial cells (HPMECs) were pretreated with TXL for 4 h and then incubated with cigarette smoke extract (CSE) and homocysteine (Hcy) for 36 h to induce barrier dysfunction. Then the indicators of barrier function, oxidative stress and ferroptosis were measured. The results demonstrate that CS aggravated dyslipidaemia, atherosclerotic plaque formation, pulmonary function decline, pathological injury, barrier dysfunction, oxidative stress and ferroptosis in the HFD-fed mice. However, these abnormalities were partially reversed by ATO and TXL. Similar results were observed in vitro. In conclusion, pulmonary microvascular barrier dysfunction plays an important role by which COPD affects the progression of AS, and ferroptosis may be involved. Moreover, TXL delays the progression of AS and reduces cardiovascular events by protecting the pulmonary microvascular barrier and inhibiting ferroptosis.

Right ventricular end-diastolic volume and outcomes in exacerbations of COPD

BACKGROUND AND OBJECTIVE

Right ventricular (RV) volumes are crucial outcome determinants in pulmonary diseases. Little is known about the associations of RV volumes during hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD). We aimed to ascertain associations of RV end-diastolic volume indexed to body surface area (RVEDVI) during hospitalized AECOPD and its relationship with mortality in long-term follow-up.

METHODS

This is a prospective observational cohort study (December 2013-November 2019, ACTRN12617001562369) using dynamic retrospective ECG-gated computed tomography during hospitalized AECOPD. RVEDVI was defined as normal or high using Framingham Offspring Cohort values. Cox regression determined the prognostic relevance of RVEDVI for death.

RESULTS

A total of 148 participants (70 ± 10 years [mean ± SD], 88 [59%] men) were included, of whom 75 (51%) had high RVEDVI. This was associated with more frequent hospital admissions in the 12 months before admission (52/75 [69%] vs. 38/73 [52%], p = 0.04) and higher breathlessness (modified Medical Research Council score, 2.9 ± 1.3 vs. 2.4 ± 1.2, p = 0.007). During follow-up, high RVEDVI was associated with greater mortality (log-rank p = 0.001). In univariable Cox regression, increasing RVEDVI was associated with higher mortality (hazard ratio [HR]: 1.02 per ml/m² ; 95% CI: 1.01, 1.03; p = 0.001). In multivariable Cox regression, RVEDVI was independently associated with mortality (HR: 1.01 per ml/m² ; 95% CI: 1.00, 1.03; p = 0.050) at a borderline significance level. Adding RVEDVI to three COPD mortality prediction systems improved model fit (pooled chi-square test [BODE: p = 0.05, ADO: p = 0.04, DOSE: p = 0.02]).

CONCLUSION

In patients with hospitalized AECOPD, higher RV end-diastolic volume was associated with worse acute clinical parameters and greater mortality.

Characteristics of length of stay and cardiovascular pharmacotherapy advice among chronic obstructive pulmonary disease patients

Chronic obstructive pulmonary disease (COPD) increases the global disease burden due to its diverse adverse health effects on the respiratory and cardiovascular systems. This study aimed to elucidate the potential indicators of length of stay (LOS) and pharmacotherapy advice among COPD patients. Thereafter, hospitalized COPD patients with clinical records and respiratory and cardiovascular pharmacotherapy advice were retrospectively collected from a tertiary hospital between April 2017 and September 2020, and the determinants of LOS and cardiovascular pharmacotherapy advice were explored using regression analyses. Overall, 475 patients with COPD were recruited and stratified according to exacerbation and presence of Cor pulmonale (CP). The extended LOS, increased B-type natriuretic peptides (BNP), and a higher percentage of cardiovascular pharmacotherapy advice were observed in COPD with CP regardless of exacerbation, although the percentage of respiratory prescriptions was comparable. The presence of CP indicated a longer LOS (B = 1.850, p < 0.001) for COPD regardless of exacerbation. Meanwhile, elevated BNP levels indicated cardiovascular pharmacotherapy advise for both COPD in exacerbation (OR = 1.003, p = 0.012) and absence of exacerbation (OR = 1.006, p = 0.015). Moreover, advice for trimetazidine use for COPD in exacerbation (OR = 1.005, p = 0.002) has been suggested. Therefore, CP appears to be an important comorbidity resulting in extended LOS for COPD, which is likely to be advised with cardiovascular pharmacotherapy, which might be guided through BNP monitoring.

Prediction of cardiovascular risk in patients with chronic obstructive pulmonary disease: a study of the National Health and Nutrition Examination Survey database

Background

Cardiovascular disease (CVD) is a common comorbidity associated with chronic obstructive pulmonary disease (COPD), but few studies have been conducted to identify CVD risk in COPD patients. This study was to develop a predictive model of CVD in COPD patients based on the National Health and Nutrition Examination Survey (NHANES) database.

Methods

A total of 3,226 COPD patients were retrieved from NHANES 2007–2012, dividing into the training (n = 2351) and testing (n = 895) sets. The prediction models were conducted using the multivariable logistic regression and random forest analyses, respectively. Receiver operating characteristic (ROC) curves, area under the curves (AUC) and internal validation were used to assess the predictive performance of models.

Results

The logistic regression model for predicting the risk of CVD was developed regarding age, gender, body mass index (BMI), high-density lipoprotein (HDL), glycosylated hemoglobin (HbA1c), family history of heart disease, and stayed overnight in the hospital due to illness last year, which the AUC of the internal validation was 0.741. According to the random forest analysis, the important variables-associated with CVD risk were screened including smoking (NNAL and cotinine), HbA1c, HDL, age, gender, diastolic blood pressure, poverty income ratio, BMI, systolic blood pressure, and sedentary activity per day. The AUC of the internal validation was 0.984, indicating the random forest model for predicting the CVD risk in COPD cases was superior to the logistic regression model.

Conclusion

The random forest model performed better predictive effectiveness for the cardiovascular risk among COPD patients, which may be useful for clinicians to guide the clinical practice.

Chronic bronchial infection and incident cardiovascular events in chronic obstructive pulmonary disease patients: A long-term observational study

BACKGROUND AND OBJECTIVE

Cardiovascular (CV) diseases are frequent in patients with chronic obstructive pulmonary disease (COPD). Likewise, chronic bronchial infection (CBI) is also frequent in COPD and it is associated with systemic inflammation, a well-known CV risk factor. The objective of this study was to investigate the relationship between CBI, systemic inflammation and incident CV events.

METHODS

A post hoc analysis of prospectively collected cohort of 201 COPD patients [Global Initiative for Chronic Obstructive Lung Disease (GOLD) II-IV] followed up every 3-6 months for 84 months was conducted. CBI was defined as ≥3 positive pathogenic microorganisms sputum cultures over 1 year, separated by ≥3 months. Systemic inflammation was assessed by circulating levels of C-reactive protein and fibrinogen. Fatal and non-fatal CV events, including coronary and cerebrovascular events as well as arrhythmia episodes, were prospectively recorded. For analysis, they were analysed separately and combined in a composite variable.

RESULTS

As hypothesized, CBI was associated with persistent systemic inflammation and a significantly higher incidence of CV events (HR: 3.88; 95% CI: 1.83-8.22), mainly of coronary origin independent of age, number and severity of exacerbations, comorbidities, other CV risk factors, lung function, BMI, smoking status and treatments. These associations were particularly significant in patients with CBI by Pseudomonas aeruginosa (PA).

CONCLUSION

CBI, particularly by PA, is associated with sustained and enhanced systemic inflammation and a higher incidence of CV events (especially coronary events). The possibility that treating CBI may decrease systemic inflammation and CV events in COPD deserves prospective, interventional studies.

Treatable cardiac disease in hospitalised COPD exacerbations

Introduction

Acute exacerbations of COPD (AECOPD) are accompanied by escalations in cardiac risk superimposed upon elevated baseline risk. Appropriate treatment for coronary artery disease (CAD) and heart failure with reduced ejection fraction (HFrEF) could improve outcomes. However, securing these diagnoses during AECOPD is difficult, so their true prevalence remains unknown, as does the magnitude of this treatment opportunity. We aimed to determine the prevalence of severe CAD and severe HFrEF during hospitalised AECOPD using dynamic computed tomography (CT).

Methods

A cross-sectional study of 148 patients with hospitalised AECOPD was conducted. Dynamic CT was used to identify severe CAD (Agatston score ≥400) and HFrEF (left ventricular ejection fraction ≤40% and/or right ventricular ejection fraction ≤35%).

Results

Severe CAD was detected in 51 of 148 patients (35%), left ventricular systolic dysfunction was identified in 12 cases (8%) and right ventricular systolic dysfunction was present in 18 (12%). Clinical history and examination did not identify severe CAD in approximately one-third of cases and missed HFrEF in two-thirds of cases. Elevated troponin and brain natriuretic peptide did not differentiate subjects with severe CAD from nonsevere CAD, nor distinguish HFrEF from normal ejection fraction. Undertreatment was common. Of those with severe CAD, only 39% were prescribed an antiplatelet agent, and 53% received a statin. Of individuals with HFrEF, 50% or less received angiotensin blockers, beta blockers or antimineralocorticoids.

Conclusion

Dynamic CT detects clinically covert CAD and HFrEF during AECOPD, identifying opportunities to improve outcomes via well-established cardiac treatments.

Severe, treatable cardiac disease is present during hospitalised #AECOPD exacerbations, and is often clinically unsuspected. This cardiac disease can be detected with dynamic CT. Appropriate treatment could change outcomes.https://bit.ly/2Is45wO

Different Clusters in Patients with Chronic Obstructive Pulmonary Disease (COPD): A Two-Center Study in Brazil

Background

Chronic obstructive pulmonary disease (COPD) has a functional definition. However, differences in clinical characteristics and systemic manifestations make COPD a heterogeneous disease and some manifestations have been associated with different risks of acute exacerbations, hospitalizations, and death.

Objective

Therefore, the objective of the study was to evaluate possible clinical clusters in COPD at two study centers in Brazil and identify the associated exacerbation and mortality rate during 1 year of follow-up.

Methods

We included patients with COPD and all underwent an evaluation composed of the Charlson Index, body mass index (BMI), current pharmacological treatment, smoking history (packs-year), history of exacerbations/hospitalizations in the last year, spirometry, six-minute walking test (6MWT), quality of life questionnaires, dyspnea, and hospital anxiety and depression scale. Blood samples were also collected for measurements of C-reactive protein (CRP), blood gases, laboratory analysis, and blood count. For the construction of the clusters, 13 continuous variables of clinical importance were considered: hematocrit, CRP, triglycerides, low density lipoprotein, absolute number of peripheral eosinophils, age, pulse oximetry, BMI, forced expiratory volume in the first second, dyspnea, 6MWD, total score of the Saint George Respiratory Questionnaire and packs-year of smoking. We used the Ward and K-means methods and determined the best silhouette value to identify similarities of individuals within the cluster (cohesion) in relation to the other clusters (separation). The number of clusters was determined by the heterogeneity values of the cluster, which in this case was determined as four clusters.

Results

We evaluated 301 COPD patients and identified four different groups of COPD patients. The first cluster (203 patients) was characterized by fewer symptoms and lower functional severity of the disease, the second cluster by higher values of peripheral eosinophils, the third cluster by more systemic inflammation and the fourth cluster by greater obstructive severity and worse gas exchange. Cluster 2 had an average of 959±3 peripheral eosinophils, cluster 3 had a higher prevalence of nutritional depletion (46.1%), and cluster 4 had a higher BODE index. Regarding the associated comorbidities, we found that only obstructive sleep apnea syndrome and pulmonary thromboembolism were more prevalent in cluster 4. Almost 50% of all patients presented an exacerbation during 1 year of follow-up. However, it was higher in cluster 4, with 65% of all patients having at least one exacerbation. The mortality rate was statistically higher in cluster 4, with 26.9%, vs 9.6% in cluster 1.

Conclusion

We could identify four clinical different clusters in these COPD populations, that were related to different clinical manifestations, comorbidities, exacerbation, and mortality rate. We also identified a specific cluster with higher values of peripheral eosinophils.

Increased risk of peripheral arterial occlusive diseases in patients with chronic obstructive pulmonary disease: a nationwide study in Taiwan

Objective

Chronic obstructive pulmonary disease (COPD) is associated with atherosclerosis. Previous studies including limited sample sizes have shown the prevalence of peripheral arterial occlusive disease (PAOD) among COPD patients. We sought to investigate the incidence of PAOD among COPD patients in Taiwan using a national database.

Methods

COPD patients were collected from the National Health Insurance Research Database of Taiwan from 1996 to 2010. The COPD cohort was propensity score matched according to age, sex, and comorbidities of atrial fibrillation, hypertension, diabetes, hyperlipidemia, cerebrovascular accidents, and chronic liver disease to patients without COPD (the control cohort). We evaluated the incidence of PAOD in COPD patients and the risk of PAOD associated with atrial fibrillation, hypertension, diabetes, hyperlipidemia, cerebrovascular accidents, and chronic liver disease.

Results

The study included 51,869 COPD patients and 51,869 control patients without COPD. The incidence of PAOD was 1.23-fold higher (95% confidence interval [CI]  =1.17–1.29) in the COPD group than in the non-COPD group. Moreover, COPD and atrial fibrillation alone (adjusted hazard ratio (aHR) 2.99; P=0.001), hypertension alone (aHR, 2.05; P<0.001), diabetes alone (aHR, 2.62; P<0.001) and cerebrovascular accidents alone (aHR 2.05; P<0.001), increased the risk of developing PAOD. The significant aHRs increased (from 3.7 to 4.9) when the number of comorbidities increased (from ≥1 to ≥3 comorbidities).

Conclusion

COPD patients have a higher incidence and an independently higher risk of PAOD than patients without COPD. The risk of PAOD is markedly elevated in COPD patients with more comorbidities.