ArticleInternational journal of chronic obstructive pulmonary disease2026
The Disproportionate Burden of Cardiovascular Disease in Mild-to-Moderate COPD.
Article in International journal of chronic obstructive pulmonary disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Cardiovascular disease (CVD) is a major comorbidity in chronic obstructive pulmonary disease (COPD). However, whether cardiovascular burden increases with the severity of COPD requires more nuanced investigation. This study investigated the association between COPD severity and CVD prevalence, and evaluated their independent and joint effects on long-term survival. Methods: This multicenter cohort study included 553 stable COPD patients. Disease severity was stratified by GOLD grades and the multidimensional BODEx index. Logistic regression and Cox proportional hazards models were used to evaluate CVD prevalence across severity stages and identify predictors of all-cause mortality. Results: Patients were classified as mild-to-moderate (GOLD 1-2; 57.7%) or severe-to-very severe (GOLD 3-4; 42.3%). A clear paradox emerged: CVD prevalence was significantly lower in severe-to-very severe COPD compared to mild-to-moderate disease (45.7% vs. 59.6%, P=0.001). Adjusted analysis indicated that severe airflow limitation was independently associated with lower odds of CVD (OR 0.68, P=0.038). Notably, CVD was a significant mortality predictor only in early-stage disease. Conversely, in advanced COPD, the multidimensional BODEx score >4 emerged as the strongest independent predictor of mortality (HR 2.19, P<0.001), rendering CVD history statistically non-significant (P=0.10). Conclusion: CVD burden is highest in mild-to-moderate stages, where it significantly drives mortality. In advanced disease, overall multidimensional severity (BODEx index) supersedes CVD to determine survival. These findings emphasize prioritizing early cardiovascular screening in mild COPD while utilizing multidimensional indices for advanced prognosis.
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