Clinical significance of HIF-1α, ET-1, and NO as biomarkers in chronic obstructive pulmonary disease patients with pulmonary hypertension

医学 慢性阻塞性肺病 内科学 恶化 胃肠病学 肺动脉高压 心脏病学 缺氧(环境) 肺病 内皮功能障碍 化学 有机化学 氧气
作者
Xuan Zhang,Youxia Zhou,Huicong Zhang
标识
DOI:10.17305/bb.2024.11078
摘要

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD), with repeated infections and airflow limitation leading to endothelial dysfunction. The objective of this study was to retrospectively investigate the clinical significance of serum hypoxia-inducible factor 1-alpha (HIF-1α), plasma endothelin-1 (ET-1), and nitric oxide (NO) as non-invasive blood biomarkers for diagnosing patients with acute exacerbation of COPD (AECOPD). A total of 230 AECOPD patients were assessed for serum HIF-1α, plasma ET-1, and NO levels using Doppler echocardiography and blood tests. Clinical characteristics, including age, COPD duration, and comorbidities, were compared between patients with and without PH. The diagnostic value was determined through receiver operating characteristic analysis. Pearson correlation and multivariate logistic analyses explored the correlation of biomarkers in AECOPD with PH. Serum HIF-1α, plasma ET-1, and NO levels showed significant differences between COPD patients with and without PH. The combination model (0.027 * HIF-1α + 0.028 * ET-1 − 0.049 * NO) demonstrated an area under the curve of 0.89, indicating superior diagnostic value compared to individual biomarkers. Multivariate logistic analysis identified smoking, higher Global Initiative for Chronic Obstructive Lung Disease grade, hypertension, and elevated levels of HIF-1α, ET-1, and NO as independent risk factors for AECOPD. Positive correlations were observed between serum HIF-1α and plasma ET-1 levels with pulmonary artery systolic pressure, while NO demonstrated a negative correlation. Serum HIF-1α, plasma ET-1, and NO were associated with AECOPD and PH, and detecting individual or combined levels of these biomarkers in the blood can predict COPD-related PH.

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