ELECTROCARDIOGRAPHIC ALTERATIONS IN COPD: A MARKER OF DISEASE SEVERITY AND CARDIAC RISK

PRAVEEN BAHADUR GAUTAM; BABULAL KANNOUJIA; SWARAJ SHARMA

doi:10.22159/ijcpr.2025v17i3.55063

Authors

PRAVEEN BAHADUR GAUTAM Department of Tuberculosis and Chest disease, Maharshi Vashishtha Autonomous State Medical College, Basti, Uttar Pradesh, India
BABULAL KANNOUJIA Department of Medicine, Maharshi Vashishtha Autonomous State Medical College, Basti, Uttar Pradesh, India
SWARAJ SHARMA Department of Pathology, Maharshi Vashishtha Autonomous State Medical College, Basti, Uttar Pradesh, India https://orcid.org/0009-0004-0514-3059

DOI:

https://doi.org/10.22159/ijcpr.2025v17i3.55063

Keywords:

COPD, Electrocardiography, Cardiac risk, Disease severity, Right ventricular hypertrophy

Abstract

Objective: Chronic Obstructive Pulmonary Disease (COPD) is associated with significant cardiovascular complications, often reflected in electrocardiographic (ECG) changes. Understanding these alterations can aid in assessing disease severity and predicting cardiac risk in COPD patients. This study aimed to evaluate ECG abnormalities in COPD patients and their correlation with disease severity.

Methods: A cross-sectional study was conducted on 138 COPD patients (62% male, 38% female). Standard 12-lead ECG recordings were analyzed for common abnormalities, including right axis deviation (RAD), P pulmonale, right ventricular hypertrophy (RVH), arrhythmias, and QTc prolongation. Statistical analysis was performed to assess associations between ECG findings and COPD severity.

Results: Significant ECG alterations were observed, with RAD (45.7%), P pulmonale (38.4%), and RVH (34.8%) being the most prevalent. QTc prolongation was noted in 22.5% of cases, with a significant association with disease severity (p<0.05). Patients with severe COPD showed a higher prevalence of ECG abnormalities, suggesting increased cardiac strain. Conclusion: ECG changes in COPD patients are common and correlate with disease severity. Routine ECG screening in COPD management may help identify high-risk individuals for cardiovascular complications, improving clinical outcomes.

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