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Prevalence and Associated Factors of Electrocardiogram Abnormalities in Patients With Systemic Lupus Erythematosus: A
Zhuoran Hu1, Lin Wu1, Zhiming Lin1
1Third Affiliated Hospital of Sun Yat-sen University, Guangzhou City, China.
Insights
Electrocardiogram (EKG) abnormalities like T wave and ST-T changes are common in systemic lupus erythematosus (SLE) patients. Factors such as age, disease duration, and hypertension influence these cardiac findings.
Area of Science:
- Cardiology
- Rheumatology
- Medical Informatics
Background:
- Cardiac involvement is frequent in Systemic Lupus Erythematosus (SLE).
- Electrocardiogram (EKG) abnormalities can predict future cardiovascular events.
- Understanding EKG changes in SLE is crucial for patient management.
Purpose of the Study:
- To determine the prevalence of EKG abnormalities in SLE patients.
- To identify factors associated with these EKG abnormalities using machine learning.
Main Methods:
- A cross-sectional study analyzed records of 299 SLE patients.
- EKG abnormalities were categorized, and associated factors were assessed.
- Machine learning models, including random forests, were employed.
Main Results:
- 128 out of 299 SLE patients had clinically significant EKG abnormalities.
- T wave changes (52.3%) and nonspecific ST-T changes (26.6%) were most prevalent.
- Machine learning identified age, disease duration, disease activity, hypertension, anti-SSA antibodies, and Sjögren's syndrome as associated factors.
Conclusions:
- Nonspecific ST-T and T wave changes are common EKG findings in SLE.
- Clinical and demographic factors significantly influence these cardiac abnormalities.
- Machine learning effectively identified key predictors of EKG abnormalities in SLE.
Objective:
Electrocardiogram (EKG) abnormalities are predictive of subsequent cardiovascular events. Cardiac involvement is common in systemic lupus erythematosus (SLE). We aimed to determine the prevalence of EKG abnormalities in SLE patients and to examine the factors associated with EKG abnormalities with machine learning approaches.
Methods:
Consecutive SLE patients' records were retrieved from the database of the hospital for the cross-sectional study. Abnormal EKGs with clinical significance were grouped by the presence of tachyarrhythmias, atrioventricular block, nonspecific ST segment changes, T wave abnormalities, ventricular hypertrophy, axis deviation, bundle branch block, and QT interval prolongation. Associated factors of the most common EKG abnormalities were assessed by comparing logistic regression and 4 other machine learning approaches.
Results:
In the present study, 299 patients were enrolled, with 128 showing clinically significant abnormalities on EKG. T wave changes (52.3%), nonspecific ST segment-T wave (ST-T) changes (26.6%), and prolonged QT interval (8.6%) were the most prevalent abnormalities among patients with abnormal findings on EKG. Random forests models had the best performance in the discovery of associated factors. Age, disease duration, antinuclear antibody titer, disease activity (as measured by the Systemic Lupus Erythematosus Disease Activity Index 2000) were associated with nonspecific ST-T changes, prolonged QT interval, and T wave changes. Hypertension, positivity for anti-SSA antibodies, and secondary Sjögren's syndrome were influential factors for nonspecific ST-T changes, prolonged QT interval, and T wave changes, specifically.
Conclusion:
ST-T and T wave changes were the most common abnormalities seen on EKGs of SLE patients. Our finding suggests that age, longer disease duration, higher disease activity, hypertension, anti-SSA antibody positivity, and secondary Sjögren's syndrome are important and influential factors in these EKG abnormalities.
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