4.7 Article

Prevalence and Clinical Impact of Electrocardiographic Abnormalities in Patients with Chronic Kidney Disease

期刊

JOURNAL OF CLINICAL MEDICINE
卷 11, 期 18, 页码 -

出版社

MDPI
DOI: 10.3390/jcm11185414

关键词

electrocardiogram; chronic kidney disease; major adverse cerebrocardiovascular events

资金

  1. Young Medical Scientist Research Grant through the Seokchunnanum Foundation [SCY2106P]

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Chronic kidney disease (CKD) is a significant risk factor for cardiovascular disease, and electrocardiogram (ECG) can help predict future cerebrocardiovascular events in CKD patients. ECG abnormalities are closely associated with the incidence of major adverse cerebrocardiovascular events (MACCE) in CKD patients, and ECG diagnosis can be used in conjunction with traditional risk stratification models to improve cardiovascular risk assessment accuracy.
Chronic kidney disease (CKD) is a strong risk factor for cardiovascular disease. An electrocardiogram (ECG) is a basic test for screening cardiovascular disease. However, the impact of ECG abnormalities on cardiovascular prognosis in patients with CKD is largely unknown. A total of 2442 patients with CKD (stages 3-5) who underwent ECG between 2013 and 2015 were selected from the electronic health record database of the Korea University Anam Hospital. ECG abnormalities were defined using the Minnesota classification. The five-year major adverse cerebrocardiovascular event (MACCE), the composite of death, myocardial infarction (MI), and stroke were analyzed. The five-year incidences for MACCE were 27.7%, 20.8%, and 17.2% in patients with no, minor, and major ECG abnormality (p < 0.01). Kaplan-Meier curves also showed the highest incidence of MI, death, and MACCE in patients with major ECG abnormality. Multivariable Cox regression analysis revealed age, sex, diabetes, CKD stage, hsCRP, antipsychotic use, and major ECG abnormality as independent risk predictors for MACCE (adjusted HR of major ECG abnormality: 1.39, 95% CI: 1.09-1.76, p < 01). Among the detailed ECG diagnoses, sinus tachycardia, myocardial ischemia, atrial premature complex, and right axis deviation were proposed as important ECG diagnoses. The accuracy of cardiovascular risk stratification was improved when the ECG results were added to the conventional SCORE model (net reclassification index 0.07). ECG helps to predict future cerebrocardiovascular events in CKD patients. ECG diagnosis can be useful for cardiovascular risk evaluation in CKD patients when applied in addition to the conventional risk stratification model.

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