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The Impact of Cluster-Type Risk Factors on Adverse Clinical Prognosis in Patients with Coronary Artery Disease: A Secondary Data Analysis

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KMID : 0367020200320020156
¾öÀξ֠( Uhm In-Ae ) - Hanyang University Graduate School of Nursing

Ȳ¼±¿µ ( Hwang Seon-Young ) - Hanyang University School of Nursing

Abstract

Purpose: Identify the cluster-type risk factors when disease occurs in patients with coronary artery disease (CAD) and examine the impact of the cluster-type on adverse clinical prognosis in CAD patients.

Methods: Secondary data analysis was utilized with data collected from electronic medical records of patients who underwent percutaneous coronary intervention in a university hospital from 2011 to 2015 and who were on an outpatient follow-up visit as of January 2020. The K-means cluster analysis was performed on seven cardiovascular risk factors. Major adverse cardiac events (MACEs), including hospitalization due to restenosis or cardiac-related death, was required in clinical prognosis. The Cox proportional-hazard regression and Kaplan-Meier survival analyses were used.

Results: Cluster analysis identified three clusters of ¡®obesity and family history¡¯ (n=150), ¡®smoking and drinking¡¯ (n=178), and ¡®chronic disease¡¯ (n=190). The MACEs occurred in 10.4% of study subjects. When the ¡®obesity and family history¡¯ cluster (62.94¡¾12.09 years) was used as a reference, the relative risk of MACEs was 2.57 times higher in the ¡®smoking and drinking¡¯ cluster (62.63¡¾13.31 years) and 2.41 times higher in the ¡®chronic disease¡¯ cluster (70.90¡¾10.30 years).
Conclusion: Cluster-type risk factors are necessary when considering secondary prevention strategies for MACEs in patients with CAD. Patients with smoking, drinking, and chronic diseases are especially required to improve their lifestyles and to regularly monitor their management of underlying diseases during follow-up periods.
KeyWords
°ü»óµ¿¸ÆÁúȯ, °æÇÇÀû°ü»óµ¿¸ÆÁßÀç¼ú, ÁÖ¿ä ºÎÁ¤Àû ½ÉÀå»ç°Ç, ¿¹ÈÄ, ±ºÁýºÐ¼®
Coronary artery disease, Percutaneous coronary intervention, Major adverse cardiac events, Prognosis, Cluster analysis
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