Korean Circ J.  2012 Jan;42(1):16-22. 10.4070/kcj.2012.42.1.16.

Atypical Symptom Cluster Predicts a Higher Mortality in Patients With First-Time Acute Myocardial Infarction

• Hwang SY
• Ahn YG
• Jeong MH

• KMID: 2297903
• DOI: http://doi.org/10.4070/kcj.2012.42.1.16

Abstract

BACKGROUND AND OBJECTIVES
Identifying symptom clusters of acute myocardial infarction (AMI) and their clinical significance may be useful in guiding treatment seeking behaviors and in planning treatment strategy. The aim of this study was to identify clusters of acute symptoms and their associated factors that manifested in patients with first-time AMI, and to compare clinical outcomes among cluster groups within 1-year of follow-up.
SUBJECTS AND METHODS
A total of 391 AMI patients were interviewed individually using a structured questionnaire for acute and associated symptoms between March 2008 and June 2009 in Korea.
RESULTS
Among 14 acute symptoms, three distinct clusters were identified by Latent Class Cluster Analysis: typical chest symptom (57.0%), multiple symptom (27.9%), and atypical symptom (15.1%) clusters. The cluster with atypical symptoms was characterized by the least chest pain (3.4%) and moderate frequencies (31-61%) of gastrointestinal symptoms, weakness or fatigue, and shortness of breath; they were more likely to be older, diabetic and to have worse clinical markers at hospital presentation compared with those with other clusters. Cox proportional hazards regression analysis showed that, when age and gender were adjusted for, the atypical symptom cluster significantly predicted a higher risk of 1-year mortality compared to the typical chest pain cluster (hazard ratio 3.288, 95% confidence interval 1.087-9.943, p=0.035).
CONCLUSION
Clusters of symptoms can be utilized in guiding a rapid identification of symptom patterns and in detecting higher risk patients. Intensive treatment should be considered for older and diabetic patients with atypical presentation.

Keyword

Acute myocardial infarction; Acute coronary syndrome; Symptom; Cluster analysis

MeSH Terms

Acute Coronary Syndrome
Biomarkers
Chest Pain
Cluster Analysis
Fatigue
Humans
Myocardial Infarction
Regression Analysis
Thorax
Surveys and Questionnaires

Figure

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  Fig. 1 Symptom distribution by clustered groups.

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