Differences in mortality in acute coronary syndrome symptom clusters
Barbara Riegel1, Alexandra L Hanlon, Sharon McKinley
1School of Nursing, University of Pennsylvania, Philadelphia, PA, USA. briegel@nursing.upenn.edu
American Heart Journal
|March 10, 2010
Summary
Identifying acute coronary syndrome (ACS) symptom clusters is crucial. The "Diffuse Symptoms" cluster showed significantly higher mortality, highlighting the need for rapid ACS diagnosis.
Area of Science:
- Cardiology
- Clinical Research
- Symptomology
Background:
- Accurate acute coronary syndrome (ACS) symptom identification is challenging.
- Differences in response times and outcomes based on specific ACS symptoms are not well understood.
- This study aimed to identify ACS symptom clusters and analyze associated characteristics, response times, and outcomes.
Purpose of the Study:
- To identify related symptom clusters in acute coronary syndrome (ACS).
- To determine if patient characteristics, prehospital delay times, and clinical outcomes differ among ACS symptom clusters.
- To improve the timely and accurate diagnosis of ACS.
Main Methods:
- A multisite randomized clinical trial followed 3522 patients with known cardiovascular disease for 2 years.
- Cluster analysis was used to examine 8 presenting symptoms in 331 patients who experienced a confirmed ACS event.
- Differences in symptom cluster characteristics, delay times, and outcomes were analyzed.
Main Results:
- Four ACS symptom clusters were identified: Classic ACS, Pain Symptoms, Stress Symptoms, and Diffuse Symptoms.
- The Diffuse Symptoms cluster was associated with older patients and had a significantly higher 2-year mortality rate (17%) compared to other clusters (2%-5%).
- Prehospital delay times did not significantly differ between symptom clusters.
Conclusions:
- Acute coronary syndrome symptoms frequently present as distinct clusters.
- Uncharacteristic ACS symptom patterns can impede rapid diagnosis and treatment.
- Recognizing common ACS symptom patterns can aid clinicians in faster identification and intervention.
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