The primary objective of this study is to characterize the morphological patterns of high frequency QRS components (HFQRS) in patients with acute myocardial infarction (AMI), including STEMI and NSTEMI, compared to patients without AMI.
Chest pain is one of the leading reasons of hospital emergency department (ED) visits worldwide. In the US, approximately 6 million people annually undergo evaluation in the ED for acute chest pain. Despite the wealth of knowledge available about acute coronary syndrome (ACS), this condition continues to be among the most difficult to predict or diagnose. Misdiagnoses may lead to discharge of patients with ACS, who should have been admitted as well as costly unnecessary hospitalizations of patients who do not have ACS. More than 2/3 of the patients with ACS have unstable angina (UA) or non-ST-elevation myocardial infarction (NSTEMI). Conventional ECG has low sensitivity of less than 50% in diagnosing these conditions. As the initial ECG in the ED is often non-diagnostic in ACS patients, the diagnosis of ST-elevation myocardial infarction (STEMI) during its early stages may also be difficult. Analysis of high-frequency QRS components (HFQRS), which quantifies changes in the depolarization phase of the cardiac cycle, has been previously reported to be a sensitive method for detection of demand ischemia. Preliminary studies have shown that HFQRS-derived indices can also identify supply ischemia caused by prolonged balloon occlusion, and transient ischemic episodes in patients with chest pain.
Study Type
OBSERVATIONAL
Enrollment
50
Soroka University Medical Center
Beersheba, Israel
RECRUITINGDiagnosis of Acute Myocardial Infarction
The primary end-point of the study is diagnosis of acute myocardial infarction, based on cardiac biomarkers, ECG changes clinical symptoms and coronary angiography.
Time frame: Prior to hospitalization release
HFQRS analysis for detecting NSTEMI
To evaluate the usefulness of HFQRS analysis in early detection of non-ST segment elevation myocardial infarction (NSTEMI).
Time frame: Post data processing
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