Usefulness of High-frequency QRS Analysis in the Evaluation of Patients With Chest Pain

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT01185899
Recruitment Status : Completed
First Posted : August 20, 2010
Last Update Posted : November 20, 2015
BSP Biological Signal Processing Ltd.
Information provided by (Responsible Party):
Ori Galante, Soroka University Medical Center

August 18, 2010
August 20, 2010
November 20, 2015
August 2010
August 2013   (Final data collection date for primary outcome measure)
diagnosis or rule-out of acute coronary syndrome [ Time Frame: diagnosis or rule-out of ACS will be determined at two time points: 1) upon diacharge when discharge diagnosis is determined. Follow up information will be obtained one month post discharge ]
The primary end-point of the study is definite discharge diagnosis or rule-out of acute coronary syndrome, based on cardiac biomarkers, ECG changes, clinical symptoms and cardiac imaging tests.
Same as current
Complete list of historical versions of study NCT01185899 on Archive Site
Not Provided
Not Provided
Not Provided
Not Provided
Usefulness of High-frequency QRS Analysis in the Evaluation of Patients With Chest Pain
The Usefulness of High-frequency QRS Analysis in the Evaluation of Patients Presenting to the Emergency Department With Chest Pain
Accurate detection of a heart attack (an acute myocardial infarction) is one of the most pressing needs in medicine. Recordings of the electrocardiogram (ECG) (electrical activity of the heart) are one of the first tools used to diagnose a heart attack, but the ECG is not very accurate, especially at the beginning of a heart attack. A new technique for analysing a special part of the ECG may provide more accurate detection of a heart attack. The study hypothesis is that this new technique, the HFQRS analysis, will provide important additional information to that available from the regular ECG.

Chest pain is one of the leading reasons for hospital emergency department (ED) visits worldwide. In the United States (US), over 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. Nearly half of patients hospitalized for unstable angina eventually receive a non-cardiac-related diagnosis. Nonetheless, 2-8% of patients with myocardial infarction (MI) are inappropriately discharged from the ED and mortality rates among patients with an MI who were mistakenly sent home are disproportionately higher (25-33%) than those among patients who were admitted.

Although the ECG is a mainstay in the management of suspected ACS, it has major limitations in both sensitivity and specificity for diagnosis of ACS. The initial 12-lead ECG in the ED is often non-diagnostic in ACS patients, especially in non-ST elevation MI (NSTEMI) and unstable angina (UA), and therefore cannot rule-out ischemia or infarction. Elevation in serum biomarkers is usually not detectable for 4-6 hours after an MI, and some patients do not show a biomarker elevation for as long as 12 hours. Consequently, new clinical tools for early risk stratification of patients with acute chest pain are being sought.

Conventional analysis of ST segment deviations aims to detect repolarization abnormalities. However, ischemia may also bring about changes in the depolarization phase of the electrical cardiac cycle. These depolarization changes can be detected and quantified using analysis of the high-frequency components of the QRS complex (HFQRS). HFQRS analysis has been previously reported to be a sensitive method for detection of demand ischemia during exercise testing. 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.

Observational Model: Cohort
Time Perspective: Prospective
Not Provided
Not Provided
Non-Probability Sample
Patients arriving to the emergency department of Soroka University Medical Center with chest pain that is suspected of being due to acute coronary syndrome
  • Acute Coronary Syndrome
  • Unstable Angina
  • Chest Pain
Not Provided
Suspected ACS patients
Patients presenting with chest pain to the Emergency Department, who are suspected of having ACS, will be asked to participate in the study.
Galante O, Amit G, Granot Y, Davrath LR, Abboud S, Zahger D. High-frequency QRS analysis in the evaluation of chest pain in the emergency department. J Electrocardiol. 2017 Jul - Aug;50(4):457-465. doi: 10.1016/j.jelectrocard.2017.02.009. Epub 2017 Feb 20.

*   Includes publications given by the data provider as well as publications identified by Identifier (NCT Number) in Medline.
August 2013
August 2013   (Final data collection date for primary outcome measure)

Inclusion Criteria:

  • Patients with chest pain, suspected to have ACS
  • Duration of chest pain greater than 20 minutes
  • Time from onset of chest pain less than 12h
  • Signed an informed consent

Exclusion Criteria:

  • History of trauma or any other evident medical cause of chest pain
  • Prior coronary artery bypass graft
  • Pre-excitation syndrome (example WPW)
  • Atrial Fibrillation or significant ventricular arrhythmia
  • Bundle branch block, intraventricular conduction delay or
  • QRS duration greater than 120 ms
  • Implanted pacemaker or defibrillator
  • Patients who received fibrinolytic therapy, glycoprotein IIb or IIIa inhibitors before the initial ECG recording
Sexes Eligible for Study: All
18 Years and older   (Adult, Older Adult)
Contact information is only displayed when the study is recruiting subjects
Not Provided
Not Provided
Ori Galante, Soroka University Medical Center
Ori Galante
BSP Biological Signal Processing Ltd.
Principal Investigator: Doron Zahger, MD Soroka University Medical Center
Soroka University Medical Center
November 2015