Automatically computed ECG algorithm for the quantification of myocardial scar and the prediction of mortality
Myocardial scar is associated with adverse cardiac outcomes. The Selvester QRS-score was developed to estimate myocardial scar from the 12-lead ECG, but its manual calculation is difficult. An automatically computed QRS-score would allow identification of patients with myocardial scar and an increased risk of mortality.
To assess the diagnostic and prognostic value of the automatically computed QRS-score.
The diagnostic value of the QRS-score computed automatically from a standard digital 12-lead was prospectively assessed in 2742 patients with suspected myocardial ischemia referred for myocardial perfusion imaging (MPI). The prognostic value of the QRS-score was then prospectively tested in 1151 consecutive patients presenting to the emergency department (ED) with suspected acute heart failure (AHF).
Overall, the QRS-score was significantly higher in patients with more extensive myocardial scar: the median QRS-score was 3 (IQR 2–5), 4 (IQR 2–6), and 7 (IQR 4–10) for patients with 0, 5–20 and > 20% myocardial scar as quantified by MPI (p < 0.001 for all pairwise comparisons). A QRS-score ≥ 9 (n = 284, 10%) predicted a large scar defined as > 20% of the LV with a specificity of 91% (95% CI 90–92%). Regarding clinical outcomes in patients presenting to the ED with symptoms suggestive of AHF, mortality after 1 year was 28% in patients with a QRS-score ≥ 3 as opposed to 20% in patients with a QRS-score < 3 (p = 0.001).
The QRS-score can be computed automatically from the 12-lead ECG for simple, non-invasive and inexpensive detection and quantification of myocardial scar and for the prediction of mortality.
http://www.clinicaltrials.gov. Identifier, NCT01838148 and NCT01831115.
KeywordsSelvester QRS-score ECG Myocardial scar Heart failure Cardiac imaging
The authors thank the patients who participated in the study and the staff of the Department of Nuclear Medicine.
Compliance with ethical standards
Conflict of interest
Dr. Mueller has received research support from the Swiss National Science Foundation, the Swiss Heart Foundation, the Cardiovascular Research Foundation Basel, Abbott, Beckman Coulter, BRAHMS, Roche, Siemens. and the University Hospital Basel, as well as speaker honoraria from Abbott, ALERE, Astra Zeneca, BG Medicine, Biomerieux, Brahms, Cardiorentis, Lilly, Novartis, Roche, and Siemens. Dr. Reichlin has received research grants from the Goldschmidt-Jacobson Foundation, the Swiss National Science Foundation (PASMP3-136995) the Swiss Heart Foundation, the Professor Max Cloëtta Foundation, the Cardiovascular Research Foundation Basel, the University of Basel and the University Hospital Basel as well as speaker honoraria from Brahms and Roche. Dr. Twerenbold has received research support from the Swiss National Science Foundation (P300PB-167803/1) and speaker honoraria/consulting honoraria from Roche, Abbott, Siemens and Brahms. Dr. Boeddinghaus has received speaker honoraria from Siemens. All other authors declare that they have no conflict of interest with this study.
- 3.Ponikowski P, Voors AA, Anker SD et al (2016) 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of. Eur Heart J 37(27):2129–2200. https://doi.org/10.1093/eurheartj/ehw128 CrossRefPubMedGoogle Scholar
- 4.Schmidt A, Azevedo CF, Cheng A et al (2007) Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction. Circulation 115(15):2006–2014. https://doi.org/10.1161/CIRCULATIONAHA.106.653568 CrossRefPubMedPubMedCentralGoogle Scholar
- 9.Strauss DG, Selvester RH (2009) The QRS complex—a biomarker that “images” the heart: QRS scores to quantify myocardial scar in the presence of normal and abnormal ventricular conduction. J Electrocardiol 42(1):85–96. https://doi.org/10.1016/j.jelectrocard.2008.07.011 CrossRefPubMedGoogle Scholar
- 11.Yokota H, Heidary S, Katikireddy CK et al (2008) Quantitative characterization of myocardial infarction by cardiovascular magnetic resonance predicts future cardiovascular events in patients with ischemic cardiomyopathy. J Cardiovasc Magn Reson 10(1):17. https://doi.org/10.1186/1532-429X-10-17 CrossRefPubMedPubMedCentralGoogle Scholar
- 18.Zellweger MJ, Maraun M, Osterhues HH et al (2014) Progression to overt or silent CAD in asymptomatic patients with diabetes mellitus at high coronary risk: main findings of the prospective multicenter BARDOT trial with a pilot randomized treatment substudy. JACC Cardiovasc Imaging 7(10):1001–1010. https://doi.org/10.1016/j.jcmg.2014.07.010 CrossRefPubMedGoogle Scholar
- 22.Loring Z, Chelliah S, Selvester RH, Wagner G, Strauss DG (2011) A detailed guide for quantification of myocardial scar with the Selvester QRS score in the presence of electrocardiogram confounders. J Electrocardiol 44(5):544–554. https://doi.org/10.1016/j.jelectrocard.2011.06.008 CrossRefPubMedPubMedCentralGoogle Scholar
- 25.Geerse DA, Wu KC, Gorgels AP, Zimmet J, Wagner GS, Miller JM (2009) Comparison between contrast-enhanced magnetic resonance imaging and selvester qrs scoring system in estimating changes in infarct size between the acute and chronic phases of myocardial infarction. Ann Noninvasive Electrocardiol 14(4):360–365. https://doi.org/10.1111/j.1542-474X.2009.00327.x CrossRefPubMedGoogle Scholar
- 30.Horáček BM, Warren JW, Albano A et al (2006) Development of an automated Selvester scoring system for estimating the size of myocardial infarction from the electrocardiogram. J Electrocardiol 39(2):162–168. https://doi.org/10.1016/j.jelectrocard.2005.08.013 CrossRefPubMedGoogle Scholar
- 33.Abächerli R, Twerenbold R, Boeddinghaus J et al (February 2017) Diagnostic and prognostic values of the V-index, a novel ECG marker quantifying spatial heterogeneity of ventricular repolarization, in patients with symptoms suggestive of non-ST-elevation myocardial infarction. Int J Cardiol. https://doi.org/10.1016/j.ijcard.2017.01.151 Google Scholar
- 34.Wagner A, Mahrholdt H, Holly TA et al (2003) Contrast-enhanced MRI and routine single photon emission computed tomography (SPECT) perfusion imaging for detection of subendocardial myocardial infarcts: an imaging study. Lancet 361(9355):374–379. https://doi.org/10.1016/S0140-6736(03)12389-6 CrossRefPubMedGoogle Scholar