Literature DB >> 24122522

Screening entire health system ECG databases to identify patients at increased risk of death.

David G Strauss1, Nathan Mewton, Richard L Verrier, Bruce D Nearing, Francis E Marchlinski, Tony Killian, John Moxley, Larisa G Tereshchenko, Katherine C Wu, Raimond Winslow, Christopher Cox, Peter M Spooner, João A C Lima.   

Abstract

BACKGROUND: Current methods to identify patients at higher risk for sudden cardiac death, primarily left ventricular ejection fraction ≤35%, miss ≈80% of patients who die suddenly. We tested the hypothesis that patients with elevated QRS-scores (index of myocardial scar) and wide QRS-T angles (index abnormal depolarization-repolarization relationship) have high 1-year all-cause mortality and could be further risk stratified with clinical characteristics. METHODS AND
RESULTS: We screened all 12-lead ECGs over 6 months at 2 large hospital systems and analyzed clinical characteristics and 1-year mortality. Patients with ECGs obtained in hospital areas with known high mortality rates were excluded. At the first hospital, QRS-score ≥5 and QRS-T angle ≥105° identified 8.0% of patients and was associated with an odds ratio of 2.79 (95% confidence interval, 2.10-3.69) for 1-year mortality compared with patients below both ECG thresholds (13.9% versus 5.5% death rate). Left ventricular ejection fraction was >35% in 82% of the former group of patients, and addition of ECG measures to left ventricular ejection fraction increased the discrimination of death risk (P<0.0001). At the second hospital, the odds ratio was 2.42 (1.95-3.01) for 1-year mortality (8.8% versus 3.8%). Adjustment for patient characteristics eliminated interhospital differences. Multivariable adjusted odds ratio combining data from both hospitals was 1.53 (1.28-1.83). Increasing heart rate and chronic renal impairment further predicted mortality.
CONCLUSIONS: Screening hospital ECG databases with QRS-scoring and QRS-T angle analysis identifies patients with high 1-year all-cause mortality and predominantly preserved left ventricular ejection fraction. This approach may represent a widely available method to identify patients at increased risk of death.

Entities:  

Keywords:  arrhythmias, cardiac; death; electrocardiography; fibrosis; mass screening

Mesh:

Year:  2013        PMID: 24122522      PMCID: PMC3992472          DOI: 10.1161/CIRCEP.113.000411

Source DB:  PubMed          Journal:  Circ Arrhythm Electrophysiol        ISSN: 1941-3084


  24 in total

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2.  Microvolt T-wave alternans testing has a role in arrhythmia risk stratification.

Authors:  Richard L Verrier; Thomas Klingenheben; Marek Malik; Nabil El-Sherif; Derek V Exner; Stefan H Hohnloser; Takanori Ikeda; Juan Pablo Martínez; Sanjiv M Narayan; Tuomo Nieminen; David S Rosenbaum
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3.  Spatial QRS-T angle predicts cardiac death in a clinical population.

Authors:  Takuya Yamazaki; Victor F Froelicher; Jonathan Myers; Sung Chun; Paul Wang
Journal:  Heart Rhythm       Date:  2005-01       Impact factor: 6.343

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Review 6.  Biomarkers in heart failure.

Authors:  Eugene Braunwald
Journal:  N Engl J Med       Date:  2008-05-15       Impact factor: 91.245

7.  Characterization of the peri-infarct zone by contrast-enhanced cardiac magnetic resonance imaging is a powerful predictor of post-myocardial infarction mortality.

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Journal:  Circulation       Date:  2006-06-26       Impact factor: 29.690

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9.  Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction.

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Journal:  Circulation       Date:  2007-03-26       Impact factor: 29.690

10.  Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate.

Authors:  Andrew S Levey; Josef Coresh; Tom Greene; Lesley A Stevens; Yaping Lucy Zhang; Stephen Hendriksen; John W Kusek; Frederick Van Lente
Journal:  Ann Intern Med       Date:  2006-08-15       Impact factor: 25.391

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  16 in total

1.  Associations of electrocardiographic P-wave characteristics with left atrial function, and diffuse left ventricular fibrosis defined by cardiac magnetic resonance: The PRIMERI Study.

Authors:  Theingi Tiffany Win; Bharath Ambale Venkatesh; Gustavo J Volpe; Nathan Mewton; Patricia Rizzi; Ravi K Sharma; David G Strauss; Joao A Lima; Larisa G Tereshchenko
Journal:  Heart Rhythm       Date:  2014-10-14       Impact factor: 6.343

Review 2.  The potential of electrocardiography for cardiac risk prediction in chronic and end-stage kidney disease.

Authors:  Sofia Skampardoni; Dimitrios Poulikakos; Marek Malik; Darren Green; Philip A Kalra
Journal:  Nephrol Dial Transplant       Date:  2019-07-01       Impact factor: 5.992

3.  Automatically computed ECG algorithm for the quantification of myocardial scar and the prediction of mortality.

Authors:  Patrick Badertscher; Ivo Strebel; Ursina Honegger; Nicolas Schaerli; Deborah Mueller; Christian Puelacher; Max Wagener; Roger Abächerli; Joan Walter; Zaid Sabti; Lorraine Sazgary; Stella Marbot; Jeanne du Fay de Lavallaz; Raphael Twerenbold; Jasper Boeddinghaus; Thomas Nestelberger; Nikola Kozhuharov; Tobias Breidthardt; Samyut Shrestha; Dayana Flores; Carmela Schumacher; Damian Wild; Stefan Osswald; Michael J Zellweger; Christian Mueller; Tobias Reichlin
Journal:  Clin Res Cardiol       Date:  2018-04-17       Impact factor: 5.460

4.  Screening entire healthcare system ECG database: Association of deep terminal negativity of P wave in lead V1 and ECG referral with mortality.

Authors:  Allison Junell; Jason Thomas; Lauren Hawkins; Jiri Sklenar; Trevor Feldman; Charles A Henrikson; Larisa G Tereshchenko
Journal:  Int J Cardiol       Date:  2016-11-10       Impact factor: 4.164

5.  WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data.

Authors:  Raimond L Winslow; Stephen Granite; Christian Jurado
Journal:  Comput Sci Eng       Date:  2016-08-24       Impact factor: 2.080

6.  Electrocardiographic QRS-T angle and the risk of incident silent myocardial infarction in the Atherosclerosis Risk in Communities study.

Authors:  Zhu-Ming Zhang; Pentti M Rautaharju; Ronald J Prineas; Larisa Tereshchenko; Elsayed Z Soliman
Journal:  J Electrocardiol       Date:  2017-05-04       Impact factor: 1.438

7.  Electrophysiologic Substrate and Risk of Mortality in Incident Hemodialysis.

Authors:  Larisa G Tereshchenko; Esther D Kim; Andrew Oehler; Lucy A Meoni; Elyar Ghafoori; Tejal Rami; Maggie Maly; Muammar Kabir; Lauren Hawkins; Gordon F Tomaselli; Joao A Lima; Bernard G Jaar; Stephen M Sozio; Michelle Estrella; W H Linda Kao; Rulan S Parekh
Journal:  J Am Soc Nephrol       Date:  2016-04-29       Impact factor: 10.121

8.  Electrocardiographic Markers and the Left Ventricular Ejection Fraction have Cumulative Effects on Risk of Sudden Cardiac Death.

Authors:  Kyndaron Reinier; Kumar Narayanan; Audrey Uy-Evanado; Carmen Teodorescu; Harpriya Chugh; Wendy J Mack; Karen Gunson; Jonathan Jui; Sumeet S Chugh
Journal:  JACC Clin Electrophysiol       Date:  2015-12-01

9.  Screening for Cardiac Magnetic Resonance Scar Features by 12-Lead ECG, in Patients with Preserved Ejection Fraction.

Authors:  Nathan Mewton; David G Strauss; Patricia Rizzi; Richard L Verrier; Chia Ying Liu; Larisa G Tereshchenko; Bruce Nearing; Gustavo J Volpe; Francis E Marchlinski; John Moxley; Tony Killian; Katherine C Wu; Peter Spooner; João A C Lima
Journal:  Ann Noninvasive Electrocardiol       Date:  2016-01       Impact factor: 1.468

10.  Number of P-wave fragmentations on P-SAECG correlates with infiltrated atrial fat.

Authors:  Sindhoora Murthy; Patricia Rizzi; Nathan Mewton; David G Strauss; Chia Y Liu; Gustavo Jardim Volpe; Francis E Marchlinski; Peter Spooner; Ronald D Berger; Peter Kellman; Joao A C Lima; Larisa G Tereshchenko
Journal:  Ann Noninvasive Electrocardiol       Date:  2013-09-09       Impact factor: 1.468

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