Evidence map›Paper›PMID 25187521›Full record

ArticleJournal of the American Heart Association2014

A novel method to capture the onset of dynamic electrocardiographic ischemic changes and its implications to arrhythmia susceptibility.

Omid Sayadi, Dheeraj Puppala, Nosheen Ishaque, Rajiv Doddamani, Faisal M Merchant, Conor Barrett, Jagmeet P Singh, E Kevin Heist, Theofanie Mela, Juan Pablo Martínez and 2 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in Journal of the American Heart Association, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 17 citations in OpenAlex.

  1. Trial
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  4. Review
  5. Utility of a Smartphone-Based System (cvrPhone) in Estimating Minute Ventilation from Electrocardiographic Signals.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 2 countries.

Omid SayadiDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA (O.S., D.P., N.I., R.D., A.A.A.).
Dheeraj PuppalaDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA (O.S., D.P., N.I., R.D., A.A.A.).
Nosheen IshaqueDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA (O.S., D.P., N.I., R.D., A.A.A.).
Rajiv DoddamaniDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA (O.S., D.P., N.I., R.D., A.A.A.).
Faisal M MerchantCardiology Division, Emory University School of Medicine, Atlanta, GA (F.M.M.).
Conor BarrettDivision of Cardiology, Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA (C.B., J.P.S., K.H., T.M.).
Jagmeet P SinghDivision of Cardiology, Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA (C.B., J.P.S., K.H., T.M.).
E Kevin HeistDivision of Cardiology, Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA (C.B., J.P.S., K.H., T.M.).
Theofanie MelaDivision of Cardiology, Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA (C.B., J.P.S., K.H., T.M.).
Juan Pablo MartínezBiomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research, IIS Aragón, University of Zaragoza, Zaragoza, Aragon, Spain (J.P.M., P.L.) Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Aragon, Spain (J.P.M., P.L.).
Pablo LagunaBiomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research, IIS Aragón, University of Zaragoza, Zaragoza, Aragon, Spain (J.P.M., P.L.) Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Aragon, Spain (J.P.M., P.L.).
Antonis A ArmoundasDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA (O.S., D.P., N.I., R.D., A.A.A.).
Massachusetts General Hospital · USBiomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine · ESHarvard University · USEmory University · US

Funding

Harvard Clinical and Translational Science Center (UL1)UL1TR000170 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2012 to 2013
$31.4M
Advanced Pacing Methods for Treating Heart Rhythm DisturbancesR21AG035128 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI ARMOUNDAS, ANTONIS A · 2010 to 2011
$372k
NCATS NIH HHS 8UL1TR000170-05NCATS NIH HHS UL1 TR000170NIA NIH HHS R21 AG035128
6 · The paper itself

Abstract

backgroundThis study investigates the hypothesis that morphologic analysis of intracardiac electrograms provides a sensitive approach to detect acute myocardial infarction or myocardial infarction-induced arrhythmia susceptibility. Large proportions of irreversible myocardial injury and fatal ventricular tachyarrhythmias occur in the first hour after coronary occlusion; therefore, early detection of acute myocardial infarction may improve clinical outcomes. METHODS AND

resultsWe developed a method that uses the wavelet transform to delineate electrocardiographic signals, and we have devised an index to quantify the ischemia-induced changes in these signals. We recorded body-surface and intracardiac electrograms at baseline and following myocardial infarction in 24 swine. Statistically significant ischemia-induced changes after the initiation of occlusion compared with baseline were detectable within 30 seconds in intracardiac left ventricle (P<0.0016) and right ventricle-coronary sinus (P<0.0011) leads, 60 seconds in coronary sinus leads (P<0.0002), 90 seconds in right ventricle leads (P<0.0020), and 360 seconds in body-surface electrocardiographic signals (P<0.0022). Intracardiac leads exhibited a higher probability of detecting ischemia-induced changes than body-surface leads (P<0.0381), and the right ventricle-coronary sinus configuration provided the highest sensitivity (96%). The 24-hour ECG recordings showed that the ischemic index is statistically significantly increased compared with baseline in lead I, aVR, and all precordial leads (P<0.0388). Finally, we showed that the ischemic index in intracardiac electrograms is significantly increased preceding ventricular tachyarrhythmic events (P<0.0360).

conclusionsWe present a novel method that is capable of detecting ischemia-induced changes in intracardiac electrograms as early as 30 seconds following myocardial infarction or as early as 12 minutes preceding tachyarrhythmic events.

Indexed as

Signal Processing, Computer-AssistedAnimalsBody Surface Potential MappingDisease Models, AnimalDisease ProgressionEarly DiagnosisElectrocardiographyElectrocardiography, AmbulatoryMaleMyocardial IschemiaRandom AllocationSensitivity and SpecificitySwineTachycardia, VentricularTime FactorsECG delineationintracardiac signalsischemic indexmyocardial infarctionwavelet transform

Identifiers

PMID25187521
PMCPMC4323775
OpenAlexW2102363854

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.