Evidence map›Paper›PMID 35187560›Full record

ArticleEuropean heart journal2022

QRS micro-fragmentation as a mortality predictor.

Katerina Hnatkova, Irena Andršová, Tomáš Novotný, Annie Britton, Martin Shipley, Bert Vandenberk, David J Sprenkeler, Juhani Junttila, Tobias Reichlin, Simon Schlögl and 10 more

Open access · hybridAbstract read
In one paragraph

Article in European heart journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 28 citations in OpenAlex.

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  12. Development of autonomic heart rate modulations during childhood and adolescence.Pflugers Archiv : European journal of physiology · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 11 institutions in 9 countries.

Katerina HnatkovaNational Heart and Lung Institute, Imperial College, ICTEM, Hammersmith Campus, 72 Du Cane Road, Shepherd's Bush, London W12 0NN, UK.ORCID 0000-0002-0159-1610
Irena AndršováDepartment of Internal Medicine and Cardiology, University Hospital Brno, Brno, Czech Republic.ORCID 0000-0001-8973-5967
Tomáš NovotnýDepartment of Internal Medicine and Cardiology, University Hospital Brno, Brno, Czech Republic.ORCID 0000-0002-0292-4034
Annie BrittonResearch Department of Epidemiology and Public Health, University College London, UK.
Martin ShipleyResearch Department of Epidemiology and Public Health, University College London, UK.
Bert VandenberkDepartment of Cardiovascular Sciences, University of Leuven, Leuven, Belgium.ORCID 0000-0001-8296-920X
David J SprenkelerDepartment of Medical Physiology, University Medical Center Utrecht, Utrecht, The Netherlands.ORCID 0000-0003-1572-280X
Juhani JunttilaMedical Research Center Oulu, University Central Hospital of Oulu and University of Oulu, Oulu, Finland.ORCID 0000-0002-8896-1281
Tobias ReichlinDepartment of Cardiology, Inselspital, Bern University Hospital, Bern, Switzerland.ORCID 0000-0002-7197-8415
Simon SchlöglDepartment of Cardiology and Pneumology, University Medical Center, Göttingen, Germany.
Marc A VosDepartment of Medical Physiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Tim FriedeGerman Center of Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany.ORCID 0000-0001-5347-7441
Axel BauerUniversity Hospital for Internal Medicine III, Medical University Innsbruck, Innsbruck, Austria.ORCID 0000-0001-9201-8555
Heikki V HuikuriMedical Research Center Oulu, University Central Hospital of Oulu and University of Oulu, Oulu, Finland.
Rik WillemsDepartment of Cardiovascular Sciences, University of Leuven, Leuven, Belgium.ORCID 0000-0002-5469-9609
Georg SchmidtKlinikum rechts der Isar, Technical University of Munich, Munich, Germany.ORCID 0000-0003-3692-5243
Michael R FranzVeteran Affairs and Georgetown University Medical Centers, Washington, DC, USA.
Christian SticherlingDepartment of Cardiology, University Hospital of Basel, Basel, Switzerland.ORCID 0000-0001-8428-7050
Markus ZabelDepartment of Cardiology and Pneumology, University Medical Center, Göttingen, Germany.ORCID 0000-0003-0895-4602
Marek MalikNational Heart and Lung Institute, Imperial College, ICTEM, Hammersmith Campus, 72 Du Cane Road, Shepherd's Bush, London W12 0NN, UK.ORCID 0000-0002-3792-1407
Masaryk University · CZUniversitätsmedizin Göttingen · DEKU Leuven · BEOulu University Hospital · FIUniversity College London · GBUniversity Medical Center Utrecht · NLGeorgetown University · USTUM Klinikum · DEUniversity Hospital Innsbruck · ATUniversity Hospital of Basel · CHUniversity Hospital of Bern · CH

Funding

British Heart Foundation NH/16/2/32499Medical Research Council MR/M006638/1Medical Research Council MR/R024227/1Medical Research Council MR/S011676/1
6 · The paper itself

Abstract

aimsFragmented QRS complex with visible notching on standard 12-lead electrocardiogram (ECG) is understood to represent depolarization abnormalities and to signify risk of cardiac events. Depolarization abnormalities with similar prognostic implications likely exist beyond visual recognition but no technology is presently suitable for quantification of such invisible ECG abnormalities. We present such a technology. METHODS AND

resultsA signal processing method projects all ECG leads of the QRS complex into optimized three perpendicular dimensions, reconstructs the ECG back from this three-dimensional projection, and quantifies the difference (QRS 'micro'-fragmentation, QRS-μf) between the original and reconstructed signals. QRS 'micro'-fragmentation was assessed in three different populations: cardiac patients with automatic implantable cardioverter-defibrillators, cardiac patients with severe abnormalities, and general public. The predictive value of QRS-μf for mortality was investigated both univariably and in multivariable comparisons with other risk factors including visible QRS 'macro'-fragmentation, QRS-Mf. The analysis was made in a total of 7779 subjects of whom 504 have not survived the first 5 years of follow-up. In all three populations, QRS-μf was strongly predictive of survival (P < 0.001 univariably, and P < 0.001 to P = 0.024 in multivariable regression analyses). A similar strong association with outcome was found when dichotomizing QRS-μf prospectively at 3.5%. When QRS-μf was used in multivariable analyses, QRS-Mf and QRS duration lost their predictive value.

conclusionIn three populations with different clinical characteristics, QRS-μf was a powerful mortality risk factor independent of several previously established risk indices. Electrophysiologic abnormalities that contribute to increased QRS-μf values are likely responsible for the predictive power of visible QRS-Mf.

Indexed as

ElectrocardiographyHumansPredictive Value of TestsPrognosisRisk FactorsElectrocardiogramFragmentationMortality predictionQRS complex

Identifiers

PMID35187560
PMCPMC9584751
OpenAlexW4210898588

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Registered trials

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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.