Evidence map›Paper›PMID 31134468›Full record

ArticleNetherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation2019

UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking.

A Sammani, M Jansen, M Linschoten, A Bagheri, N de Jonge, H Kirkels, L W van Laake, A Vink, J P van Tintelen, D Dooijes and 4 more

Abstract read
In one paragraph

Article in Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
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

27 citing papers in PubMed.

  1. Article
  2. The Dutch cardiomyopathy registry (DCR); rationale and registry design.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2026
    Article
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  8. Yield of family screening for dilated cardiomyopathy: 10-year experience at a multidisciplinary cardiogenetic outpatient clinic.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2025
    Article
  9. Article
  10. Healthcare consumption of patients with left ventricular assist device: real-world data.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2024
    Article
  11. Article
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  14. Article
  15. Article
  16. Life-threatening ventricular arrhythmia prediction in patients with dilated cardiomyopathy using explainable electrocardiogram-based deep neural networks.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2022
    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

14 authors.

A SammaniDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands. a.zabihisammani-2@umcutrecht.nl.
M JansenDepartment of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
M LinschotenDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
A BagheriDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
N de JongeDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
H KirkelsDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
L W van LaakeDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
A VinkDepartment of Pathology, Division of Pathology, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
J P van TintelenDepartment of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
D DooijesDepartment of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
A S J M Te RieleDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
M HarakalovaDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
A F BaasDepartment of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.
F W AsselbergsDepartment of Cardiology, Division Heart & Lungs, University Medical Centre Utrecht, University of Utrecht, Utrecht, The Netherlands.

Funding

Hartstichting 2015T041Hartstichting 2015T058Hartstichting 2016T096Horizon 2020 680969Koninklijke Nederlandse Akademie van Wetenschappen CVON2014-40 DOSISKoninklijke Nederlandse Akademie van Wetenschappen CVON2015-12 eDETECTNederlandse Organisatie voor Wetenschappelijk Onderzoek 016.176.136Universitair Medisch Centrum Utrecht Alexandre SuermanUniversitair Medisch Centrum Utrecht Fellowship Clinical Research TalentWilhelmina Kinderziekenhuis OZF/14
6 · The paper itself

Abstract

introductionDespite major advances in our understanding of genetic cardiomyopathies, they remain the leading cause of premature sudden cardiac death and end-stage heart failure in persons under the age of 60 years. Integrated research databases based on a large number of patients may provide a scaffold for future research. Using routine electronic health records and standardised biobanking, big data analysis on a larger number of patients and investigations are possible. In this article, we describe the UNRAVEL research data platform embedded in routine practice to facilitate research in genetic cardiomyopathies.

designEligible participants with proven or suspected cardiac disease and their relatives are asked for permission to use their data and to draw blood for biobanking. Routinely collected clinical data are included in a research database by weekly extraction. A text-mining tool has been developed to enrich UNRAVEL with unstructured data in clinical notes. PRELIMINARY

resultsThus far, 828 individuals with a median age of 57 years have been included, 58% of whom are male. All data are captured in a temporal sequence amounting to a total of 18,565 electrocardiograms, 3619 echocardiograms, data from over 20,000 radiological examinations and 650,000 individual laboratory measurements.

conclusionIntegration of routine electronic health care in a research data platform allows efficient data collection, including all investigations in chronological sequence. Trials embedded in the electronic health record are now possible, providing cost-effective ways to answer clinical questions. We explicitly welcome national and international collaboration and have provided our protocols and other materials on www.unravelrdp.nl .

Indexed as

Big data analyticsBiobankingCardiomyopathyElectronic health recordMachine learningResearch data platform

Identifiers

PMID31134468
PMCPMC6712144

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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.