Swipe om te navigeren naar een ander artikel
Despite 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.
Eligible 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.
Thus 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.
Integration 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.
Maron BJ, Towbin JA, Thiene G, et al. Contemporary definitions and classification of the cardiomyopathies: an American Heart Association Scientific Statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention. Circulation. 2006;113:1807–16. CrossRef
Elliott P, Andersson B, Arbustini E, et al. Classification of the cardiomyopathies: a position statement from the European Society of Cardiology working group on myocardial and pericardial diseases. Eur Heart J. 2008;29:270–6. CrossRef
van Spaendonck-Zwarts KY, van Rijsingen IAW, van den Berg MP, et al. Genetic analysis in 418 index patients with idiopathic dilated cardiomyopathy: overview of 10 years’ experience. Eur J Heart Fail. 2013;15:628–36. CrossRef
Franaszczyk M, Chmielewski P, Truszkowska G, et al. Titin truncating variants in dilated cardiomyopathy – prevalence and genotype-phenotype correlations. PLoS ONE. 2017;12:e169007. CrossRef
Janin A, N’Guyen K, Habib G, et al. Truncating mutations on myofibrillar myopathies causing genes as prevalent molecular explanations on patients with dilated cardiomyopathy. Clin Genet. 2017;92:616–23. CrossRef
Harakalova M, Kummeling G, Sammani A, et al. A systematic analysis of genetic dilated cardiomyopathy reveals numerous ubiquitously expressed and muscle-specific genes. Eur J Heart Fail. 2015;17:484–93. CrossRef
Lund LH, Edwards LB, Kucheryavaya AY, et al. The Registry of the International Society for Heart and Lung Transplantation: Thirty-second Official Adult Heart Transplantation Report—2015; Focus Theme: Early Graft Failure. J Heart Lung Transplant. 2015;34:1244–54. CrossRef
Hemingway H, Asselbergs FW, Danesh J, et al. Big data from electronic health records for early and late translational cardiovascular research: challenges and potential. Eur Heart J. 2018;39:1481. CrossRef
Denaxas SC, George J, Herrett E, et al. Data Resource Profile: cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER). Int J Epidemiol. 2012;41:1625–38. CrossRef
Jensen PB, Jensen LJ, Brunak S. Mining electronic health records: towards better research applications and clinical care. Nat Rev Genet. 2012;13:395–405. CrossRef
Government of the Netherlands. The Municipal Personal Records Database. 2017 [cited 2017 Oct 3]. Available from: https://www.government.nl/topics/identification-documents/the-municipal-personal-records-database
Seyler C, Meder B, Weis T, et al. TranslatiOnal Registry for CardiomyopatHies (TORCH)—rationale and first results. ESC Hear Fail. IEEE Trans Med Imaging. 2017;4:209:15.
van der Linde MR, Constandse J, van Dijk APJ, et al. Projectgroup DHD diagnosis thesaurus DBC ICD 10. 2018 [cited 2018 Oct 10]. Available from: https://www.nvvc.nl/commissies-werkgroepen/Projectgroep+DHD+diagnose+thesaurus-DBC-ICD+10?utm_source=nvvc&utm_medium=email&utm_campaign=editie892
OHDSI. OMOP Common data Model. 2018 [cited 2018 Oct 15]. Available from: https://www.ohdsi.org/data-standardization/
Skripcak T, Belka C, Bosch W, et al. Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets. Radiother Oncol. 2014;113:303–9. CrossRef
Krittanawong C, Zhang HJ, Wang Z, et al. Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 2017;69:2657–64. CrossRef
Shah SJ, Katz DH, Selvaraj S, et al. Phenomapping for novel classification of heart failure with preserved ejection fraction. Circulation. 2015;131:269–79. CrossRef
Beaulieu-Jones BK, Greene CS, Pooled Resource Open-Access ALS Clinical Trials Consortium. Semi-supervised learning of the electronic health record for phenotype stratification. J Biomed Inform.. IEEE Trans Med Imaging. 2016;64:168–78.
Cowie MR, Blomster JI, Curtis LH, et al. Electronic health records to facilitate clinical research. Clin Res Cardiol. 2017;106:1–9. CrossRef
Weber GM, Mandl KD, Kohane IS. Finding the missing link for big biomedical data. JAMA. 2014;311:2479–80.
- UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking
N. de Jonge
L. W. van Laake
J. P. van Tintelen
A. S. J. M. te Riele
A. F. Baas
F. W. Asselbergs
- Bohn Stafleu van Loghum