Big Data

For Better Hearts

BigData@Heart

Publications

 

Research papers

 

 

  1. Sam H.A. Muller. The social licence for data-intensive health research: towards co-creation, public value and trust. BMC Medical Ethics. 10 August 2021.  https://doi.org/10.1186/s12910-021-00677-5
     

  2. Angela Wood. Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource. BMJ. 07 April 2021. https://doi.org/10.1136/bmj.n826
     

  3. Amitava Banerjee. Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility. BMC Medicine.  https://doi.org/10.1186/s12916-021-01940-7
     

  4. Alicia Uijl. Identification of Distinct Phenotypic Clusters in Heart Failure with Preserved Ejection Fraction. Eur. J H Failure. 29 March 2021. https://doi.org/10.1002/ejhf.2169
     

  5. Zhujie Gu. Statistical integration of two omics datasets using GO2PLS. BMC Bioinformatics. 18 March 2021. https://doi.org/10.1186/s12859-021-03958-3
     

  6. Michail Katsoulis. Estimating the Effect of Reduced Attendance at Emergency Departments for Suspected Cardiac Conditions on Cardiac Mortality During the COVID-19 Pandemic.  Circulation: Cardiovascular Quality and Outcomes. 20 December 2020. https://doi.org/10.1161/CIRCOUTCOMES.120.007085
     

  7. Gianluigi Savarese. Association between Renin-Angiotensin-Aldosterone system inhibitor use and COVID-19 Hospitalization and death: A 1,4 million patient Nation-Wide registry analysis. Eur. J H Failure. 22 November 2020. https://doi.org/10.1002/ejhf.2060
     

  8. Lorenzo Dall’Olio. Prediction of vascular aging based on smartphone acquired PPG signals. Scientific Reports. 12 November 2020. https://doi.org/10.1038/s41598-020-76816-6
     

  9. Olga E. Titova. Sleep duration and risk of overall and 22 site‐specific cancers: A Mendelian randomization study. Cancer Epidemiology. 07 September 2020. https://doi.org/10.1002/ijc.33286
     

  10. Amand Schmidt. Genetic drug target validation using Mendelian randomisation. Nature Communications. 26 June 2020. https://doi.org/10.1038/s41467-020-16969-0

     
  11. Alicia Uijl. A registry‐based algorithm to predict ejection fraction in patients with heart failure. ESC Heart Failure. 17 June 2020. https://doi.org/10.1002/ehf2.12779
     
  12. Cristina Lopez. Impact of Acute Hemoglobin Falls in Heart Failure Patients: A Population Study. J Clin Med. 15 June 2020. https://doi.org/10.3390/jcm9061869
     
  13. Amitava Banerjee. Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. The Lancet. 12 May 2020. https://doi.org/10.1016/S0140-6736(20)30854-0
     
  14. Gianluigi Savarese. Comorbidities and cause-specific outcomes in heart failure across the ejection fraction spectrum: A blueprint for clinical trial design. International Journal of Cardiology. 30 April 2020. https://doi.org/10.1016/j.ijcard.2020.04.068
     
  15. Hose Luis Holgado. Acute kidney injury in heart failure: a population study. ESC Heart Failure. 14 February 2020. https://doi.org/10.1002/ehf2.12595
     
  16. William H Seligman. Development of an international standard set of outcome measures for patients with atrial. European Heart Journal. 29 January 2020. https://doi.org/10.1093/eurheartj/ehz871
     
  17. Sonia Shah. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure. Nature Communications. 09 January 2020. doi.org/10.1038/s41467-019-13690-5 
     
  18. Shona Kalkman. Responsible data sharing in a big data-driven translational research platform: lessons learned. BMC Medical Informatics and Decision Making. 30 December 2019. doi.org/10.1186/s12911-019-1001-y
     
  19. Daniel M. Bean. Semantic computational analysis of anticoagulation use in atrial fibrillation from real world data. Plos One. 25 November 2019. doi.org/10.1371/journal.pone.0225625 
     
  20. Laura Pasea. Bleeding in cardiac patients prescribed antithrombotic drugs: Electronic health record phenotyping algorithms, incidence, trends and prognosis. BMC Medicine. 20 November 2019. doi.org/10.1186/s12916-019-1438-y 
     
  21. Shona Kalkman. Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. Journal of Medical Ethics. 12 November 2019. http://dx.doi.org/10.1136/medethics-2019-105651  
     
  22. Schrage B, Uijl A, Benson L, Westermann D, Ståhlberg M, Stolfo D, Dahstrom U, Linde C, Braunschweig F, and Savarese G. Association between use of primary prevention implantable cardioverter-defibrillators and mortality in patients with heart failure. A prospective propensity-score matched analysis from the Swedish heart failure registry. Circulation-Heart Failure. 3 September 2019. doi.org/10.1161/CIRCULATIONAHA.119.043012
     
  23. Stolfo D, Uijl A, Schrage B, Fudim M, Asselbergs FW, Koudstaal S, Sinagra G, Dahlstrom U, Rosano G, and Savarese G. Association between beta-blocker use and mortality/morbidity in older patients with heart failure with reduced ejection fraction. A propensity score-matched analysis from the Swedish Heart Failure Registry. European Journal of Heart Failure. 3 September 2019. https://doi.org/10.1002/ejhf.1615
     
  24. Qianrui Li. Diagnosis and treatment for hyperuricemia and gout: a systematic review of clinical practice guidelines and consensus statements. BMJ Open.  24 August 2019. http://dx.doi.org/10.1136/bmjopen-2018-026677
     
  25. Banerjee A, Allan V, Denaxas S, Shah A, Kotecha D, Lambiase PD, Jacob J, Lund LH,Hemingway H. Subtypes of atrial fibrillation with concomitant valvular heart disease derived from electronic health records: phenotypes, population prevalence, trends and prognosis. Europace. 14 July 2019. doi.org/10.1093/europace/euz220
     
  26. Spiros Denaxas. UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. Journal of the American Medical Informatics Association. 22 July 2019. doi.org/10.1093/jamia/ocz105 
     
  27. Shah S, Henry A, Roselli C, et al. Genome-wide association study provides new insights into the genetic architecture and pathogenesis of heart failure. BioRivix, 10 July 2019. doi.org/10.1101/682013
     
  28. Elias Allara. Genetic determinants of lipids and cardiovascular disease outcomes: a wide-angled Mendelian randomization investigation​. Circ Genom Precis Med. 12 December 2019. doi: 10.1161/CIRCGEN.119.002711 

  29. Kalkman S, Mostert M, Gerlinger C, Van Delden JJM, Van Thiel GJMW. Responsible data sharing in international health research: a systematic review of principles and norms. BMC Medical Ethics. 28 March 2019. doi.org/10.1186/s12910-019-0359-9
     
  30. Michiel Rienstra Dipak Kotecha Dirk J. van Veldhuisen. Heart rate in patients with atrial fibrillation and heart failure with preserved ejection fraction: a prognosticator like in sinus rhythm?. European Journal of Heart Failure. 30 January 2019. doi.org/10.1002/ejhf.1425
     
  31. Rachel Burns. Million Migrants study of healthcare and mortality outcomes in non-EU migrants and refugees to England: Analysis protocol for a linked population-based cohort study of 1.5 million migrants. Welcome Open Res. 17 January 2019.  10.12688/wellcomeopenres.15007.1     
     
  32. Uijl A, Koudstaal S, Direk K, Denaxas S, Groenwold RHH, Banerjee A, Hoes AW, Hemingway H, Asselbergs FW. Risk factors for incident heart failure in age‐ and sex‐specific strata: a population‐based cohort using linked electronic health records. European Journal of Heart Failure. 07 January 2019. doi.org/10.1002/ejhf.1350
     
  33. Van der Laan SW, Harshfield EL, Hemerich D, Stacey D, Wood AM, Asselbergs FW. From lipid locus to drug target through human genomics. Cardiovascular Research. 15 July 2018. doi:10.1093/cvr/cvy120
     
  34. Hemerich D., van Setten J, Tragante V, Asselbergs FW. Integrative Bioinformatics Approaches for Identification of Drug Targets in Hypertension. Front. Cardiovasc. Med. 04 April 2018. https://doi.org/10.3389/fcvm.2018.00025
     
  35. Johannes M I H Gho, An electronic health records cohort study on heart failure following myocardial infarction in England: incidence and predictors. BMJ Open. 03 March 2018. doi.org/10.1136/bmjopen-2017-018331 
     
  36. Hemingway H, Asselbergs FW, Danesh J, Dobson R, Maniadakis N, Maggioni A, van Thiel GJM, Cronin M, Brobert G, Vardas P, Anker SD, Grobbee DE, Denaxas S. Big data from electronic health records for early and late translational cardiovascular research: challenges and potential. European Heart Journal. 29 August 2017. doi:10.1093/eurheartj/ehx487
     
  37. Anker S, Asselbergs FW, Brobert G, Vardas P, Drobbee DE, Cronin M. Big Data in Cardiovascular Disease. European Heart Journal. 21 June 2017. doi: 10.1093/eurheartj/ehx283.