Denaxas Lab

  1. Chung SC et al. Time spent at blood pressure target and the risk of death and cardiovascular diseases. PLoS One. 2018 Sep 5;13(9):e0202359. doi: 10.1371/journal.pone.0202359. eCollection 2018. PMID: 30183734

  2. Archangelidi O et al. Clinically recorded heart rate and incidence of 12 coronary, cardiac, cerebrovascular and peripheral arterial diseases in 233,970 men and women: A linked electronic health record study. Eur J Prev Cardiol. 2018 Sep;25(14):1485-1495. doi: 10.1177/2047487318785228. Epub 2018 Jul 2. PMID: 29966429

  3. Pujades-Rodriguez M et al. The diagnosis, burden and prognosis of dementia: A record-linkage cohort study in England. PLoS One. 2018 Jun 26;13(6):e0199026. doi: 10.1371/journal.pone.0199026. eCollection 2018. PMID: 29944675

  4. Papez V et al. Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms. AMIA Annu Symp Proc. 2018 Apr 16;2017:1352-1361. eCollection 2017. PMID: 29854204

  5. Gho JMIH et al. An electronic health records cohort study on heart failure following myocardial infarction in England: incidence and predictors. BMJ Open. 2018 Mar 3;8(3):e018331. doi: 10.1136/bmjopen-2017-018331. PMID: 29502083

  6. Rapsomaniki E et al. Using big data from health records from four countries to evaluate chronic disease outcomes: a study in 114 364 survivors of myocardial infarction. Eur Heart J Qual Care Clin Outcomes. 2016 Jul 1;2(3):172-183. doi: 10.1093/ehjqcco/qcw004. PMID: 29474617

  7. Pujades-Rodriguez M et al. Identifying unmet clinical need in hypertrophic cardiomyopathy using national electronic health records. PLoS One. 2018 Jan 11;13(1):e0191214. doi: 10.1371/journal.pone.0191214. eCollection 2018. PMID: 29324812

  8. Denaxas S et al. Methods for enhancing the reproducibility of biomedical research findings using electronic health records. BioData Min. 2017 Sep 11;10:31. doi: 10.1186/s13040-017-0151-7. eCollection 2017. PMID: 28912836

  9. George J et al. Ethnicity and the first diagnosis of a wide range of cardiovascular diseases: Associations in a linked electronic health record cohort of 1 million patients. PLoS One. 2017 Jun 9;12(6):e0178945. doi: 10.1371/journal.pone.0178945. eCollection 2017. PMID: 28598987

  10. Forssen H et al. Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data. Stud Health Technol Inform. 2017;235:111-115. PMID: 28423765

  11. Jordan KP et al. Prognosis of undiagnosed chest pain: linked electronic health record cohort study. BMJ. 2017 Apr 3;357:j1194. doi: 10.1136/bmj.j1194. PMID: 28373173

  12. Bell S et al. Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records. BMJ. 2017 Mar 22;356:j909. doi: 10.1136/bmj.j909. PMID: 28331015

  13. Pasea L et al. Personalising the decision for prolonged dual antiplatelet therapy: development, validation and potential impact of prognostic models for cardiovascular events and bleeding in myocardial infarction survivors. Eur Heart J. 2017 Apr 7;38(14):1048-1055. doi: 10.1093/eurheartj/ehw683. PMID: 28329300

  14. Shah AD et al. Neutrophil Counts and Initial Presentation of 12 Cardiovascular Diseases: A CALIBER Cohort Study. J Am Coll Cardiol. 2017 Mar 7;69(9):1160-1169. doi: 10.1016/j.jacc.2016.12.022. PMID: 28254179

  15. Allan V et al. Are cardiovascular risk factors also associated with the incidence of atrial fibrillation? A systematic review and field synopsis of 23 factors in 32 population-based cohorts of 20 million participants. Thromb Haemost. 2017 May 3;117(5):837-850. doi: 10.1160/TH16-11-0825. Epub 2017 Feb 23. PMID: 28229164

  16. Shah AD et al. White cell count in the normal range and short-term and long-term mortality: international comparisons of electronic health record cohorts in England and New Zealand. BMJ Open. 2017 Feb 17;7(2):e013100. doi: 10.1136/bmjopen-2016-013100. PMID: 28213596

  17. Hemingway H et al. ["Using nationwide 'big data' from linked electronic health records to help improve", 'outcomes in cardiovascular diseases: 33 studies using methods from epidemiology,', 'informatics, economics and social science in the ClinicAl disease research using', 'LInked Bespoke studies and Electronic health Records (CALIBER) programme'] BMJ Open. 2017 Feb 17;7(2):e013100. doi: 10.1136/bmjopen-2016-013100. PMID: 28151614

  18. Koudstaal S et al. Prognostic burden of heart failure recorded in primary care, acute hospital admissions, or both: a population-based linked electronic health record cohort study in 2.1 million people. Eur J Heart Fail. 2017 Sep;19(9):1119-1127. doi: 10.1002/ejhf.709. Epub 2016 Dec 23. PMID: 28008698

  19. Shah AD et al. Low eosinophil and low lymphocyte counts and the incidence of 12 cardiovascular diseases: a CALIBER cohort study. Open Heart. 2016 Sep 5;3(2):e000477. doi: 10.1136/openhrt-2016-000477. eCollection 2016. PMID: 27621833

  20. Allan V et al. Net clinical benefit of warfarin in individuals with atrial fibrillation across stroke risk and across primary and secondary care. Heart. 2017 Feb;103(3):210-218. doi: 10.1136/heartjnl-2016-309910. Epub 2016 Aug 31. PMID: 27580623

  21. Timmis A et al. Prolonged dual antiplatelet therapy in stable coronary disease: comparative observational study of benefits and harms in unselected versus trial populations. BMJ. 2016 Jun 22;353:i3163. doi: 10.1136/bmj.i3163. PMID: 27334486

  22. Rothnie KJ et al. Predicting mortality after acute coronary syndromes in people with chronic obstructive pulmonary disease. Heart. 2016 Sep 15;102(18):1442-8. doi: 10.1136/heartjnl-2016-309359. Epub 2016 May 13. PMID: 27177534

  23. Daskalopoulou M et al. Depression as a Risk Factor for the Initial Presentation of Twelve Cardiac, Cerebrovascular, and Peripheral Arterial Diseases: Data Linkage Study of 1.9 Million Women and Men. PLoS One. 2016 Apr 22;11(4):e0153838. doi: 10.1371/journal.pone.0153838. eCollection 2016. PMID: 27105076

  24. Walker S et al. Long-term healthcare use and costs in patients with stable coronary artery disease: a population-based cohort using linked health records (CALIBER). Eur Heart J Qual Care Clin Outcomes. 2016 Jan 20;2(2):125-140. doi: 10.1093/ehjqcco/qcw003. PMID: 27042338

  25. Pujades-Rodriguez M et al. Rheumatoid Arthritis and Incidence of Twelve Initial Presentations of Cardiovascular Disease: A Population Record-Linkage Cohort Study in England. PLoS One. 2016 Mar 15;11(3):e0151245. doi: 10.1371/journal.pone.0151245. eCollection 2016. PMID: 26978266

  26. Asaria M et al. Using electronic health records to predict costs and outcomes in stable coronary artery disease. Heart. 2016 May 15;102(10):755-62. doi: 10.1136/heartjnl-2015-308850. Epub 2016 Feb 10. PMID: 26864674

  27. Pujades-Rodriguez M et al. Associations between polymyalgia rheumatica and giant cell arteritis and 12 cardiovascular diseases. Heart. 2016 Mar;102(5):383-9. doi: 10.1136/heartjnl-2015-308514. Epub 2016 Jan 19. PMID: 26786818

  28. Chung SC et al. Authors' reply to Gupta. BMJ. 2015 Sep 30;351:h5140. doi: 10.1136/bmj.h5140. PMID: 26423089

  29. George J et al. How Does Cardiovascular Disease First Present in Women and Men? Incidence of 12 Cardiovascular Diseases in a Contemporary Cohort of 1,937,360 People. Circulation. 2015 Oct 6;132(14):1320-8. doi: 10.1161/CIRCULATIONAHA.114.013797. Epub 2015 Sep 1. PMID: 26330414

  30. Dinesh Shah A et al. Type 2 diabetes and incidence of a wide range of cardiovascular diseases: a cohort study in 1.9 million people. Lancet. 2015 Feb 26;385 Suppl 1:S86. doi: 10.1016/S0140-6736(15)60401-9. PMID: 26312908

  31. Chung SC et al. Comparison of hospital variation in acute myocardial infarction care and outcome between Sweden and United Kingdom: population based cohort study using nationwide clinical registries. BMJ. 2015 Aug 7;351:h3913. doi: 10.1136/bmj.h3913. PMID: 26254445

  32. Rubbo B et al. Use of electronic health records to ascertain, validate and phenotype acute myocardial infarction: A systematic review and recommendations. Int J Cardiol. 2015;187:705-11. doi: 10.1016/j.ijcard.2015.03.075. Epub 2015 Mar 5. PMID: 25966015

  33. Pujades-Rodriguez M et al. Heterogeneous associations between smoking and a wide range of initial presentations of cardiovascular disease in 1937360 people in England: lifetime risks and implications for risk prediction. Int J Epidemiol. 2015 Feb;44(1):129-41. doi: 10.1093/ije/dyu218. Epub 2014 Nov 20. PMID: 25416721

  34. Morley KI et al. Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation. PLoS One. 2014 Nov 4;9(11):e110900. doi: 10.1371/journal.pone.0110900. eCollection 2014. PMID: 25369203

  35. Pujades-Rodriguez M et al. Socioeconomic deprivation and the incidence of 12 cardiovascular diseases in 1.9 million women and men: implications for risk prediction and prevention. PLoS One. 2014 Aug 21;9(8):e104671. doi: 10.1371/journal.pone.0104671. eCollection 2014. PMID: 25144739

  36. Herrett E et al. Association between clinical presentations before myocardial infarction and coronary mortality: a prospective population-based study using linked electronic records. Eur Heart J. 2014 Sep 14;35(35):2363-71. doi: 10.1093/eurheartj/ehu286. Epub 2014 Jul 19. PMID: 25038774

  37. Brauer R et al. Antipsychotic drugs and risks of myocardial infarction: a self-controlled case series study. Eur Heart J. 2015 Apr 21;36(16):984-92. doi: 10.1093/eurheartj/ehu263. Epub 2014 Jul 8. PMID: 25005706

  38. McNamara RL et al. International comparisons of the management of patients with non-ST segment elevation acute myocardial infarction in the United Kingdom, Sweden, and the United States: The MINAP/NICOR, SWEDEHEART/RIKS-HIA, and ACTION Registry-GWTG/NCDR registries. Int J Cardiol. 2014 Aug 1;175(2):240-7. doi: 10.1016/j.ijcard.2014.04.270. Epub 2014 May 9. PMID: 24882696

  39. Rapsomaniki E et al. Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1.25 million people. Lancet. 2014 May 31;383(9932):1899-911. doi: 10.1016/S0140-6736(14)60685-1. PMID: 24881994

  40. Shah AD et al. Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study. Am J Epidemiol. 2014 Mar 15;179(6):764-74. doi: 10.1093/aje/kwt312. Epub 2014 Jan 12. PMID: 24589914

  41. Chung SC et al. Acute myocardial infarction: a comparison of short-term survival in national outcome registries in Sweden and the UK. Lancet. 2014 Apr 12;383(9925):1305-12. doi: 10.1016/S0140-6736(13)62070-X. Epub 2014 Jan 23. PMID: 24461715

  42. Rapsomaniki E et al. Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients. Eur Heart J. 2014 Apr;35(13):844-52. doi: 10.1093/eurheartj/eht533. Epub 2013 Dec 17. PMID: 24353280

  43. Quint JK et al. Effect of beta blockers on mortality after myocardial infarction in adults with COPD: population based cohort study of UK electronic healthcare records. BMJ. 2013 Nov 22;347:f6650. doi: 10.1136/bmj.f6650. PMID: 24270505

  44. Herrett E et al. Type and timing of heralding in ST-elevation and non-ST-elevation myocardial infarction: an analysis of prospectively collected electronic healthcare records linked to the national registry of acute coronary syndromes. Eur Heart J Acute Cardiovasc Care. 2013 Sep;2(3):235-45. doi: 10.1177/2048872613487495. PMID: 24222835

  45. Shah AD et al. Authors' reply to Stevens and McManus. BMJ. 2013 Jun 11;346:f3741. doi: 10.1136/bmj.f3741. PMID: 23757750

  46. Herrett E et al. Completeness and diagnostic validity of recording acute myocardial infarction events in primary care, hospital care, disease registry, and national mortality records: cohort study. BMJ. 2013 May 20;346:f2350. doi: 10.1136/bmj.f2350. PMID: 23692896

  47. Denaxas SC et al. Data resource profile: cardiovascular disease research using linked bespoke studies and electronic health records (CALIBER). Int J Epidemiol. 2012 Dec;41(6):1625-38. doi: 10.1093/ije/dys188. Epub 2012 Dec 5. PMID: 23220717

  48. Warren-Gash C et al. Influenza infection and risk of acute myocardial infarction in England and Wales: a CALIBER self-controlled case series study. J Infect Dis. 2012 Dec 1;206(11):1652-9. doi: 10.1093/infdis/jis597. Epub 2012 Oct 9. PMID: 23048170

  49. Shah AD et al. The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records. BMC Med Inform Decis Mak. 2012 Aug 7;12:88. doi: 10.1186/1472-6947-12-88. PMID: 22870911

  50. Douglas IJ et al. Clopidogrel and interaction with proton pump inhibitors: comparison between cohort and within person study designs. BMJ. 2012 Jul 10;345:e4388. doi: 10.1136/bmj.e4388. PMID: 22782731

  51. Wang Z et al. Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning. PLoS One. 2012;7(1):e30412. doi: 10.1371/journal.pone.0030412. Epub 2012 Jan 19. PMID: 22276193

  52. Shah AD et al. Threshold haemoglobin levels and the prognosis of stable coronary disease: two new cohorts and a systematic review and meta-analysis. PLoS Med. 2011 May;8(5):e1000439. doi: 10.1371/journal.pmed.1000439. Epub 2011 May 31. PMID: 21655315