Publications

2021

  • Chapman, M., Mumtaz, S., Rasmussen, L. V., Karwath, A., Gkoutos, G. V., Gao, C., Thayer, D., Pacheco, J. A., Parkinson, A., Richesson, R. L., Jefferson, E., Spiros, S., Curcin, V. Desiderata for the development of next-generation electronic health record phenotype libraries, GigaScience, Volume 10, Issue 9, September 2021, giab059, 10.1093/gigascience/giab059
  • Banerjee A, Chen S, Pasea L, Lai A, Katsoulis M, Denaxas S, Nafilyan V, Williams B, Wong WK, Bakhai A, Khunti K, Pillay D, Noursadeghi M, Wu H, Pareek N, Bromage D, Mcdonagh T, Byrne J, Teo JT, Shah A, Humberstone B, Tang LV, Shah AS, Rubboli A, Guo Y, Hu H, Sudlow CLM, Lip GYH, Hemingway H. Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. 2021. European Journal of Preventive Cardiology, zwaa155, 10.1093/eurjpc/zwaa155
  • Banerjee A, Pasea L, Manohar S, HDR UK COVID-19 PPIE Panel, Lai AG, Hemingway E, Sofer I, Katsoulis M, Sood H, Morris A, Cake C, Fitzpatrick NK, Williams B, Denaxas S, Hemingway H. "What is the risk to me from Covid?": Public involvement in providing mortality risk information for people with 'high risk' conditions for COVID-19 (OurRisk.CoV). Accepted. Clinical Medicine. 2021. doi: 10.7861/clinmed.2021-0386
  • Chapman M, Domínguez J, Fairweather E, Delaney BC, Curcin V. Using Computable Phenotypes in Point-of-Care Clinical Trial Recruitment. Stud Health Technol Inform. 2021 May 27;281:560-564. doi: 10.3233/SHTI210233
  • Chapman M, Rasmussen LV, Pacheco JA, Curcin V. Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype Definitions. AMIA Annu Symp Proc. 2021 May 17;2021:142-151. PMID: 34457128; PMCID: PMC8378606
  • Chung S, Sofat R, Acosta-Mena D, Taylor JA, Lambiase PD, Casas JP, Providencia R. Atrial fibrillation epidemiology, disparity and healthcare contacts: a population-wide study of 5.6 million individuals. The Lancet Regional Health - Europe. 2021. Volume 7 100157. 10.1016/j.lanepe.2021.100157
  • Handy A, Banerjee A, Wood A, Dale CE, Sudlow C, Tomlinson C, Bean D, Thygesen JH, Mizani MA, Katsoulis M, Sofat R, Dobson R, Takhar R, Hollings S, Denaxas S, Walker V and on behalf of the CVD-COVID-UK Consortium. Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort. medRxiv 10.1101/2021.09.03.21263023
  • Lai AG, Chang WH, Parisinos CA, Katsoulis M, Blackburn RM, Shah AD, Nguyen V, Denaxas S, Davey Smith G, Gaunt TR, Nirantharakumar K, Cox MP, Forde D, Asselbergs F, Harris S, Richardson S, Sofat R, Dobson RJB, Hingorani A, Patel R, Sterne J, Banerjee A, Denniston AK, Ball S, Sebire NJ, Shah NH, Foster GR, Williams B, Hemingway H. An Informatics Consult approach for generating clinical evidence for treatment decisions. medRxiv 2021.01.10.21249331; doi: 10.1101/2021.01.10.21249331
  • Subota A, Jette N, Josephson CB, McMillan J, Keezer MR, Gonzalez-Izquierdo A, Holroyd-Leduc J. Risk factors for dementia development, frailty, and mortality in older adults with epilepsy - A population-based analysis. Epilepsy & Behavior 2021; 120:108006 medRxiv 2021.01.10.21249331; doi: 10.1016/j.yebeh.2021.108006

2020

  • Banerjee A, Pasea L, Harris S, Gonzalez-Izquierdo A, Torralbo A, Shallcross L, Noursadeghi M, Pillay D, Sebire N, Holmes C, Pagel C, Wong WK, Langenberg C, Williams B, Denaxas S, Hemingway H. Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study. The Lancet 2020 May 12. DOI: 10.1016/S0140-6736(20)30854-0
  • Chapman, M., Rasmussen, L. V, Pacheco, J. A., & Curcin, V. (2020). Phenoflow: Portable Workflow-based Phenotype Definitions. Available as a pre-print at MedRxiv: 10.1101/2020.07.01.20144196
  • Chung S-C, Providencia R, Sofat R. Association between Angiotensin Blockade and Incidence of Influenza in the United Kingdom. New Engl J Med (Letter). 2020. May 8, 2020 DOI: 10.1056/NEJMc2005396
  • Curcin C. Special Issue: Human Phenomics and the Learning Health System. Learning Health Systems 2020; Volume 4, Issue 4. First published 14 October 2020. Incl Guest Curcin V. Why does human phenomics matter today? Editor Commentary. Published 28 September 2020. 10.1002/lrh2.10249
  • Denaxas S, Shah A, Mateen BA, Kuan V, Quint JK, Fitzpatrick NK, Torralbo A, Fatemifar G, Hemingway H. A semi-supervised approach for rapidly creating clinical biomarker phenotypes in the UK Biobank using different primary care EHR and clinical terminology systems. JAMIA Open, Volume 3, Issue 4, December 2020, Pages 545-556, 10.1093/jamiaopen/ooaa047
  • Dennis JM, Mateen BA, Sonabend R, Thomas NJ, Patel KA, Hattersley AT, Denaxas S, McGovern AP, Vollmer SJ. Type 2 Diabetes and COVID-19-Related Mortality in the Critical Care Setting: A National Cohort Study in England, March-July 2020. Diabetes Care. 2021 Jan;44(1):50-57. doi: 10.2337/dc20-1444. Epub 2020 Oct 23. PMID: 33097559; PMCID: PMC7783930 10.2337/dc20-1444
  • Hobbs M, Patel R, Morrison PD, Kalk N, Stone JM. Synthetic cannabinoid use in psychiatric patients and relationship to hospitalisation: A retrospective electronic case register study. Journal of Psychopharmacology. 2020;34(6):648-653. doi: 10.1177/0269881120907973
  • Katsoulis M, Gomes M, Lai AG, Henry A, Denaxas S, Lagiou P, Nafilyan V, Humberstone B, Banerjee A, Hemingway H, Lumbers RT. Estimating the effect of reduced attendance at emergency departments for suspected cardiac conditions on cardiac mortality during the COVID-19 pandemic. Circ Cardiovasc Qual Outcomes. 2020 Dec 20. doi: 10.1161/CIRCOUTCOMES.120.007085 . Epub ahead of print. PMID: 33342219
  • Katsoulis M, Pasea L, Lai AG, Dobson RJB, Denaxas S, Hemingway H, Banerjee A. Obesity during the COVID-19 pandemic: both cause of high risk and potential effect of lockdown? A population-based electronic health record study. Public Health 2021; 191: 41-47. doi: 10.1016/j.puhe.2020.12.003
  • Katsoulis M, Lai AG, Diaz-Ordaz K, Gomes M, Pasea L, Banerjee A, Denaxas S, Tsilidis K, Lagiou P, Misirli G, Bhaskaran K, Wannamethee G, Dobson R, Batterham RL, Kipourou DK, Lumbers RT, Wareham N, Langenberg C, Hemingway H. Identifying high-risk groups for change in weight and body mass index: population cohort of 11 million measurements in 2.3 million adults. medRxiv 2021.01.19.21249898; doi: 10.1101/2021.01.19.21249898
  • Lai AG, Pasea L, Banerjee A, Hall G, Denaxas S, Chang, WH, Katsoulis M, Williams B, Pillay D, Noursadeghi M, Linch D, Hughes D, Forster MD, Turnbull C, Fitzpatrick NK, Boyd K, Foster GR, Enver T, Nafilyan V, Humberstone B, Neal RD, Cooper M, Jones M, Pritchard-Jones K, Sullivan R, Davie C, Lawler M, Hemingway H. Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study. BMJ Open 2020; 10:e043828. doi: 10.1136/bmjopen-2020-043828
  • Mansfield KE, Mathur R, Tazare J, Henderson AD, Mulick A, Carreira H, Matthews AA, Bidulka P, Gayle A, Forbes H, Cook S, Wong A, Strongman H, Wing K, Warren-Gash C, Cadogan SL, Smeeth L, Hayes J, Quint J, McKee M, Langan S. COVID-19 collateral: Indirect acute effects of the pandemic on physical and mental health in the UK. medRxiv 2020.10.29.20222174; doi: 10.1101/2020.10.29.20222174
  • Nind T, Sutherland J, McAllister G, Hardy D et al. An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data from the whole Scottish population, GigaScience, Volume 9, Issue 10, October 2020, giaa095, 10.1093/gigascience/giaa095
  • Thayer D, Rees A, Kennedy J, et al. Measuring follow-up time in routinely-collected health datasets: Challenges and solutions. PLoS One. 2020;15(2):e0228545. Published 2020 Feb 11. doi: 10.1371/journal.pone.0228545
  • Zylbersztejn A, Verfürden M, Hardelid P, Gilbert R, Wijlaars L. Phenotyping congenital anomalies in administrative hospital records. Paediatr Perinat Epidemiol. 2020 Jan;34(1):21-28. doi: 10.1111/ppe.12627 . PMID: 31960476; PMCID: PMC7003968.

2019

  • Banerjee A, Chen S, Fatemifar G, Hemingway H, Lumbers T, Denaxas S. P5705 Machine learning for phenotyping and risk prediction in cardiovascular diseases: a systematic review, Eur Heart J, Volume 40, Issue Supplement_1, October 2019, ehz746.0646, doi: 10.1093/eurheartj/ehz746.0646
  • Banerjee A, Allan V, Denaxas S, Shah A, Kotecha D, Lambiase PD, Joseph 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. 2019 Dec 1;21(12):1776-1784. doi: 10.1093/europace/euz220 . PMID: 31408153; PMCID: PMC6888023.
  • Bromage DI, Godec TR, Pujades-Rodriguez M, Gonzalez-Izquierdo A, Denaxas S, Hemingway H, Yellon DM. Metformin use and cardiovascular outcomes after acute myocardial infarction in patients with type 2 diabetes: a cohort study. Cardiovasc Diabetol. 2019 Dec 9;18(1):168. doi: 10.1186/s12933-019-0972-4 . PMID: 31815634; PMCID: PMC6900858.
  • Denaxas S, Gonzalez-Izquierdo A, Fitzpatrick NK, Direk K, Hemingway H. Phenotyping UK Electronic Health Records from 15 Million Individuals for Precision Medicine: The CALIBER Resource. Stud Health Technol Inform. 2019 Jul 4;262:220-223. DOI: 10.3233/SHTI190058
  • Denaxas S, Gonzalez-Izquierdo A, Direk K, Fitzpatrick NK, Fatemifar G, Banerjee A, Dobson R, Howe LJ, Kuan V, Lumbers T, Pasea L, Patel RS, Shah AD, Hingorani AD, Sudlow C, Hemingway H. UK phenomics platform for developing and validating EHR phenotypes: CALIBER. J Am Med Inform Assoc 22 Jul 2019 DOI: 10.1101/539403
  • Denaxas, S; Parkinson, H; Fitzpatrick, N; Sudlow, C; Hemingway, H; (2019) Analyzing the heterogeneity of rule-based EHR phenotyping algorithms in CALIBER and the UK Biobank. In: Wiratunga, N and Coenen, F and Sani, S, (eds.) CEUR Workshop Proceedings vol 2429. (pp. pp. 6-14). CEUR: Macao, China. http://ceur-ws.org/Vol-2429/paper2.pdf
  • Dickerman BA, García-Albéniz X, Logan RW, Denaxas S, Hernán MA. Avoidable flaws in observational analyses: an application to statins and cancer. Nature Medicine 2019; 25:1601-1606. DOI: 10.1038/s41591-019-0597-x
  • Hopkins C, Williamson E, Morris S, Clarke CS, Thomas M, Evans H, Little P, Lund VJ, Blackshaw H, Schilder A, Philpott C, Carpenter J, Denaxas S; MACRO programme team. Antibiotic usage in chronic rhinosinusitis: analysis of national primary care electronic health records. Rhinology. 2019 Dec 1;57(6):420-429. doi: 10.4193/Rhin19.136 . PMID: 31490466.
  • Kuan V, Denaxas S, Gonzalez-Izquierdo A, Direk K, Bhatti O, Husain S, Sutaria S, Hingorani M, Nitsch D, Parisinos CA, Lumbers RT, Mathur R, Sofat R, Casas JP, Wong ICK, Hemingway H, Hingorani AD. A Chronological Map of 308 Physical and Mental Health Conditions From 4 Million Individuals in the English National Health Service. Lancet Digit Health 2019 May 20;1(2):e63-e77. DOI: 10.1016/S2589-7500(19)30012-3
  • Mackintosh M, Aldridge R, Rossor M, González-Izquierdo A, Whitaker K, Ford E, Direk K, Denaxas S. (2019). Dementia recognition, diagnosis, and treatment in the UK, 1997-2017: a change-point analysis. The Lancet. 394. S70. doi: 10.1016/S0140-6736(19)32867-3
  • Pasea L, Chung SC, Pujades-Rodriguez M, Shah AD, Alvarez-Madrazo S, Allan V, Teo JT, Bean D, Sofat R, Dobson R, Banerjee A, Patel RS, Timmis A, Denaxas S, Hemingway H. Bleeding in cardiac patients prescribed antithrombotic drugs: electronic health record phenotyping algorithms, incidence, trends and prognosis. BMC Med. 2019 Nov 20;17(1):206. doi: 10.1186/s12916-019-1438-y . PMID: 31744503; PMCID: PMC6864929.
  • Pikoula M, Quint JK, Nissen F, Hemingway H, Smeeth L, Denaxas S. Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records. BMC Med Inform Decis Mak. 2019 Apr 18;19(1):86. doi: 10.1186/s12911-019-0805-0 . PMID: 30999919; PMCID: PMC6472089.
  • Rafiq M, Hayward A, Warren-Gash C, Denaxas S, Gonzalez-Izquierdo A, Lyratzopoulos G, Thomas S. Socioeconomic deprivation and regional variation in Hodgkin's lymphoma incidence in the UK: a population-based cohort study of 10 million individuals. BMJ Open. 2019 Sep 20;9(9):e029228. doi: 10.1136/bmjopen-2019-029228 . PMID: 31542744; PMCID: PMC6756616.
  • 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. Eur J Heart Fail. 2019 Oct;21(10):1197-1206. doi: 10.1002/ejhf.1350 . Epub 2019 Jan 7. PMID: 30618162; PMCID: PMC7074015.
  • Williamson E, Denaxas S, Morris S, Clarke CS, Thomas M, Evans H, Direk K, Gonzalez-Izquierdo A, Little P, Lund V, Blackshaw H, Schilder A, Philpott C, Hopkins C, Carpenter J, Programme Team OBOTM. Risk of mortality and cardiovascular events following macrolide prescription in chronic rhinosinusitis patients: a cohort study using linked primary care electronic health records. Rhinology. 2019 Aug 1;57(4):252-260. doi: 10.4193/Rhin18.237 . PMID: 30928998.