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Cardiovascular

Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England

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Pages 974-983 | Received 18 May 2022, Accepted 13 Jul 2022, Published online: 03 Aug 2022

References

  • Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: a global burden of disease 2010 study. Circulation. 2014;129(8):837–847.
  • Lip GYH, Brechin CM, Lane DA. The global burden of atrial fibrillation and stroke: a systematic review of the epidemiology of atrial fibrillation in regions outside North America and Europe. Chest. 2012;142(6):1489–1498.
  • Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the framingham study. Stroke. 1991;22(8):983–988.
  • Sentinel Stroke National Audit Programme (SSNAP). Clinical Audit National Results; 2019; [cited 2021Dec 12]. Available from: https://www.strokeaudit.org/results/Clinical-audit/National-Results.aspx.
  • Lamassa M, Di Carlo A, Pracucci G, et al. Characteristics, outcome, and care of stroke associated with atrial fibrillation in Europe: data from a multicenter multinational hospital-based registry (the european community stroke project). Stroke. 2001;32(2):392–398.
  • Marini C, De Santis F, Sacco S, et al. Contribution of atrial fibrillation to incidence and outcome of ischemic stroke: results from a population-based study. Stroke. 2005;36(6):1115–1119.
  • Xu X-M, Vestesson E, Paley L, et al. The economic burden of stroke care in England, Wales and Northern Ireland: using a national stroke register to estimate and report patient-level health economic outcomes in stroke. Eur Stroke J. 2018;3(1):82–91.
  • Patel A, Berdunov V, Quayyum Z, et al. Estimated societal costs of stroke in the UK based on a discrete event simulation. Age Ageing. 2020;49(2):270–276.
  • Cowan JC, Wu J, Hall M, et al. A 10 year study of hospitalized atrial fibrillation-related stroke in England and its association with uptake of oral anticoagulation. Eur Heart J. 2018;39(32):2975–2983.
  • Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation. Ann Intern Med. 2007;146(12):857–867.
  • Hindricks G, Potpara T, Dagres N, et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European association for cardio-thoracic surgery (EACTS): the task force for the diagnosis and management of atrial fibrillation of the european society of cardiology (ESC) developed with the special contribution of the european heart rhythm association (EHRA) of the ESC. Eur Heart J. 2021;42(5):373–498. Feb 1
  • British Heart Foundation. Atrial fibrillation: finding the missing 300,000 2019; [cited 2020Oct 01]. Available from: https://www.bhf.org.uk/for-professionals/healthcare-professionals/blog/2019/atrial-fibrillation-finding-the-missing-300000.
  • Hobbs FD, Fitzmaurice DA, Mant J, et al. A randomised controlled trial and cost-effectiveness study of systematic screening (targeted and total population screening) versus routine practice for the detection of atrial fibrillation in people aged 65 and over. The SAFE study. iv, ix-x. Health Technol Assess. 2005;9(40):iii–i74.
  • Khurshid S, Healey JS, McIntyre WF, et al. Population-based screening for atrial fibrillation. Circ Res. 2020;127(1):143–154. Jun 19
  • Hill NR, Ayoubkhani D, McEwan P, et al. Predicting atrial fibrillation in primary care using machine learning. PLoS One. 2019;14(11):e0224582.
  • Sekelj S, Sandler B, Johnston E, et al. Detecting undiagnosed atrial fibrillation in UK primary care: validation of a machine learning prediction algorithm in a retrospective cohort study. Eur J Prev Cardiol. 2021;28(6):598–605.
  • Szymanski T, Ashton R, Sekelj S, et al. Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients. Europace. 2022;2022:euac016.
  • Hill NR, Groves L, Dickerson C, et al. Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-Centre randomised controlled trial in England. Eur Heart J – Digital Health. 2022;3(2):195–204.
  • Hill NR, Arden C, Beresford-Hulme L, et al. Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): study protocol for a randomised controlled trial. Contemp Clin Trials. 2020;99:106191.
  • Welton NJ, McAleenan A, Thom HH, et al. Screening strategies for atrial fibrillation: a systematic review and cost-effectiveness analysis. Health Technol Assess. 2017;21(29):1–236.
  • Hill NR, Sandler B, Mokgokong R, et al. Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm. J Med Econ. 2020;23(4):386–393.
  • National Institute for Health and Care Excellence. Guide to the methods of technology appraisal.2013. Available from: https://www.nice.org.uk/process/pmg9/resources/guide-to-the-methods-of-technology-appraisal-2013-pdf-2007975843781.
  • Lopez-Lopez JA, Sterne JAC, Thom HHZ, et al. Oral anticoagulants for prevention of stroke in atrial fibrillation: systematic review, network Meta-analysis, and cost effectiveness analysis. BMJ. 2017;359:j5058.
  • National Institute for Health Research. Clinical Research Network Industry Costing Template (Primary Care) version October 2018. v1.32.
  • NHS Digital. Quality and Outcomes Framework. 2019–20; [cited 2021 Nov 08]. Available from: https://digital.nhs.uk/data-and-information/publications/statistical/quality-and-outcomes-framework-achievement-prevalence-and-exceptions-data.
  • Afzal S, Zaidi STR, Merchant HA, et al. Prescribing trends of oral anticoagulants in England over the last decade: a focus on new and old drugs and adverse events reporting. J Thromb Thrombolysis. 2021;52(2):646–653.
  • Berg J, Lindgren P, Nieuwlaat R, et al. Factors determining utility measured with the EQ-5D in patients with atrial fibrillation. Qual Life Res. 2010;19(3):381–390.
  • Haacke C, Althaus A, Spottke A, et al. Long-term outcome after stroke: evaluating health-related quality of life using utility measurements. Stroke. 2006;37(1):193–198.
  • Self-Reported Population Health: An international perspective based on EQ-5D Szende a JB., Cabases J, editor. Dordrecht: Springer; 2014.
  • Norberg J, Bäckström S, Jansson J-H, et al. Estimating the prevalence of atrial fibrillation in a general population using validated electronic health data. Clin Epidemiol. 2013;5:475–481.
  • Orlowski A, Wilkins J, Ashton R, et al. Budget impacts associated with improving diagnosis and treatment of atrial fibrillation in high-risk stroke patients. J Comp Eff Res. 2020;9(4):253–262.
  • Pharoah PD, Sewell B, Fitzsimmons D, et al. Cost effectiveness of the NHS breast screening programme: life table model. BMJ. 2013;346:f2618.
  • Taggar JS, Coleman T, Lewis S, et al. Accuracy of methods for detecting an irregular pulse and suspected atrial fibrillation: a systematic review and meta-analysis. Eur J Prev Cardiol. 2016;23(12):1330–1338.
  • Duarte R, Stainthorpe A, Greenhalgh J, et al. Lead-I ECG for detecting atrial fibrillation in patients with an irregular pulse using single time point testing: a systematic review and economic evaluation. Health Technol Assess. 2020;24(3):1–164.
  • National Institute for Health and Care Excellence. Lead-I ECG devices for detecting symptomatic atrial fibrillation using single time point testing in primary care [DG35]. 2019. Available from: https://www.nice.org.uk/guidance/dg35/chapter/1-Recommendations.
  • Savickas V, Stewart AJ, Rees-Roberts M, et al. Opportunistic screening for atrial fibrillation by clinical pharmacists in UK general practice during the influenza vaccination season: a cross-sectional feasibility study. PLoS Med. 2020;17(7):e1003197.
  • Kaasenbrood F, Hollander M, Rutten FH, et al. Yield of screening for atrial fibrillation in primary care with a hand-held, single-lead electrocardiogram device during influenza vaccination. Europace. 2016;18(10):1514–1520.
  • Murphy M, Scott LJ, Salisbury C, et al. Implementation of remote consulting in UK primary care following the COVID-19 pandemic: a mixed-methods longitudinal study. Br J Gen Pract. 2021;71(704):e166–e177.