Atrial fibrillation (AF) and diabetes are chronic conditions, which are increasing in prevalence. Stroke is a recognised complication of both conditions and can often be prevented through detection and appropriate intervention. Screening for disease has also improved over the last few decades through a plethora of tools and advances in technology. AF impacts physically, psychologically, socially and economically, and does not always present with symptoms. AF can be detected through electrocardiogram (ECG) monitoring and pulse checks, with high-risk groups typically targeted. When AF is detected, medication to control heart rate and anticoagulation can be started to reduce subsequent risks. AF is underdiagnosed in the community, particularly in the elderly, and the condition lends itself to screening.1
A review of the evidence for AF screening demonstrates a lack of homogeneity, with different target populations. High-risk groups have varied and include those with hypertension, stroke, myocardial infarction, older age and diabetes. Although the pathophysiological relationship between AF and diabetes is not entirely understood, there is an acceptance that the coexistence imposes greater risk to the patient in terms of comorbidities including stroke.
For UK healthcare professionals only
Relationship between diabetes and AF
Mass screening of AF in the STROKESTOP study2 discovered diabetes, heart failure and previous stroke/transient ischaemic attack (TIA) to be the strongest predictors for AF in multi-variate analysis. This confirms findings from the historical Framingham study, where diabetes conferred a 1.4-fold increased risk of stroke in men and a 1.6-fold increased risk in women.3 A recent review of the evidence from AF screening studies in those with perceived high risks, has demonstrated the prevalence of AF in people with diabetes ranges from 2.9%4 to 18.5%.2 Chan and Choy’s study (2016)5 did not find diabetes to be a significant risk factor at univariate analysis, yet there was a positive link when analysed using a multi-variate method. Turakhia et al. (2015)6 revealed 8.3% of patients with diabetes in their study – using extended ambulatory monitoring – had AF. Davis et al. (2012)7 found a small number (<10%) of people with diabetes had AF, yet diabetes was shown to be more common in people with AF than in a normal rhythm (9% vs. 3.9%). Diabetes was strongly associated with higher prevalence of AF in both sexes (p<0.05) in a study by Sun et al. (2014),4 with age having the most significant impact on AF in their study. Diabetes was prevalent in 2.4% of males with AF (p=0.017, odds ratio [OR] 2.16) and 3.3% of females (p<0.001, OR 3.51).4
Further evidence has shown contradictory outcomes in terms of diabetes-associated AF, but overall prevalence is high. Krijthe et al. (2013)8 and Oldgren et al. (2014)9 conducted AF registries and concluded that while there was a high prevalence of AF in diabetes, this was not significant when age adjusted. A longitudinal prevalence study demonstrated that AF was up to 44% more prevalent when diabetes co-existed.10 A Belgian population screening programme for AF,11 which analysed five years of data from their Belgian heart rhythm screening week (n=65,747), identified 26.8% of people with diabetes having AF.
Ease of screening
AF lends itself to screening and diagnostic clarity through advancements in technology, and the availability of digital applications offers alternative, transportable and convenient methods for monitoring. Screening for AF continues to receive interest, with global campaigns striving to encourage mandatory screening in targeted groups. The diabetes population is accessible and can, therefore, be targeted during routine clinical reviews. A simple pulse check is an instant and available means of detecting an irregular pulse. This can be performed during the most basic of assessments. Single-lead ECG monitoring offers advantages in terms of rhythm recordings and can be used for either single point in time analysis or intermittent monitoring. And for optimal assessment, continuous ECG monitoring can be achieved through a number of applications, including Holter-style ECGs.
It is, therefore, evident that while there is a lack of research exploring the prevalence of AF in people with diabetes as a homogenous group, there is an association with a higher number of people with diabetes having AF than those without. Research into this as a targeted group is important and may then impact on public health, policy and potential screening of this population. However, before significant changes can be made, recommendations from the European Heart Rhythm Association (EHRA)12 would be advocated in terms of encouraging large experimental outcome studies to strengthen the evidence base. This high-risk group could then receive appropriate diagnosis, treatment and management and reduce the risk of costly and disabling complications, particularly stroke.
Conflicts of interest
1. Kirchoff P, Benussi S, Kotecha D et al. 2016 ESC guidelines for the management of atrial fibrillation developed in collaboration with EACTS. Eur Heart J 2016;37:2893–962. https://doi.org/10.1093/eurheartj/ehw210
2. Svennberg E, Engdahl J, Al-Khalili F et al. Mass screening for untreated atrial fibrillation the STROKESTOP study. Circulation 2015;131:2176–84. https://doi.org/10.1161/CIRCULATIONAHA.114.014343
3. Kannel W, Wolf P, Benjamin E et al. Prevalence, incidence, prognosis, and predisposing conditions for atrial fibrillation: population-based estimates. Am J Cardiol 1998;16:2–9. https://doi.org/10.1016/S0002-9149(98)00583-9
4. Sun G, Guo L, Wang X et al. Prevalence of atrial fibrillation and its risk factors in rural China: a cross-sectional study. Int J Cardiol 2014;182:13–17. https://doi.org/10.1016/j.ijcard.2014.12.063
5. Chan N, Choy C. Screening for atrial fibrillation in 13,122 Hong Kong citizens with smartphone electrocardiogram. Heart 2017;103:24–31. https://doi.org/10.1136/heartjnl-2016-309993
6. Turakhia M, Ullal A, Hoang D et al. Feasibility of extended ambulatory electrocardiogram monitoring to identify silent atrial fibrillation in high-risk patients: the screening study for undiagnosed atrial fibrillation (STUDY-AF). Clin Cardiol 2015;38:285–92. https://doi.org/10.1002/clc.22387
7. Davis R, Hobbs R, Kenkre J et al. Prevalence of atrial fibrillation in the general population and in high-risk groups: the ECHOES study. Europace 2012;14:1553–9. https://doi.org/10.1093/europace/eus087
8. Krijthe B, Kunst A, Benjamin E et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J 2013;34:2746–51. https://doi.org/10.1093/eurheartj/eht280
9. Oldgren J, Healey J, Ezekowitz M et al. Variations in etiology and management of atrial fibrillation in a prospective registry of 15,400 emergency department patients in 46 countries: the RE-LY AF registry. Circulation 2014;129:1568–76. https://doi.org/10.1161/CIRCULATIONAHA.113.005451
10. Nichols G, Reinier K, Chugh S. Independent contribution of diabetes to increased prevalence and incidence of atrial fibrillation. Diabetes Care 2009;373:1851–6. https://doi.org/10.2337/dc09-0939
11. Proietti M, Mairesse G, Goethalis P, Lip G. A population screening programme for atrial fibrillation. A report from the Belgian Heart Rhythm week programme. Europace 2016;18:1779–86. https://doi.org/10.1093/europace/euw069
12. Mairesse G, Moran, P, Van Gelder I et al. Screening for atrial fibrillation: a European Heart Rhythm Association (EHRA) consensus document endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (ASHRS), and Sociedad Latinoamericana de Estimulación Cardíaca y Electrofisiología (SOLAECE). EP Europace 2017;19:1589–623. https://doi.org/10.1093/europace/eux177