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15/Should we be screening people with diabetes for AF? A cross sectional screening study

Published Online: October 3rd 2021 European Journal of Arrhythmia & Electrophysiology. 2021;7(Suppl. 1):abstr15
Authors: A Hall (Presenting Author) - Jersey General Hospital, St Helier; A Mitchell - Jersey General Hospital, St Helier; Carol Holland - Lancaster University, Lancaster; L Ashmore - Jersey General Hospital, St Helier,
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Introduction: There is an increasing prevalence of atrial fibrillation (AF) and diabetes worldwide, and diabetes is recognised as a risk factor for developing AF. Both diabetes and AF increase stroke risk. Previous AF screening studies have recruited high-risk patient groups but not with diabetes as the lone target group. The aim of this study is to determine whether people with diabetes have a higher prevalence of AF than the general population and investigate whether further determinants, such as duration of diabetes or level of diabetes control, add to the risk of AF. This study screens people with diabetes for AF using a single-lead ECG device (Kardia®, Mountainview, California, USA) and then examines the role of age, gender and other risk factor variables in relation to the likelihood of AF diagnosis.

Methods: This cross-sectional screening study was conducted in two community settings in Jersey – the diabetes centre (an out-patient hospital setting) and a central clinical locality – where patients recruited from participating GP surgeries attended. Patients were invited to participate on arrival to the diabetes centre or via letter sent out from participating GP surgeries. A 30-second ECG was recorded using the Kardia® device along with physiological measurements and details relating to risk-factor variables.

Results: A total of 300 participants with a diagnosis of diabetes were recruited (156 from the diabetes centre and 144 from GP surgeries). Single-lead ECG screenings were recorded on all participants and 16 patients were identified with AF, providing a 5.3% prevalence in this sample. The population in this study do not show a significantly greater likelihood of AF than the background population, although there is a non-significant trend in this direction t(298)=1.803; p=0.072. One-way ANOVA determined a statistically significant difference in age between groups (p=0.003). The Chi-square test of independence identified a statistically significant difference in diabetes type (p=0.030). Logistic regression was used to examine prediction of AF diagnosis with age, sex, diabetes type, diabetes duration and level of control as predictors. The only significant predictor was age (X2=4.696; p=0.030).

Conclusion: The diabetes population in this study does not show a significantly greater likelihood of AF than the background population. Age was identified as the only significant predictor of AF. These findings can add to existing data around the association of the two chronic conditions and assist in guiding further the importance of screening for AF in this high-risk group, but particularly in those of older age. This can then inform and contribute to appropriate management of both conditions when in combination, not least with regards to stroke prevention.

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