Screen-detected atrial fibrillation predicts mortality in elderly subjects

Matthias D Zink, Karl G Mischke, Andras P Keszei, Christian Rummey, Ben Freedman, Gabriele Neumann, Alina Tolksdorf, Friederike Frank, Jan Wienströer, Nicole Kuth, Jörg B Schulz, Nikolaus Marx, Matthias D Zink, Karl G Mischke, Andras P Keszei, Christian Rummey, Ben Freedman, Gabriele Neumann, Alina Tolksdorf, Friederike Frank, Jan Wienströer, Nicole Kuth, Jörg B Schulz, Nikolaus Marx

Abstract

Aims: Current guidelines recommend opportunistic screening for atrial fibrillation (AF) but the prognosis of individuals is unclear. The aim of this investigation is to determine prevalence and 1-year outcome of individuals with screen-detected AF.

Methods and results: We performed a prospective, pharmacy-based single time point AF screening study in 7107 elderly citizens (≥65 years) using a hand-held, single-lead electrocardiogram (ECG) device. Prevalence of AF was assessed, and data on all-cause death and hospitalization for cardiovascular (CV) causes were collected over a median follow-up of 401 (372; 435) days. Mean age of participants was 74 ± 5.9 years, with 58% (N = 4130) of female sex. Automated heart rhythm analyses identified AF in 432 (6.1%) participants, with newly diagnosed AF in 3.6% of all subjects. During follow-up, 62 participants (0.9%) died and 390 (6.0%) were hospitalized for CV causes. Total mortality was 2.3% in participants with a screen-detected AF and 0.8% in subjects with a normal ECG [hazard ratio (HR) 2.94; 95% confidence interval (CI) 1.49-5.78; P = 0.002]; hospitalization for CV causes occurred in 10.6% and 5.5%, respectively (HR 2.08; 95% CI 1.52-2.84; P < 0.001). Compared with subjects without a history of AF at baseline and a normal ECG, participants with newly diagnosed or known AF had a significantly higher mortality risk with HRs of 2.64 (95% CI 1.05-6.66; P = 0.04) and 2.68 (95% CI 1.44-4.97; P = 0.002), respectively. After multivariable adjustment, screen-detected AF remained a significant predictor of death or hospitalization for CV causes.

Conclusion: Pharmacy-based, automated AF screening in elderly citizens identified subjects with unknown AF and an excess mortality risk over the next year.

Trial registration: ClinicalTrials.gov NCT03004859.

Keywords: Atrial fibrillation; Opportunistic; Outcome; Pharmacy; Prognosis; Screening.

© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.

Figures

Graphical abstract
Graphical abstract
Figure 1
Figure 1
Study design.
Figure 2
Figure 2
Flow chart of participants in the study. A total of 7295 subjects were screened in the study. We found 7107 patients eligible to participate in the study with correct age, automated SL-ECG analyses, and completed self-reported baseline characteristics. All subjects with screen-detected AF were contacted 8 weeks after index measurement. All participants were contacted after at least 12 months to obtain detailed medical information. The 8-week and 12-month follow-up consist of a telephone questionnaire in which information on medical history, AF and cardiovascular-related events after the pharmacy measurement were obtained (Supplementary material online, Figure S2). In case the participants could not be reached, could not answer, or in case of patient death all information were obtained from treating physicians and first degree relatives. All fatality cases were confirmed by treating physicians, medical records, first degree relatives, obituaries, and death certificates. AF, atrial fibrillation; FU, follow-up; EOS, end of study.
Figure 3
Figure 3
One year outcome of subjects with and without atrial fibrillation. (A and B) Time to death or hospitalization in participants with screen-detected AF (red line) vs. participants with a normal SL-ECG (green line). (A) Kaplan–Meier curves for survival. (B) Cumulative incidences of hospitalization for cardiovascular causes. For time to death 6552 subjects with 62 events were analysed. For time to hospitalization 6504 subjects with 390 events were analysed. (C and D) Time to death or hospitalization in participants with no AF (green line), newly detected AF (black line), as well as known AF (red line) based on history of AF at baseline and results of the automated SL-ECG analysis. (C) Kaplan–Meier curves for survival. (D) Cumulative incidences for hospitalization for cardiovascular causes. For time to death 6552 subjects with 62 events were analysed. For time to hospitalization 6504 subjects with 390 events were analysed.

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Source: PubMed

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