Previously unknown AF prevalent, but AF burden low in at-risk elderly persons with implanted loop recorder

Natural History of Subclinical Atrial Fibrillation Detected by Implanted Loop Recorders

Literature - Diederichsen SZ, Haugan KJ, Brandes A et al., - J Am Coll Cardiol. 2019 Dec, 74 (22) 2771-2781, DOI: 10.1016/j.jacc.2019.09.050

Introduction and methods

Atrial fibrillation (AF) is a well-known risk factor for ischemic stroke. Studies have shown that even short, subclinical episodes of AF are associated with increased risk of stroke [1]. This has led to an increased interest in AF screening and the development of new heart rhythm monitoring technologies [2-4]. It was recently shown that continuous ECG monitoring with implantable loop recorders will find previously undetected AF in approximately 30% of patients with risk factors [5,6]. However, the pathophysiology of asymptomatic AF remains largely unknown. This study aimed to characterize subclinical AF regarding AF burden, AF progression, and symptoms and heart rate during AF.

The current study took place within the ongoing, investigator-initiated, randomized controlled LOOP (Atrial Fibrillation Detected by Continuous ECG Monitoring Using Implantable Loop Recorder to Prevent Stroke in High-risk Individuals) trial. Participants aged ≥ 70 years with stroke risk factors (≥1 of hypertension, diabetes, previous stroke, or HF), without a history of AF were recruited from the general population. Participants were randomized in a 1:3 ratio to receive an implantable loop recorder (ILR) or to be a control. This analysis focused on 590 participants in the ILR group. Who were continuously monitored during a median of 40.2 (37.6 to 42.2) months.

The primary endpoint was AF burden, defined as the cumulative duration of AF episodes ≥ 6 min from the first adjudicated AF episode until end of monitoring, divided by the total duration of monitoring.

Main results

  • 205 Participants (35%) had adjudicated AF episodes lasting ≥6 min. Among them, AF burden was <0.05%, 0.05% to 0.5%, 0.5% to 5%, and 5% in 66 (32%), 68 (33%), 53 (26%), and 18 (9%) patients, respectively. Mean AF burden was 2.98 ±11.24% and median AF burden was 0.13% (0.03% to 1.05%) of the monitoring time.
  • In a multivariable model, increased OR’s for AF detection were associated with older age (per 5 years OR: 1.33 (1.7-1.04), P=0.021) and higher NT-proBNP (per doubling OR:1.27 (1.49-1.07), P=0.0053).
  • Among subjects with detected AF, increased incidence rate ratios of cumulative AF duration were associated with younger age (increasing age per 5 years IRR:0.54 (0.36-0.82), P=0.0034), male sex (3.42 (1.65-7.08), P=0.00094), history of hypertension (5.92 (1.48-23.73), P=0.012), and higher NT-proBNP (1.31 (1.02-1.69), P=0.038).
  • AF progression was heterogeneous in the population. Among patients with AF, 16.1% of the subjects had AF episodes lasting ≥24h, which was in 85% of the cases preceded by shorter AF episodes.
  • 51% Of the participants with AF had a reduced burden in last half compared to the first half of the monitoring time from debut to end of monitoring. Spontaneous, complete remission of AF (meaning, no further AF in the last 6 months of monitoring or longer) occurred in 22.4% of the subjects.
  • 90.2% Of all subjects with AF denied any symptoms at debut, and 86.8% never reported symptoms during AF after debut.
  • The median heart rate during AF was 96 (IQR: 83-114) beats/min, this was 24 (IQR: 9-41) beats/min faster than daytime sinus rates.


In a population of persons with stroke risk factors but no history of AF, previously unknown AF was often detected when using an implanted loop recorder. However, the AF burden was low, and symptoms were scarce. Progression from detected AF to longer AF episodes was limited and highly heterogeneous. Heart rate was only modestly elevated during AF episodes. Future studies are necessary to determine the effect of interventions on clinical outcomes of patients with subclinical AF detected by long-term rhythm monitoring.

Editorial comment

In her editorial comment [7], Glotzer discusses what lessons we should learn from the paper by Diederichsen et al. The finding that new subclinical AF was detected in 35% of subjects in the studied population confirms what has been found in many other studies.

Glotzer thinks the most interesting and novel finding is that AF lasting ≥24h was preceded with shorter episodes in 85% of cases. This makes her wonder whether it could be possible to predict which patients would progress to ≥24h episodes. A future machine-learning algorithm that could identify predictive patterns in the ECG in patients who progressed to 24h episodes compared to patterns in those who did not progress, could possibly help us identify patients who are at highest risk for progression.

Subclinical AF detected in this study had a highly heterogeneous progression profile. Detected AF could progress or recede. Glotzer supports the notion by the authors that subclinical AF as detected by continuous monitoring should not in general be regarded as a progressive disease. However, she hypothesizes that subclinical AF can come and go as a result of subtle changes in clinical conditions in the early stage of AF, but once AF episodes last longer and structural and electrical remodeling occur this may lead to further AF progression. Furthermore, Glotzer mentions the role of hypertension in the progression of AF and questions whether this is the most important clinical factor that should be modified when subclinical AF is detected.

Elevated NT-proBNP was associated with AF detection and AF burden. Glotzer argues that this information should be used in the design of future studies to enrich populations for the likelihood of developing AF. An interesting prospective therapeutic strategy may lie in lowering NT-proBNP levels and studying the effect on AF onset and progression.

The results of this study confirm that AF is most often asymptomatic. Glotzer states that therapies for the prevention of stroke, dementia, CHF and death should be implemented regardless of the presence or absence of symptoms. She eagerly awaits the final results of the LOOP study about the long-term effects of early AF detection and whether early detection and treatment can prevent poor clinical outcomes (stroke, death, CHF, and dementia).


1. Mahajan R, Perera T, Elliott AD, et al. Subclinical device-detected atrial fibrillation and stroke risk: a systematic review and meta-analysis. Eur Heart J 2018;39:1407–15.

2. Curry SJ, Krist AH, Owens DK, et al. Screening for atrial fibrillation with electrocardiography: US Preventive Services Task Force Recommendation Statement. JAMA 2018;320:478–84.

3. Li KHC,White FA, Tipoe T, et al. The current state of mobile phone apps for monitoring heart rate, heart rate variability, and atrial fibrillation: narrative review. JMIR Mhealth Uhealth 2019;7:e11606.

4. Turakhia MP, Desai M, Hedlin H, et al. Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: the Apple Heart Study. Am Heart J 2019;207:66–75.

5. Reiffel JA, Verma A, Kowey PR, et al. Incidence of previously undiagnosed atrial fibrillation using insertable cardiac monitors in a high-risk population. JAMA Cardiol 2017;2:1120–7.

6. Nasir JM, Pomeroy W, Marler A, et al. Predicting determinants of atrial fibrillation or flutter for therapy elucidation in patients at risk for thromboembolic events (PREDATE AF) study. Heart Rhythm 2017;14:955–61.

7. Glotzer TV, The Naissance of Atrial Fibrillation, J Am Coll Cardiol. 2019 Dec, 74 (22) 2782-2785.

Find this article online at J Am Coll Cardiol.

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