Incidence and predictors of atrial fibrillation episodes as detected by implantable loop recorder in patients at risk: From the LOOP study

TY - JOUR

T1 - Incidence and predictors of atrial fibrillation episodes as detected by implantable loop recorder in patients at risk

T2 - From the LOOP study

AU - Diederichsen, Søren Zöga

AU - Haugan, Ketil Jørgen

AU - Brandes, Axel

AU - Graff, Claus

AU - Krieger, Derk

AU - Kronborg, Christian

AU - Holst, Anders Gaarsdal

AU - Nielsen, Jonas Bille

AU - Køber, Lars

AU - Højberg, Søren

AU - Svendsen, Jesper Hastrup

PY - 2020/1

Y1 - 2020/1

N2 - Background: Recent studies have suggested a high prevalence of subclinical atrial fibrillation (AF) in various patient populations, and interest in AF screening has increased. However, knowledge about episode duration is scarce, and risk factors for short or long subclinical AF episodes have yet to be recognized. The aim of the study was to assess AF by long-term continuous screening and to investigate predictors of episodes lasting ≥6 minutes, ≥5.5 hours, or ≥24 hours, respectively. Methods: A total of 597 patients aged ≥70 years and diagnosed with ≥1 of hypertension, diabetes, previous stroke, or heart failure were recruited from the general population to receive implantable loop recorder with remote monitoring. Exclusion criteria included history of AF or cardiac implantable electronic device. AF episodes were adjudicated by senior cardiologists. Results: During 40 (37; 42) months of continuous monitoring, AF was detected in 209 (35%) of the patients. The cumulative incidences at 3 years were 33.8% (30.2%-37.8%), 16.1% (13.4%-19.4%), and 5.7% (4.1%-7.9%) for AF episodes lasting ≥6 minutes, ≥5.5 hours, and ≥24 hours, respectively. Slower resting sinus rate and higher body mass index, N-terminal prohormone of brain natriuretic peptide, and troponin T at baseline were independently associated with AF detection. Addition of these markers to a model of sex, age, and comorbidities improved prediction of AF episodes ≥24 hours (time-dependent area under the receiver operating characteristic curve 79% vs 65%, P =.037). Conclusions: A considerable burden of previously unknown AF was detected when long-term monitoring was applied in at-risk patients. Biomarkers were associated with AF incidence and improved prediction of long AF episodes.

AB - Background: Recent studies have suggested a high prevalence of subclinical atrial fibrillation (AF) in various patient populations, and interest in AF screening has increased. However, knowledge about episode duration is scarce, and risk factors for short or long subclinical AF episodes have yet to be recognized. The aim of the study was to assess AF by long-term continuous screening and to investigate predictors of episodes lasting ≥6 minutes, ≥5.5 hours, or ≥24 hours, respectively. Methods: A total of 597 patients aged ≥70 years and diagnosed with ≥1 of hypertension, diabetes, previous stroke, or heart failure were recruited from the general population to receive implantable loop recorder with remote monitoring. Exclusion criteria included history of AF or cardiac implantable electronic device. AF episodes were adjudicated by senior cardiologists. Results: During 40 (37; 42) months of continuous monitoring, AF was detected in 209 (35%) of the patients. The cumulative incidences at 3 years were 33.8% (30.2%-37.8%), 16.1% (13.4%-19.4%), and 5.7% (4.1%-7.9%) for AF episodes lasting ≥6 minutes, ≥5.5 hours, and ≥24 hours, respectively. Slower resting sinus rate and higher body mass index, N-terminal prohormone of brain natriuretic peptide, and troponin T at baseline were independently associated with AF detection. Addition of these markers to a model of sex, age, and comorbidities improved prediction of AF episodes ≥24 hours (time-dependent area under the receiver operating characteristic curve 79% vs 65%, P =.037). Conclusions: A considerable burden of previously unknown AF was detected when long-term monitoring was applied in at-risk patients. Biomarkers were associated with AF incidence and improved prediction of long AF episodes.

U2 - 10.1016/j.ahj.2019.09.009

DO - 10.1016/j.ahj.2019.09.009

M3 - Journal article

C2 - 31699295

AN - SCOPUS:85074819761

SN - 0002-8703

JO - American Heart Journal

JF - American Heart Journal

ER -