Highlights
- •New-onset AF was detected in 21% of patients with CIEDs.
- •Age, diabetes mellitus, heart failure, and left atrial enlargement predicted new-onset AF.
- •Four clinical factors provide clinically useful risk assessment of new-onset AF.
Abstract
Introduction
Cardiac implantable electronic devices (CIEDs) can detect atrial fibrillation (AF)
early and accurately. Risk factors for the development of new-onset AF in patients
with CIEDs remains uncertain.
Methods
Patients with CIEDs who visited Chiba University Hospital between January 2016 and
December 2016 were enrolled. We only included patients without single chamber CIEDs
or a known history of AF.
Results
Of 371 patients with CIEDs, 78 (21.0%; median age 61.0 years, 65.5% male) developed
new-onset AF. Multivariate analysis demonstrated that independent predictors for the
development of new or incident AF were age ≥65 years (odd ratio [OR] 2.76, 95% confidence
interval [CI] 1.54–4.96, P = 0.001), diabetes mellitus (OR 2.24, 95% CI 1.20–4.19,
P = 0.011), congestive heart failure (OR 1.94, 95% CI 1.06–3.54, P = 0.031), and left
atrial volume index >34 ml/m2 (OR 3.51, 95% CI 1.96–6.25, P < 0.001). Based on these 4 clinical factors (age ≥ 65,
diabetes mellitus, congestive heart failure, left atrial volume index > 34 ml/m2) there was a good predictive ability for new AF development (AUC 0.728) and clinically
usefulness using decision curve analysis.
Conclusions
A substantial number of patients with CIEDs develop new-onset AF. Four clinical factors
(age ≥ 65, diabetes mellitus, congestive heart failure, left atrial volume index > 34 ml/m2) independently predicted new-onset AF and may provide an approach to clinically useful
risk assessment for incident AF.
Keywords
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References
- Incidence of atrial fibrillation and relationship with cardiovascular events, heart failure, and mortality: a community-based study from the Netherlands.J Am Coll Cardiol. 2015; 66: 1000-1007
- Clinical relevance of silent atrial fibrillation: prevalence, prognosis, quality of life, and management.J Interv Card Electrophysiol. 2000; 4: 369-382
- Atrial fibrillation in patients with cryptogenic stroke.N Engl J Med. 2014; 370: 2467-2477
- Newly diagnosed atrial fibrillation and acute stroke. The Framingham Study.Stroke. 1995; 26: 1527-1530
- Clinical utility of intraatrial pacemaker stored electrograms to diagnose atrial fibrillation and flutter.Pacing Clin Electrophysiol. 2001; 24: 424-429
- Atrial high rate episodes detected by pacemaker diagnostics predict death and stroke: report of the Atrial Diagnostics Ancillary Study of the MOde Selection Trial (MOST).Circulation. 2003; 107: 1614-1619
- The relationship between daily atrial tachyarrhythmia burden from implantable device diagnostics and stroke risk: the TRENDS study.Circ Arrhythm Electrophysiol. 2009; 2: 474-480
- Subclinical atrial fibrillation and the risk of stroke.N Engl J Med. 2012; 366: 120-129
- Left atrial volume as an index of left atrial size: a population-based study.J Am Coll Cardiol. 2003; 41: 1036-1043
- 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS.Eur Heart J. 2016; 37: 2893-2962
- Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.JAMA. 2001; 285: 2864-2870
- Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.Chest. 2010; 137: 263-272
- Progression from paroxysmal to persistent atrial fibrillation clinical correlates and prognosis.J Am Coll Cardiol. 2010; 55: 725-731
- Usefulness of HATCH score in the prediction of new-onset atrial fibrillation for Asians.Medicine (Baltimore). 2017; 96e5597
- Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.Biometrics. 1988; 44: 837-845
- Decision curve analysis: a novel method for evaluating prediction models.Med Decis Making. 2006; 26: 565-574
- Presence and duration of atrial fibrillation detected by continuous monitoring: crucial implications for the risk of thromboembolic events.J Cardiovasc Electrophysiol. 2009; 20: 241-248
- Monitored atrial fibrillation duration predicts arterial embolic events in patients suffering from bradycardia and atrial fibrillation implanted with antitachycardia pacemakers.J Am Coll Cardiol. 2005; 46: 1913-1920
- Atrial fibrillation after DDDR pacemaker implantation.J Cardiovasc Electrophysiol. 2002; 13: 542-547
- Pacemaker-detected atrial fibrillation in patients with pacemakers: prevalence, predictors, and current use of oral anticoagulation.Can J Cardiol. 2013; 29: 224-228
- Clinical implications of brief device-detected atrial tachyarrhythmias in a cardiac rhythm management device population: results from the registry of atrial tachycardia and atrial fibrillation episodes.Circulation. 2016; 134: 1130-1140
- Predictors and long-term clinical outcomes of newly developed atrial fibrillation in patients with cardiac implantable electronic devices.Medicine (Baltimore). 2016; 95e4181
- Characteristics and prognosis of pacemaker-identified new-onset atrial fibrillation in Japanese people.Circ J. 2017; 81: 794-798
- Adverse effect of ventricular pacing on heart failure and atrial fibrillation among patients with normal baseline QRS duration in a clinical trial of pacemaker therapy for sinus node dysfunction.Circulation. 2003; 107: 2932-2937
- Managed ventricular pacing vs. conventional dual-chamber pacing for elective replacements: the PreFER MVP study: clinical background, rationale, and design.Europace. 2008; 10: 321-326
- Coronary heart disease and atrial fibrillation: the Framingham Study.Am Heart J. 1983; 106: 389-396
- Incidence of and risk factors for atrial fibrillation in older adults.Circulation. 1997; 96: 2455-2461
- Prevalence of unknown atrial fibrillation in patients with risk factors.Europace. 2013; 15: 657-662
- Comparison of the microlife blood pressure monitor with the Omron blood pressure monitor for detecting atrial fibrillation.Am J Cardiol. 2014; 114: 1046-1048
- Triage tests for identifying atrial fibrillation in primary care: a diagnostic accuracy study comparing single-lead ECG and modified BP monitors.BMJ Open. 2014; 4: e004565
- A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation.Heart Rhythm. 2013; 10: 315-319
- Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study.JAMA. 1994; 271: 840-844
- Risk factors for atrial fibrillation in patients with normal versus dilated left atrium (from the Atherosclerosis Risk in Communities Study).Am J Cardiol. 2014; 114: 1368-1372
- Relationship of CHA2DS2-VASc and CHADS2 score to left atrial remodeling detected by velocity vector imaging in patients with atrial fibrillation.PLoS One. 2013; 8e77653
- CHADS(2) and CHA(2)DS(2)-VASc scores in the prediction of clinical outcomes in patients with atrial fibrillation after catheter ablation.J Am Coll Cardiol. 2011; 58: 2380-2385
- Usefulness of CHADS2 and CHA2DS2-VASc scores in the prediction of new-onset atrial fibrillation: a population-based study.Am J Med. 2016; 129: 843-849
Article info
Publication history
Published online: February 26, 2018
Accepted:
February 21,
2018
Received in revised form:
January 30,
2018
Received:
October 22,
2017
Identification
Copyright
© 2018 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.