From Minor Monitoring to Major Insight: Predicting AF Development in the Congenital Heart Disease Population

Background: The prognostic value of electrocardiography (ECG)- and continuous rhythm monitoring (CRM)-derived markers for predicting atrial fibrillation (AF) onset and progression remains unclear in patients with congenital heart disease (CHD). Methods: We retrospectively analyzed 573 CHD patients who underwent 24 h Holter monitoring between 2003 and 2015. Baseline ECG and CRM parameters were assessed. Cox regression identified predictors of new-onset AF and AF progression, and interaction analyses explored effect modification by left atrial (LA) dilatation. Results: During 13 ± 5 years of follow-up, AF occurred in 107 patients (18.7%), of whom 32 (29.9%) progressed to persistent/permanent AF (PeAF). Patients with AF more frequently had prolonged PR and QTc intervals and higher atrial ectopy (AE) and ventricular ectopy burdens. Independent predictors of new-onset AF were older age, LA dilatation, higher AE burden, atrial tachycardia, and pacemaker implantation. AF progression was independently associated with older age, LA dilatation, higher AE burden, and prolonged PR interval. AE burden showed a stronger association with AF risk in patients without LA dilatation. Conclusions: In CHD patients, baseline ECG PR-intervals and CRM-derived AE burden independently predict AF onset and/or progression. These noninvasive markers may improve risk stratification and support earlier personalized rhythm management.

Authors

Institutions

Publication Details

Journal
Journal of Cardiovascular Development and Disease
Published
2026-06-24
DOI
https://doi.org/10.3390/jcdd13070293
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Minor Monitoring to Major Insight: Predicting AF Development in the Congenital Heart Disease Population

Natasja M.S. de Groot, Mathijs S. van Schie, Annemien E. van den Bosch, Vehpi Yildirim et al.
Journal of Cardiovascular Development and Disease
Atrial Fibrillation Management and Outcomes
article

From Minor Monitoring to Major Insight: Predicting AF Development in the Congenital Heart Disease Population

Natasja M.S. de Groot, Mathijs S. van Schie, Annemien E. van den Bosch, Vehpi Yildirim, Y J H J Taverne, Lixia Dai, Can Zhang
article en

Abstract

Background: The prognostic value of electrocardiography (ECG)- and continuous rhythm monitoring (CRM)-derived markers for predicting atrial fibrillation (AF) onset and progression remains unclear in patients with congenital heart disease (CHD). Methods: We retrospectively analyzed 573 CHD patients who underwent 24 h Holter monitoring between 2003 and 2015. Baseline ECG and CRM parameters were assessed. Cox regression identified predictors of new-onset AF and AF progression, and interaction analyses explored effect modification by left atrial (LA) dilatation. Results: During 13 ± 5 years of follow-up, AF occurred in 107 patients (18.7%), of whom 32 (29.9%) progressed to persistent/permanent AF (PeAF). Patients with AF more frequently had prolonged PR and QTc intervals and higher atrial ectopy (AE) and ventricular ectopy burdens. Independent predictors of new-onset AF were older age, LA dilatation, higher AE burden, atrial tachycardia, and pacemaker implantation. AF progression was independently associated with older age, LA dilatation, higher AE burden, and prolonged PR interval. AE burden showed a stronger association with AF risk in patients without LA dilatation. Conclusions: In CHD patients, baseline ECG PR-intervals and CRM-derived AE burden independently predict AF onset and/or progression. These noninvasive markers may improve risk stratification and support earlier personalized rhythm management.

Journal of Cardiovascular Development and DiseaseVol. 13(7)
Erasmus MC (NL), First People's Hospital of Chongqing (CN), Delft University of Technology (NL)
Good health and well-being
Openalex Percentile: Top 9%
Atrial Fibrillation Management and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.