Abstract
Objective: Approximately 20% of strokes are embolic strokes of undetermined source (ESUS). Undetected atrial fibrillation (AF) remains an important cause. Yet, oral anticoagulation in unselected ESUS patients failed in secondary stroke prevention. Guidance on effective AF detection is lacking. Here, we introduce a novel, non-invasive AF risk assessment after ESUS.
Methods: Catch-Up ESUS is an investigator-initiated, observational cohort study conducted between 2018 and 2019 at the Munich University Hospital. Besides clinical characteristics, patients received & GE;72 h digital electrocardiogram recordings to generate the rhythm irregularity burden. Uni- and multivariable regression models predicted the primary endpoint of incident AF, ascertained by standardized follow-up including implantable cardiac monitors. Predictors included the novel rhythm irregularity burden constructed from digital electrocardiogram recordings. We independently validated our model in ESUS patients from the University Hospital Tubingen, Germany.
Results: A total of 297 ESUS patients were followed for 15.6 +/- 7.6 months. Incident AF (46 patients, 15.4%) occurred after a median of 105 days (25th to 75th percentile 31-33 days). Secondary outcomes were recurrent stroke in 7.7% and death in 6.1%. Multivariable-adjusted analyses identified the rhythm irregularity burden as the strongest AF-predictor (hazard ratio 3.12, 95% confidence interval 1.62-5.80, p < 0001) while accounting for the known risk factors age, CHA(2)DS(2)-VASc-Score, and NT-proBNP. Independent validation confirmed the rhythm irregularity burden as the most significant AF-predictor (hazard ratio 2.20, 95% confidence interval 1.45-3.33, p < 0001).
Interpretation: The novel, non-invasive, electrocardiogram-based rhythm irregularity burden may help adjudicating AF risk after ESUS, and subsequently guide AF-detection after ESUS. Clinical trials need to clarify if high-AF risk patients benefit from tailored secondary stroke prevention.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin
Medizin > Munich Cluster for Systems Neurology (SyNergy) |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-106258-7 |
ISSN: | 0364-5134 |
Sprache: | Englisch |
Dokumenten ID: | 106258 |
Datum der Veröffentlichung auf Open Access LMU: | 11. Sep. 2023, 13:36 |
Letzte Änderungen: | 06. Jun. 2024, 16:17 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 413635475 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |