The Role of Electrocardiographic Markers for Predicting Atrial Fibrillation in Patients with Acute Ischemic Stroke: Data from the BIOSIGNAL Cohort Study.

Schütz, Valerie; Dougoud, Svetlana; Bracher, Katja; Arnold, Markus; Schweizer, Juliane; Nakas, Christos; Westphal, Laura P; Inauen, Corinne; Pokorny, Thomas; Duru, Firat; Steffel, Jan; Luft, Andreas; Spanaus, Katharina; Saguner, Ardan Muammer; Katan, Mira (2023). The Role of Electrocardiographic Markers for Predicting Atrial Fibrillation in Patients with Acute Ischemic Stroke: Data from the BIOSIGNAL Cohort Study. Journal of clinical medicine, 12(21) MDPI 10.3390/jcm12216830

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BACKGROUND AND AIMS

P-wave abnormalities in the 12-lead electrocardiogram (ECG) have been associated with a higher risk of acute ischemic stroke (AIS) as well as atrial fibrillation (AF). This study aimed to assess pre-determined ECG criteria during sinus rhythm in unselected AIS patients and their value for predicting newly diagnosed atrial fibrillation (NDAF) after hospital admission.

METHODS

P-wave alterations were measured on 12-lead ECG on admission in all consecutively enrolled patients without known AF between October 2014 and 2017. The outcome of interest was NDAF, identified by prolonged electrocardiographic monitoring within one year after the index AIS. Univariable and multivariable logistic regression was applied to assess the magnitude and independence of the association between pre-selected ECG markers and NDAF. The discriminatory accuracy was evaluated with the area under the receiver operating characteristic curve (AUC), and the incremental prognostic value was estimated with the net reclassification index.

RESULTS

NDAF was detected in 87 (10%) of 856 patients during a follow-up of 365 days. Out of the pre-selected ECG parameters, advanced interatrial block (aIAB) and PR interval in lead II were independently associated with NDAF in univariable regression analysis. Only aIAB remained a significant predictor in multivariable analysis. Adding aIAB to the best-performing multivariable regression model improved the discriminatory accuracy to predict NDAF from an AUC of 0.78 (95%-CI 0.77-0.80) to 0.81 (95%-CI 0.80-0.83, p < 0.001).

CONCLUSION

aIAB is independently and highly associated with NDAF in patients with AIS, has high inter-rater reliability, and therefore may be helpful to refine diagnostic work-up to search for AF in AIS.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Institute of Clinical Chemistry

UniBE Contributor:

Nakas, Christos T.

Subjects:

600 Technology > 610 Medicine & health

ISSN:

2077-0383

Publisher:

MDPI

Language:

English

Submitter:

Pubmed Import

Date Deposited:

15 Nov 2023 12:27

Last Modified:

15 Nov 2023 12:37

Publisher DOI:

10.3390/jcm12216830

PubMed ID:

37959294

Uncontrolled Keywords:

P-wave abnormalities acute ischemic stroke biomarkers newly diagnosed atrial fibrillation secondary prevention stroke etiology

BORIS DOI:

10.48350/188916

URI:

https://boris.unibe.ch/id/eprint/188916

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