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Article: Clinical Profiling and Biomarkers for Post-Operative Atrial Fibrillation Prediction in Patients Undergoing Cardiac Surgery.

Iglesias-Álvarez, Diego / Fu, Xiaoran / Martínez-Cereijo, José Manuel / Agra-Bermejo, Rosa María / Veiras-Del Río, Sonia / Selas-Cobos, Salomé / Rial-Munin, María Victoria / Eiras-Mariño, María / Martínez-Salgado, Adrián / Taboada-Muñiz, Manuel / Reija-López, Laura / Souaf, Souhayla / García-Carro, Javier / Fernández-González, Ángel Luis / Adrio-Nazar, Belén / González-Juanatey, José Ramón / Eiras, Sonia / Rodríguez-Mañero, Moisés

Journal of clinical medicine

2023  Volume 12, Issue 10

Abstract: Post-operative atrial fibrillation (POAF) is the most common arrhythmia in the post-operative period after cardiac surgery. We aim to investigate the main clinical, local, and/or peripheral biochemical and molecular predictors for POAF in patients ... ...

Abstract Post-operative atrial fibrillation (POAF) is the most common arrhythmia in the post-operative period after cardiac surgery. We aim to investigate the main clinical, local, and/or peripheral biochemical and molecular predictors for POAF in patients undergoing coronary and/or valve surgery. Between August 2020 and September 2022, consecutive patients undergoing cardiac surgery without previous history of AF were studied. Clinical variables, plasma, and biological tissues (epicardial and subcutaneous fat) were obtained before surgery. Pre-operative markers associated with inflammation, adiposity, atrial stretch, and fibrosis were analyzed on peripheral and local samples with multiplex assay and real-time PCR. Univariate and multivariate logistic regression analyses were performed in order to identify the main predictors for POAF. Patients were followed-up until hospital discharge. Out of 123 consecutive patients without prior AF, 43 (34.9%) developed POAF during hospitalization. The main predictors were cardiopulmonary bypass time (odds ratio (OR) 1.008 (95% confidence interval (CI), 1.002-1.013),
Language English
Publishing date 2023-05-19
Publishing country Switzerland
Document type Journal Article
ZDB-ID 2662592-1
ISSN 2077-0383
ISSN 2077-0383
DOI 10.3390/jcm12103565
Database MEDical Literature Analysis and Retrieval System OnLINE

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