Background: Biomarkers have been related to the arrhythmia recurrence following catheter ablation (CA) of atrial fibrillation (AF). We hypothesized that concurrent measurement of several biomarkers would additively improve their predictive value.
Methods: One thousand four hundred and ten consecutive AF patients (68% male; 57.2 ± 11.6 years) undergoing CA were enrolled. Baseline characteristics, serum B type brain natriuretic peptide (BNP) and high sensitivity C reactive protein (hsCRP), estimated glomerular filtration rate (eGFR), ablation parameters, arrhythmia data at discharge, 1, 3, 6, and then every 6 months post CA were collected. Follow-up ended when arrhythmia recurred or until 31st December 2016.
Results: Three hundred and sixty-five (25.9%) patients had arrhythmia recurrence post-CA during a mean follow-up of 20.7 ± 8.8 months. BNP, hsCRP, and eGFR levels and their cut-off values of 237.45 pg/mL, 1.6 mg/dL, and 82.5 mL/min/1.73 m were good predictors for AF recurrence (all < 0.01). On multivariate analysis, increasing BNP and hsCRP, decreasing eGFR, gender, and early recurrence (ER) were independent predictors of AF recurrence (all < 0.01). Compared to BNP alone, BNP plus eGFR or both eGFR and CRP showed incrementally better predictive values (ROC comparisons, all < 0.01). Similar findings were evident in the subgroups of patients with paroxysmal or nonparoxysmal AF.
Conclusion: Measurement of BNP, CRP, and eGFR were incrementally additive to clinical risk factors in a cumulative manner to improve prediction of arrhythmia recurrence post-CA of AF. The implications of poor arrhythmia outcome in AF patients with multiple abnormal biomarkers pre-CA procedure may help with patient selection and inform the likelihood of success or the need of more complicated CA procedure(s).
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http://dx.doi.org/10.1002/joa3.12111 | DOI Listing |
Curr Oncol Rep
January 2025
Department of Radiology, Albert Einstein College of Medicine and the Montefiore Medical Center, 111 East 210Th Street, Bronx, NY, 10461, USA.
Purpose Of Review: This paper reviewed the current literature on incidence, clinical manifestations, and risk factors of Chimeric Antigen Receptor T-cell (CAR-T) cardiotoxicity.
Recent Findings: CAR-T therapy has emerged as a groundbreaking treatment for hematological malignancies since FDA approval in 2017. CAR-T therapy is however associated with a few side effects, among which cardiotoxicity is of significant concern.
Eur J Clin Invest
January 2025
Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Liverpool, UK.
Cureus
December 2024
Internal Medicine, University of Health Sciences, Lahore, PAK.
Acute coronary syndrome (ACS) remains a major global health burden, encompassing a spectrum of conditions from unstable angina to acute myocardial infarction. Despite advancements in early detection and management, ACS is often complicated by the development of heart failure. This systematic review and meta-analysis aimed to identify factors associated with the development of heart failure following acute coronary syndrome.
View Article and Find Full Text PDFCureus
December 2024
Cardiology, Avicenna Military Hospital, Marrakesh, MAR.
Introduction Atrial fibrillation (AF), the most common cardiac arrhythmia, poses challenges in predicting thromboembolic risk. While the CHADS-VASc (congestive heart failure, hypertension, age ≥ 75 years (doubled), type 2 diabetes mellitus, previous stroke, transient ischemic attack, or thromboembolism (doubled), vascular disease, age 65-74 years, and sex category) score remains essential, its limitations include failure to identify left atrial (LA) thrombus in some patients. Transesophageal echocardiography (TEE) provides superior detection of LA thrombi and thrombogenic factors compared to transthoracic echocardiography (TTE), improving risk stratification, especially in intermediate-risk groups.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Introduction: The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.
Methods: The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet).
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