Development and external validation of predictive models for prevalent and recurrent atrial fibrillation: a protocol for the analysis of the CATCH ME combined dataset

Background: Atrial fibrillation (AF) is caused by different mechanisms but current treatment strategies do not target these mechanisms. Stratified therapy based on mechanistic drivers and biomarkers of AF have the potential to improve AF prevention and management outcomes. We will integrate mechanistic insights with known pathophysiological drivers of AF in models predicting recurrent AF and prevalent AF to test hypotheses related to AF mechanisms and response to rhythm control therapy. Methods: We will harmonise and combine baseline and outcome data from 12 studies collected by six centres from the United Kingdom, Germany, France, Spain, and the Netherlands which assess prevalent AF or recurrent AF. A Delphi process and statistical selection will be used to identify candidate clinical predictors. Prediction models will be developed in patients with AF for AF recurrence and AF-related outcomes, and in patients with or without AF at baseline for prevalent AF. Models will be used to test mechanistic hypotheses and investigate the predictive value of plasma biomarkers. Discussion: This retrospective, harmonised, individual patient data analysis will use information from 12 datasets collected in five European countries. It is envisioned that the outcome of this analysis would provide a greater understanding of the factors associated with recurrent and prevalent AF, potentially allowing development of stratified approaches to prevention and therapy management

Heart Failure, Female Sex, and Atrial Fibrillation Are the Main Drivers of Human Atrial Cardiomyopathy: Results From the CATCH ME Consortium

Background: Atrial cardiomyopathy (atCM) is an emerging prognostic factor in cardiovascular disease. Fibrotic remodeling, cardiomyocyte hypertrophy, and capillary density are hallmarks of atCM. The contribution of etiological factors and atrial fibrillation (AF) to the development of differential atCM phenotypes has not been quantified. This study aimed to evaluate the association between histological features of atCM and the clinical phenotype. Methods and results: We examined left atrial (LA, n=95) and right atrial (RA, n=76) appendages from a European cohort of patients undergoing cardiac surgery. Quantification of histological atCM features was performed following wheat germ agglutinin/CD31/vimentin staining. The contributions of AF, heart failure, sex, and age to histological characteristics were determined with multiple linear regression models. Persistent AF was associated with increased endomysial fibrosis (LA: +1.13±0.47 μm, P=0.038; RA: +0.94±0.38 μm, P=0.041), whereas total extracellular matrix content was not. Men had larger cardiomyocytes (LA: +1.92±0.72 μm, P<0.001), while women had more endomysial fibrosis (LA: +0.99±0.56 μm, P=0.003). Patients with heart failure showed more endomysial fibrosis (LA: +1.85±0.48 μm, P<0.001) and extracellular matrix content (LA: +3.07±1.29%, P=0.016), and a higher capillary density (LA: +0.13±0.06, P=0.007) and size (LA: +0.46±0.22 μm, P=0.044). Fuzzy k-means clustering of histological features identified 2 subtypes of atCM: 1 characterized by enhanced endomysial fibrosis (LA: +3.17 μm, P<0.001; RA: +2.86 μm, P<0.001), extracellular matrix content (LA: +3.53%, P<0.001; RA: +6.40%, P<0.001) and fibroblast density (LA: +4.38%, P<0.001), and 1 characterized by cardiomyocyte hypertrophy (LA: +1.16 μm, P=0.008; RA: +2.58 μm, P<0.001). Patients with fibrotic atCM were more frequently female (LA: odds ratio [OR], 1.33, P=0.002; RA: OR, 1.54, P=0.004), with persistent AF (LA: OR, 1.22, P=0.036) or heart failure (LA: OR, 1.62, P<0.001). Hypertrophic features were more common in men (LA: OR=1.33, P=0.002; RA: OR, 1.54, P=0.004). Conclusions: Fibrotic atCM is associated with female sex, persistent AF, and heart failure, while hypertrophic features are more common in men