Work

Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model

Year: 2016

Type: article

Abstract: Atrial fibrillation is an arrhythmic disorder where the electrical signals of the heart become irregular. The probability of atrial fibrillation (binary response) is often time varying in a structured fashion, as is the influence of associated risk factors. A generalized nonlinear mixed effects model is presented to estimate the time-related probability of atrial fibrillation using a temporal decomposition approach to reveal the pattern of the probability of atrial fibrillation and their determinants. This methodology generalizes to patient-specific analysis of longitudinal binary data with possibly time-varying effects of covariates and with different patient-specific random effects influencing different temporal phases. The motivation and application of this model is illustrated using longitudinally measured atrial fibrillation data obtained through weekly trans-telephonic monitoring from an NIH sponsored clinical trial being conducted by the Cardiothoracic Surgery Clinical Trials Network.

Source: Statistical Methods in Medical Research

DOI: 10.1177/0962280215623583

Authors: Jeevanantham Rajeswaran, Eugene H Blackstone, John Ehrlinger, Liang Li, Hemant Ishwaran, Michael K Parides

Institutions: Cleveland Clinic, The University of Texas MD Anderson Cancer Center, University of Miami, Mount Sinai Hospital

Language: English

Topic: Atrial Fibrillation Management and Outcomes

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute