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Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model
Statistical Methods in Medical Research (2016)
  • J Rajeswaran
  • Eugene Blackstone
  • John Ehrlinger
  • Liang Li
  • Hemant Ishwaran
  • MK Parides
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.
Publication Date
2016
Citation Information
J Rajeswaran, Eugene Blackstone, John Ehrlinger, Liang Li, et al.. "Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model" Statistical Methods in Medical Research (2016)
Available at: http://works.bepress.com/LiangLi-Biostatistician/8/