Evolution of association between renal and liver functions while awaiting heart transplant: An application using a bivariate multiphase nonlinear mixed effects model. (July 2018)

• Record Type: Journal Article
• Authors: Rajeswaran, Jeevanantham; Blackstone, Eugene H; Barnard, John
• Other Names: Dattner Itai guest-editor.; Huppert Amit guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 27:Number 7(2018)
• Page Start: 2216
• Page End: 2230
• Publication Date: 2018-07
• Subjects: Nonlinear model -- mixed effects model -- temporal decomposition -- bivariate mixed effects model -- evolution of correlation -- additive regression; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280216678022
• Languages: English
• ISSNs: 0962-2802

Abstract

In many longitudinal follow-up studies, we observe more than one longitudinal outcome. Impaired renal and liver functions are indicators of poor clinical outcomes for patients who are on mechanical circulatory support and awaiting heart transplant. Hence, monitoring organ functions while waiting for heart transplant is an integral part of patient management. Longitudinal measurements of bilirubin can be used as a marker for liver function and glomerular filtration rate for renal function. We derive an approximation to evolution of association between these two organ functions using a bivariate nonlinear mixed effects model for continuous longitudinal measurements, where the two submodels are linked by a common distribution of time-dependent latent variables and a common distribution of measurement errors.