Piecewise nonlinear mixed-effects models for modeling cardiac function and assessing treatment effects.

Piecewise nonlinear mixed-effects models for modeling cardiac function and assessing treatment effects.
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DOI:
10.1016/j.cmpb.2012.11.007
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发表时间:
2013-06
影响因子:
6.1
通讯作者:
Kong M
Kong M
中科院分区:
工程技术2区
文献类型:
--
作者:
Jang H;Conklin DJ;Kong M

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Mixed-effects model is an efficient tool for analyzing longitudinal data. The random effects in a mixed-effects model can be used to capture the correlations among repeated measurements within a subject. Mixed effects model can be used to describe individual response profile as well as population response profile. In this manuscript, we apply mixed-effects models to the repeated measurements of cardiac function variables including heart rate, coronary flow, and left ventricle developed pressure (LVDP) in the isolated, Langendorff-perfused hearts of glutathione s-transferase P1/P2 (GSTP) gene knockout and wild-type mice. Cardiac function was measured before and during ischemia/reperfusion injury in these hearts. To describe the dynamics of each cardiac function variable during the entire experiment, we developed piecewise nonlinear mixed-effects models and a change point nonlinear mixed effect model. These models can be used to examine how cardiac function variables were altered by ischemia/reperfusion-induced injury and to compare the cardiac function variable between genetically engineered (null or transgenic) mice and wild-type mice. Hypothesis tests were constructed to evaluate the impact of deletion of GSTP gene for different cardiac function variables. These findings provide a new application for mixed-effects models in physiological and pharmacological studies of the isolated Langendorff-perfused heart.
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