Background: In many clinical trials and medical studies, the
survival and longitudinal data are collected simultaneously. When these two
outcomes are measured from each subject and the survival variable depends on a
longitudinal biomarker, using joint modelling of survival and longitudinal
outcomes is a proper choice for analyzing the available data.
Methods: In this retrospective archival study, 84 patients with coronary
artery bypass surgery admitted in the intensive care unit of Jamaran Hospital
in Tehran were randomly selected during 2001-2008. We defined the survival
event as the 25% decline in GFR from baseline and the repeated measurements of
urinary output from ICU admission to time of event as the longitudinal
biomarker.
Results: The study showed that older age (HR=1.112), male sex
(HR= 4.307), and number of bypassed grafts (HR=1.874) were
significant effective factors on reducing the amount of GFR and risk stage of
acute kidney injury event.
Conclusion: In this study, it was concluded that decreasing urinary
output can be considered as an informative medical biomarker for acute kidney
injury. Moreover, joint modeling of longitudinal and survival data which
considers the relationship between these two outcomes, is an efficient approach
for analyzing these kinds of datasets.
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