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World Science and Technology-Modernization of Traditional Chinese Medicine ; (12): 1443-1448, 2017.
Article in Chinese | WPRIM | ID: wpr-696043

ABSTRACT

Multiple outcomes measured repeatedly for the same subject are common in longitudinal observation.If we use the approach by analyzing each outcome separately,it may lead to wrong conclusions due to the failure of accounting for joint evolution of different outcomes.To adequately capture the interdependence among multiple outcomes,we proposed a joint modeling for multivariate longitudinal data by constructing a linear mixed-effects model for each outcome and accommodating the relationship among multiple outcomes through correlation in random effects.Maximum likelihood method was adopted to estimate parameters in this model.The application of this method was demonstrated through the analysis of stroke data.

2.
Kidney Research and Clinical Practice ; : 182-191, 2017.
Article in English | WPRIM | ID: wpr-48163

ABSTRACT

BACKGROUND: In peritoneal dialysis, technique failure is an important metric to be considered. This study was performed in order to identify the relationship between trajectories of serum albumin levels and peritoneal dialysis technique failure on end-stage renal disease patients according to diabetic status. Furthermore, this study was performed to reveal predictors of serum albumin and technique failure simultaneously. METHODS: This retrospective cohort study included 300 (189 non-diabetic and 111 diabetic) end-stage renal disease patients on continuous ambulatory peritoneal dialysis treated in Al-Zahra Hospital, Isfahan, Iran, from May 2005 to March 2015. Bayesian joint modeling was carried out in order to determine the relationship between trajectories of serum albumin levels and peritoneal dialysis technique failure in the patients according to diabetic status. Death from all causes was considered as a competing risk. RESULTS: Using joint modeling approach, a relationship between trajectories of serum albumin with hazard of transfer to hemodialysis was estimated as −0.720 (95% confidence interval [CI], −0.971 to −0.472) for diabetic and −0.784 (95% CI, −0.963 to −0.587) for non-diabetic patients. From our findings it was showed that predictors of low serum albumin over time were time on peritoneal dialysis for diabetic patients and increase in age and time on peritoneal dialysis, history of previous hemodialysis, and lower body mass index in non-diabetic patients. CONCLUSION: The results of current study showed that controlling serum albumin over time in non-diabetic and diabetic patients undergoing continuous ambulatory peritoneal dialysis treatment can decrease risk of adverse outcomes during the peritoneal dialysis period.


Subject(s)
Humans , Body Mass Index , Cohort Studies , Iran , Joints , Kidney Failure, Chronic , Peritoneal Dialysis , Peritoneal Dialysis, Continuous Ambulatory , Renal Dialysis , Retrospective Studies , Serum Albumin
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