Modeling the Progression of Haematocrit Level over Time

Abstract

Abstract Haematocrit Levels is defined as the proportion, by volume, of the blood that consists of red blood cells. This study was conducted to model the progress of haematocrit levels over time in kidney patients after their transplant and to determine how the progress depends on the age and gender of the patient and other factors. This is a longitudinal study, and haematocrit level was considered as a response while the covariates were time, gender, age, cardio-vascular problem during the years preceding the transplantation, and rejection symptoms during the first three months after the transplantation took place of the patients. Different statistical methods such as, multivariate regression model, two stage analysis and linear mixed effects model were employed to explore the progress of haematocrit over time. Models revealed that haematocrit levels in kidney transplant patients evolve over time. Gender and Age of the patient have significant effect on the evolution of haematocrit levels. Males tend to have a high increase in haematocrit levels over time than females. With regards to age, haematocrit levels tend to increase with increasing age. Moreover, it was observed that experience of cardio-vascular problems before trandplant and rejection symptoms did not have a significant effect on the progress of haematicrit levels. The growth of Haematocrit levels evolve over time follows a quartic time effect. Change in haematocrit levels varies according to gender and age of the patient. Patients starting with low haematocrit levels tend to have a larger increase over time.

Keywords

• Kidney transplant
• Longitudinal data
• Multivariate regression
• Two stage analysis