Joint modeling on serum creatinine and time to end stage of renal disease for chronic kidney disease patients under treatment at the University of Gondar Referral Hospital.

Abstract

Chronic kidney disease (CKD) is a major health problem worldwide. The general objective of this study is to identify the joint factors of serum creatinine (SCr) and time to end stage of renal disease(ESRD) for CKD patients under treatment at University of Gondar Referral Hospital (UOGRH). A retrospective cohort study was conducted. The collected information was secondary data type obtained from 311 CKD patient's medical charts in the UOGRH from September 2019 to January 2022 G.C. Joint modeling analysis contained a linear mixed model for SCr and the Cox-PH model for time to ESRD of CKD patients under treatment was used. From the total of 311 patients, 104 (33.4%) patients were developed the ESRD, while the other 207 (66.6%) were censored patients. In the longitudinal submodel, the variable sex, age, electrolyte, visit time, anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis have a significant effect on the variable SCr. In survival process, anemia (HR = 2.53, p = < 0.001), diabetes mellitus (HR = 2.206, p = < 0.0047), chronic heart disease (HR = 2.83, p = < 0.0011), HIV (HR = 2.778, p = < 0.0045), hypertension (HR = 2.616, p = < 0.001), and hepatitis (HR = 4.4, p = < 0.0074) have a significant effect on the variable ESRD. On the basis of the result of the joint model, the variable anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis were common significant factors. The majority of patients 207 (66.6%) of CKD patients were censored. On the basis of the smaller information criteria value and the significance association value, the joint model better fits the data. In the joint model, the variable anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis were common factors of two responses, and also concluded that the rate of progression of longitudinal measure SCr decreased over time.