Background
Chronic kidney disease (CKD) now affects 850 million individuals worldwide, exceeding the global prevalence of diabetes, cancer and HIV/AIDS. In addition, end-stage renal disease affects 7.4 million individuals and mortality rate for individuals burdened by kidney disease is now estimated at 5 to 10 million individuals each year. Therefore, developing better diagnostic and treatment approaches for the kidney disease epidemic is a global priority, as leading professional societies and health agencies have emphasized (the US Food \& Drug Administration, the National Kidney Foundation, the European Medicines Agency, the European Society of Organ Transplantation, the American Society for Transplantation and the American Society of Transplant Surgeons).
However, current approaches for investigating the relationship between eGFR course and outcomes such as ESRD and mortality have been limited by registries with an overall lack on granular data, including infrequent eGFR measurements for a single patient and convenience clinical samples. An unsupervised longitudinal approach to determine patient eGFR evolution may bring an original perspective to the traditional clinical interpretation of kidney function based on limited eGFR measurements, short-term follow-up, and standard statistical approach.
Main Outcome(s) and Measure(s)
* eGFR trajectories
* Determinants of eGFR trajectories
* Associations of eGFR trajectories with ESRD and death
* Prediction system that will provide the personalized probabilities of belonging to eGFR trajectories
