Chronic kidney disease (CKD) is a global public health problem that is associated with excess morbidity, mortality, and health resource utilization. The progression of CKD is defined by a decrease in glomerular filtration rate and leads to a variety of metabolic abnormalities including acidosis, hypertension, anemia, and mineral bone disorder. Lower glomerular filtration rate also bears a strong relationship with an increased risk of cardiovascular events, end-stage renal disease, and death. Patterns of CKD progression include linear and nonlinear trajectories, but kidney function can remain stable for years in some individuals. Addressing modifiable risk factors for the progression of CKD is needed to attenuate its associated morbidity and mortality. Developing effective risk prediction models for CKD progression is critical to identify patients who are more likely to benefit from interventions and more intensive monitoring. Accurate risk-prediction algorithms permit systems to best align health care resources with risk to maximize their effects and efficiency while guiding overall decision making.
Keywords: CKD; progression; risk prediction.
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