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Published on: June 16, 2014
The Patterns, Risk Factors, and Prediction of Progression in Chronic Kidney Disease: A Narrative Review
David Collister1, Thomas Ferguson1, Paul Komenda1
1Department of Medicine, University of Manitoba, Winnipeg, Canada; Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada; Chronic Disease Innovation Center, Seven Oaks General Hospital, Winnipeg, Canada.
Insights
Chronic kidney disease (CKD) is a global health issue. Developing risk prediction models is crucial for identifying patients who will benefit from interventions and intensive monitoring to manage CKD progression.
Area of Science:
- Nephrology
- Public Health
- Epidemiology
Background:
- Chronic kidney disease (CKD) presents a significant global health challenge, contributing to increased illness, death, and healthcare costs.
- CKD progression, marked by declining glomerular filtration rate, causes metabolic issues like acidosis, hypertension, anemia, and mineral bone disorder.
- Reduced kidney function is linked to higher risks of cardiovascular events, end-stage renal disease, and mortality.
Purpose of the Study:
- To highlight the need for addressing modifiable risk factors in CKD progression.
- To emphasize the importance of developing effective risk prediction models for CKD.
- To guide healthcare resource allocation and decision-making for CKD patient management.
Main Methods:
- Review of existing literature on CKD progression patterns.
- Analysis of factors influencing CKD progression trajectories (linear and nonlinear).
- Discussion on the utility of risk prediction models in clinical settings.
Main Results:
- CKD progression varies, with some patients maintaining stable kidney function for extended periods.
- Identifying modifiable risk factors is essential for mitigating CKD-related morbidity and mortality.
- Accurate risk prediction models can optimize interventions and monitoring.
Conclusions:
- Effective risk prediction models are vital for personalized CKD management.
- Targeting modifiable risk factors can attenuate CKD progression and its complications.
- Optimized risk stratification enhances healthcare efficiency and patient outcomes.
Abstract:
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.
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