Keywords
Chronic kidney disease
Cardiovascular disease
Creatinine
Inulin
Cystatin C
How to Cite
Abstract
Context: Chronic kidney disease (CKD) represents a global public health challenge, with increasing prevalence driven by factors such as hypertension, diabetes, and obesity. Its strong association with cardiovascular disease (CVD) highlights the critical role of estimated glomerular filtration rate (eGFR) in assessing CKD progression and cardiovascular risk. Given its significance, refining eGFR estimations is essential for improving risk prediction and clinical management.
Objective: This study evaluates eGFR as a predictor of cardiovascular risk in CKD patients, assessing the accuracy of various estimation formulas and their clinical implications. Additionally, it explores emerging renal filtration abnormalities, such as glomerular hyperfiltration (GHF) and selective hypofiltration syndrome (SHS), which have gained attention for cardiovascular associations.
Methodology: A systematic literature review was conducted across major scientific databases, including PubMed, Ovid-MEDLINE, Web of Science, EMBASE, and Redalyc. The search covered publications from January 2000 to April 2024, focusing on studies that examined eGFR estimations based on creatinine (Cr) and cystatin C (Cys C) and their predictive utility for cardiovascular outcomes.
Results: Creatinine-based eGFR is widely used due to its accessibility; however, its precision is limited. Incorporating Cys C improves risk stratification for both CKD progression and cardiovascular events. Elevated eGFR values may signal overestimation rather than optimal kidney function, thus influencing cardiovascular risk assessment. Furthermore, SHS, associated with inflammatory markers and CVD, underscores the need for refined filtration assessments beyond conventional metrics.
Conclusions: Early CKD diagnosis is crucial for mitigating disease progression and reducing cardiovascular morbidity. While eGFR estimation has improved, significant variability persists. Integrating Cys C into predictive models and recognizing newly characterized filtration syndromes such as SHS and GHF may enhance cardiovascular risk assessment in CKD patients.
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