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Updated: Sep 1, 2025

Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP
Kunihiro Matsushita1, Stephen Kaptoge2, Steven H J Hageman3
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Insights
New add-on tools incorporating chronic kidney disease (CKD) measures significantly improve cardiovascular disease (CVD) risk prediction for patients, enhancing current risk algorithms like SCORE2 and SCORE2-OP.
Area of Science:
- Cardiology
- Nephrology
- Public Health
Background:
- The 2021 European Society of Cardiology (ESC) guideline classifies moderate to severe chronic kidney disease (CKD) as high/very-high cardiovascular disease (CVD) risk.
- Current CVD risk algorithms (SCORE2, SCORE2-OP) do not incorporate estimated glomerular filtration rate (eGFR) or albuminuria for risk prediction.
Purpose of the Study:
- To develop and validate 'Add-on' algorithms that integrate CKD measures (eGFR, albuminuria) into existing CVD risk prediction tools.
- To enhance the accuracy of CVD risk stratification in patients with CKD.
Main Methods:
- Developed three Add-ons: eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR), and eGFR + dipstick proteinuria.
- Validated these Add-ons using C-statistics and net reclassification improvement (NRI) in large datasets (over 3 million participants for development, nearly 6 million for validation).
- Accounted for competing risks of non-CVD mortality.
Main Results:
- The CKD Add-ons (eGFR only, eGFR + ACR) significantly improved C-statistics for SCORE2 and SCORE2-OP in populations without and with diabetes.
- The primary Add-on (eGFR + ACR) demonstrated notable improvements in risk prediction.
- In European participants with CKD, SCORE2/SCORE2-OP with a CKD Add-on showed significant net reclassification improvement compared to the ESC guideline's qualitative approach.
Conclusions:
- Add-on algorithms incorporating CKD measures substantially improve CVD risk prediction beyond existing SCORE2 and SCORE2-OP models.
- This approach enables more precise risk assessment for individuals with CKD.
- Facilitates personalized preventive therapy strategies for CVD in CKD patients.
Aims:
The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach.
Methods:
In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets.
Results:
In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline.
Conclusion:
Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.
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