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Comparison of three creatinine-based equations to predict adverse outcome in a cardiovascular high-risk cohort: an
Insa E Emrich1,2, John W Pickering3, Felix Götzinger1,2
1Saarland University Medical Center, Department of Internal Medicine III, Cardiology, Angiology, and Intensive Care Medicine, Homburg, Germany.
Insights
New creatinine-based equations for estimating glomerular filtration rate (eGFR) do not improve cardiovascular event prediction in high-risk individuals compared to the established CKD-EPI 2009 equation. These updated formulas changed chronic kidney disease (CKD) prevalence but did not enhance risk assessment.
Area of Science:
- Nephrology
- Cardiology
- Epidemiology
Background:
- Novel creatinine-based equations for estimating glomerular filtration rate (eGFR) have emerged.
- Their comparative predictive performance for cardiovascular outcomes in high-risk populations against the CKD-EPI 2009 equation remains unclear.
Purpose of the Study:
- To evaluate the predictive accuracy of newer eGFR equations (CKD-EPI 2021 and EKFC) for cardiovascular events.
- To compare these predictions against the established CKD-EPI 2009 equation in a high-risk cohort.
Main Methods:
- Utilized data from 9361 participants in the SPRINT trial.
- Calculated baseline eGFR using CKD-EPI 2009, CKD-EPI 2021, and EKFC equations.
- Assessed predictive value for cardiovascular events using net reclassification improvement (NRI).
Main Results:
- CKD prevalence varied: CKD-EPI 2009 (37%), CKD-EPI 2021 (35.3%), EKFC (46.4%).
- Mean eGFR also differed: CKD-EPI 2009 (72.5), CKD-EPI 2021 (73.2), EKFC (64.6).
- Neither CKD-EPI 2021 nor EKFC significantly improved cardiovascular event prediction (NRI) compared to CKD-EPI 2009.
Conclusions:
- Updating eGFR calculation from CKD-EPI 2009 to CKD-EPI 2021 or EKFC in high-risk, non-diabetic individuals altered CKD prevalence.
- These newer equations did not enhance the prediction of cardiovascular events for individuals with or without events.
Background:
Novel creatinine-based equations have recently been proposed but their predictive performance for cardiovascular outcomes in participants at high cardiovascular risk in comparison to the established CKD-EPI 2009 equation is unknown.
Method:
In 9361 participants from the United States included in the randomized controlled SPRINT trial, we calculated baseline estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009, CKD-EPI 2021, and EKFC equations and compared their predictive value of cardiovascular events. The statistical metric used is the net reclassification improvement (NRI) presented separately for those with and those without events.
Results:
During a mean follow-up of 3.1 ± 0.9 years, the primary endpoint occurred in 559 participants (6.0%). When using the CKD-EPI 2009, the CKD-EPI 2021, and the EKFC equations, the prevalence of CKD (eGFR <60 ml/min/1.73 m2 or >60 ml/min/1.73 m2 with an ACR ≥30 mg/g) was 37% vs. 35.3% (P = 0.02) vs. 46.4% (P < 0.001), respectively. The corresponding mean eGFR was 72.5 ± 20.1 ml/min/1.73 m2 vs. 73.2 ± 19.4 ml/min/1.73 m2 (P < 0.001) vs. 64.6 ± 17.4 ml/min/1.73 m2 (P < 0.001). Neither reclassification according to the CKD-EPI 2021 equation [CKD-EPI 2021 vs. CKD-EPI 2009: NRIevents: -9.5% (95% confidence interval (CI) -13.0% to -5.9%); NRInonevents: 4.8% (95% CI 3.9% to 5.7%)], nor reclassification according to the EKFC equation allowed better prediction of cardiovascular events compared to the CKD-EPI 2009 equation (EKFC vs. CKD-EPI 2009: NRIevents: 31.2% (95% CI 27.5% to 35.0%); NRInonevents: -31.1% (95% CI -32.1% to -30.1%)).
Conclusion:
Substituting the CKD-EPI 2009 with the CKD-EPI 2021 or the EKFC equation for calculation of eGFR in participants with high cardiovascular risk without diabetes changed the prevalence of CKD but was not associated with improved risk prediction of cardiovascular events for both those with and without the event.
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