Kidney Week

Abstract: FR-PO345

Glomerular Filtration Rate by Differing Measures and Prediction Utility of Peripheral Artery Disease

Session Information

• Hypertension, CVD, and the Kidneys: Epidemiology
  October 25, 2024 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Hypertension and CVD

• 1602 Hypertension and CVD: Clinical

Authors

• Li, Chenglong, Peking University Health Science Center, Beijing, Beijing, China

Chenglong Li, PhD

• He, Daijun, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Daijun He, MD, PhD

• Gao, Bixia, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Bixia Gao

• Yang, Chao, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Chao Yang, MS, MPH

• Wang, Jinwei, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Jinwei Wang, PhD

• Zhao, Ming-Hui, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Ming-Hui Zhao, MD, PhD

• Zhang, Luxia, Peking University First Hospital Department of Nephrology, Beijing, Beijing, China

Luxia Zhang, MD, MPH

Background

The utility of creatinine-based estimate glomerular filtration rate (eGFRcr) for predicting peripheral artery disease (PAD) has been evaluated. However, some guides recommended incorporating cystatin C, either alone or in combination with creatinine, into eGFR formulae, which perform better than eGFRcr in estimating GFR and in predicting the risk of cardiovascular disease and mortality. Therefore, we aimed to determine whether incorporating cystatin C into eGFR formulae would improve risk stratification and prediction for PAD.

Methods

We included 466,245 participants free of PAD at baseline (2006 to 2010) from the UK Biobank. The 2012 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) cystatin C equation and 2021 race-free CKD-EPI equations were used to calculate eGFRcys, eGFRcr, and eGFRcr-cys, respectively. Incidence of PAD was ascertained using electronic health records. Cox proportional hazards regression models were used to evaluate the associations of eGFRs with PAD. The relative importance of differentiating eGFRs in predicting PAD was evaluated. We also calculated net reclassification improvement and integrated discrimination improvement to examine the additive value of eGFRs in predicting PAD.

Results

During a median follow-up of 13.8 years, a total of 7,210 PAD cases were recorded. eGFRcys was most evidently associated with PAD and the most important predictor for PAD. Regardless of the eGFRcr, the adjusted incidence rate (aIR) and the hazard ratios (HRs) of PAD were low when eGFRcys≥60 mL/min/1.73 m². Conversely, with eGFRcys<60 mL/min/1.73 m², the aIR and the HRs of PAD have no difference between eGFRcr groups. eGFRcys presented the most significantly additive value in predicting PAD, while no significant utility was identified for eGFRcr.

Conclusion

eGFRcys appears to be more sensitive and specific for PAD risk. These findings underscore the importance of incorporating cystatin C into eGFR formulae to improve risk stratification and prediction for PAD.