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Clinical Implications of Estimating Glomerular Filtration Rate with Three Different Equations Among Older People. Preliminary Results of the Project "Screening for Chronic Kidney Disease among Older People across Europe (SCOPE)".

Andrea CorsonelloRegina Elisabeth Roller-WirnsbergerGerhard WirnsbergerJohan ÄrnlövAxel C CarlssonLisanne TapFrancesco U S Mattace-RasoFrancesc FormigaRafael Moreno-GonzalezChristian WeingartCornel SieberTomasz KostkaAgnieszka GuligowskaPedro GilSara Lainez MartinezRada Artzi-MedvedikItshak MelzerFabrizia Lattanzio
Published in: Journal of clinical medicine (2020)
We aimed at investigating to what extent CKD may be staged interchangeably by three different eGFR equations in older people, and evaluating the source of discrepancies among equations in a population of 2257 patients older than 75 years enrolled in a multicenter observational study. eGFR was calculated by CKD-EPI, BIS and FAS equations. Statistical analysis was carried out by Bland-Altman analysis. κ statistic was used to quantify the agreement between equations in classifying CKD stages. The impact of selected variables on the difference among equations was graphically explored. The average difference between BIS and FAS was -0.24 (95% limits of agreement (95%LA = -4.64-4.14) mL/min/1.73 m2. The difference between CKD-EPI and BIS and between CKD-EPI and FAS was 8.97 (95%LA = -2.90-20.84) and 8.72 (95%LA = -2.11-19.56) mL/min/1.73 m2, respectively. As regards CKD stage classification, κ value was 0.47 for both CKD-EPI vs. FAS and CKD-EPI vs. BIS, while BIS and FAS had similar classificatory properties (κ = 0.90). Muscle mass was found related to the difference between CKD-EPI and BIS (R2 = 0.11) or FAS (R2 = 0.14), but not to the difference between BIS and FAS. In conclusion, CKD-EPI and BIS/FAS equations are not interchangeable to assess eGFR among older people. Muscle mass may represent a relevant source of discrepancy among eGFR equations.
Keyphrases
  • chronic kidney disease
  • end stage renal disease
  • ionic liquid
  • small cell lung cancer
  • epidermal growth factor receptor
  • deep learning
  • machine learning
  • peritoneal dialysis
  • physical activity
  • cross sectional