Kidney Week

Abstract: PUB560

Bioelectrical Impedance Markers as Predictors of CKD Progression

Session Information

• Publication Only

Category: CKD (Non-Dialysis)

• 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Yen, Timothy E., The University of Mississippi Medical Center, Jackson, Mississippi, United States

Timothy E. Yen, MD

• Zhu, Xiaoqian, The University of Mississippi Medical Center, Jackson, Mississippi, United States

Xiaoqian Zhu, PhD

• Tio, Maria Clarissa, The University of Mississippi Medical Center, Jackson, Mississippi, United States

Maria Clarissa Tio, MD, MPH, FASN

• Obi, Yoshitsugu, The University of Mississippi Medical Center, Jackson, Mississippi, United States

Yoshitsugu Obi, MD, PhD, FASN

• Hall, Michael E., The University of Mississippi Medical Center, Jackson, Mississippi, United States

Michael E. Hall, MD, MS

• Dossabhoy, Neville R., The University of Mississippi Medical Center, Jackson, Mississippi, United States

Neville R. Dossabhoy, MD, FASN

• Shafi, Tariq, Houston Methodist Hospital, Houston, Texas, United States

Tariq Shafi, MBBS, MHS, FASN

Background

Bioelectric Impedance Analysis (BIA) objectively quantifies body composition metrics which change during CKD progression. The predictive utility of BIA metrics for outcomes in CKD, especially in advanced disease, is unknown.

Methods

We analyzed 3,632 participants from the Chronic Renal Insufficiency Cohort (total-CRIC) (data provided by NIDDK CR) and a sub-group of 1771 participants with advanced CKD (<30 eGFR, mL/min/1.73 m²) which was comprised of individuals who started with or progressed to advanced CKD during the study. We analyzed BIA metrics—total body water (TBW, kg), vector length (VL, Ω), phase angle (PA, °), and fat free mass (FFM, kg) as continuous variables. We used multivariable Cox proportional hazard models to examine the associations of each BIA metric with incident CKD progression (≥50% eGFR decline or ESKD) in total-CRIC, and with incident ESKD in the advanced CKD group. We calculated three risks scores--the 2-year and 5-year Kidney Failure Risk Equation (KFRE), and CKD Prognosis Consortium (CKD-PC) 3-year risk score for 40% eGFR decline or ESKD--and evaluated if BIA metrics improved prediction of CKD progression or ESRD compared to using these risk scores alone (Harrel’s C).

Results

In the total population, mean age was 58 years, 46% were women, 42% were Black persons, and mean eGFR was 42. In unadjusted models, TBW, VL and FFM were associated with CKD progression in total-CRIC, while VL and FFM were associated with ESKD in advanced CKD. Associations were statistically insignificant after multivariable adjustment (Table). Addition of the BIA parameters did not significantly improve prediction of CKD progression or ESRD (Harrel’s C) compared to models using KFRE or CKD-PC risk alone in either group.

Conclusion

BIA, although widely available and easily implementable, did not improve prediction of CKD progression beyond existing risk factors. Our study highlights the limitations of existing technologies and the need for innovation to advance precision medicine for individuals with CKD.