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Kidney Week

Abstract: FR-PO0344

Urine Albumin-to-Creatinine Ratio (UACR) Assessment and Health Care Resource Utilization (HRU) in Patients with CKD with and Without Type 2 Diabetes

Session Information

Category: Diabetic Kidney Disease

  • 702 Diabetic Kidney Disease: Clinical

Authors

  • Mares, Jon, Bayer Corporation, Whippany, New Jersey, United States
  • Taliercio, Jonathan J., Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Zajichek, Alex, Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Shokles, Cassidy, Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Milinovich, Alex T., Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Katta, Arvind, Bayer Corporation, Whippany, New Jersey, United States
  • Martyn-Dow, Blaine, Bayer Corporation, Whippany, New Jersey, United States
  • Misra-Hebert, Anita D., Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Aldworth, Carolina A R, Bayer Corporation, Whippany, New Jersey, United States
  • Zimmerman, Robert, Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Pantalone, Kevin M., Cleveland Clinic Foundation, Cleveland, Ohio, United States
  • Rotroff, Daniel M, Cleveland Clinic Foundation, Cleveland, Ohio, United States
Background

The Kidney Disease: Improving Global Outcomes (KDIGO) prediction heatmap is a widely accepted tool for early recognition and progression of chronic kidney disease (CKD) based on eGFR and albuminuria levels. Recent evidence has shown low rates of albuminuria testing among patients with hypertension or diabetes, while albuminuria presence was associated with higher use of RAAS and SGLT2 inhibitors. Therefore, we examined the rates of urine albumin to creatinine ratio (UACR) testing in real-world practice among patients with CKD with and without T2D.

Methods

We utilized Cleveland Clinic electronic health record data from 12/1/2011 to 8/1/2024 to identify eligible adult patients with moderate or high prognostic risk of CKD per KDIGO heatmap staging (N=29,985). Patients were required to have 2 eGFR or UACR measurements 90 to 365 days apart for initial category mapping. Index date was the earliest record where patients had 2 consecutive and consistent KDIGO risk categories. Patients were compared by baseline T2D status. Outcomes of interest included UACR testing (tests ordered vs tests completed) and HRU (healthcare professional visits, emergency department visits, and hospitalizations).

Results

Measures of UACR were comparable across groups; however, a diagnosis of T2D was associated with higher HRU. Patients not diagnosed with T2D had a higher proportion of incomplete UACR orders compared to patients previously diagnosed with T2D. Further results are described in the table below.

Conclusion

While HRU was generally similar across groups, the analysis of UACR testing revealed a gap in completion rates of orders, highlighting potential issues identifying CKD progression, particularly when utilizing the KDIGO heatmap.

Initial CKD risk category and T2D statusNo T2DHas T2Da
ModerateHighModerateHigh
N=2,486N=1,602N=18,015N=7,882
UACR
Number of UACR labs ordered48,65840,273375,919174,462
% UACR not completed41%43.3%31%32%
HRU, median (IQR)
HCP visit49 (25,84)46 (23,78)54 (26,92)61 (33,98)
ED visit1 (0,3)1 (0,4)2 (0,5)2 (0,4)
Hospitalizations2 (0,4)2 (0,5)3 (1,7)2 (1,6)

a. Had T2D regardless of whether diagnosis came prior to or after CKD diagnosis.

Funding

  • Commercial Support – Bayer HealthCare

Digital Object Identifier (DOI)