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Kidney Week

Abstract: FR-PO0338

Risk of Kidney Failure by Diagnosis and Histology in Diabetes

Session Information

Category: Diabetic Kidney Disease

  • 702 Diabetic Kidney Disease: Clinical

Authors

  • Tuttle, Katherine R., Providence Health and Services, Spokane, Washington, United States
  • Kornowske, Lindsey M., Providence Health and Services, Spokane, Washington, United States
  • Zuckerman, Jonathan E., University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, United States
  • Shpaner, Leonid, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, United States
  • Petousis, Panayiotis, University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, United States
  • Nast, Cynthia C., Cedars-Sinai, Los Angeles, California, United States
  • Nicholas, Susanne B., University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, United States
  • Norris, Keith C., University of California Los Angeles David Geffen School of Medicine, Los Angeles, California, United States
  • Jones, Cami R., Providence Health and Services, Spokane, Washington, United States
  • Inampudi, Chakradhari, Medical University of South Carolina, Charleston, South Carolina, United States
  • Daratha, Kenn B., Providence Health and Services, Spokane, Washington, United States
  • Bruce, Marino A., University of Houston System, Houston, Texas, United States
  • Alicic, Radica Z., Providence Health and Services, Spokane, Washington, United States

Group or Team Name

  • CURE-CKD Consortium.
Background

Risk of kidney failure with diabetic nephropathy (DN) versus another diagnosis (non-DN) or mixed-DN (DN and non-DN) diagnosis is unknown. This study evaluated kidney biopsies from patients with diabetes for diagnosis and histology to predict kidney failure.

Methods

The study included patients with diabetes who had a kidney biopsy at Providence and UCLA Health systems in 2015-2017. Pathology reports for diagnosis and histologic features, and demographic and clinical data were extracted from electronic health records. Patients were followed from biopsy through 2023 for kidney failure (estimated glomerular filtration rate-eGFR <15 mL/min/1.73 m2, dialysis, or kidney transplant) and death. Cumulative incidence (CMI) was estimated and SHapley Additive exPlanations (SHAP) analysis of random survival forests ranked predictors of kidney failure with competing risk of death.

Results

The study population (N=477) was 54% male and had a mean±SD age of 60±12 years. Baseline eGFR was 38±26 mL/min/1.73 m2 and median (interquartile range) urine protein-to-creatinine ratio (UPCR) was 5 (2-9) g/g. Median follow-up was 6.4 (5.2-7.5) years. The 2-year CMI (95% confidence interval [CI]) for kidney failure was highest in the group with DN (n=192; 60% [53%-67%]), followed by mixed-DN (n=181; 53% [45%-60%]), and non-DN (n=104; 39% [29%-48%], Figure A). CMIs for death were much lower. The top 10 predictors of kidney failure (SHAP C-index 0.23) were lower eGFR, nodular sclerosis, younger age, higher social vulnerability index, higher UPCR, arteriolar hyalinosis, higher body mass index, higher HbA1c, DN diagnosis, and >50% global glomerulosclerosis (Figure B).

Conclusion

Kidney failure occurred in over half of patients with DN or mixed-DN diagnoses within 2 years of biopsy. The most important predictors were specific histological features and DN along with clinical characteristics and social determinants.

Cumulative incidence and predictors of kidney failure

Funding

  • Commercial Support – Goldfinch Bio

Digital Object Identifier (DOI)