Kidney Week

Abstract: SA-PO801

Risk Prediction for Early Post-Donation Kidney Dysfunction in Live Kidney Donors Using a Common Data Model

Session Information

• Transplantation: Clinical - Pretransplant Assessment and Living Donors
  November 05, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
  Abstract Time: 10:00 AM - 12:00 PM

Category: Transplantation

• 2002 Transplantation: Clinical

Authors

• Park, Sehoon, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)

Sehoon Park,

• Kang, Eunjeong, Ewha Womans University Seoul Hospital, Seoul, Korea (the Republic of)

Eunjeong Kang,

• Kim, Sejoong, Seoul National University Bundang Hospital, Seongnam, Korea (the Republic of)

Sejoong Kim,

• Joo, Kwon Wook, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)

Kwon Wook Joo,

• Kim, Yon Su, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)

Yon Su Kim,

• Lee, Hajeong, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)

Hajeong Lee,

Background

Determination of the prognosis of living kidney donors is important. Impairment of early post-donation kidney function is associated with a higher risk of long-term kidney failure. Therefore, a prediction model for early post-donation kidney function in living kidney donors is warranted.

Methods

Common Data Model was implemented for inclusion of uniform data from three tertiary hospitals in Korea. The development cohort consisted of living kidney donors at Seoul National University Hospital (N=1074), and the two validation cohorts consisted of 2595 and 189 living kidney donors from other hospitals in Korea. Logistic regression analysis was performed for insufficient kidney function recovery, comprising estimated glomerular filtration rates (eGFRs) <60 and <50 mL/min/1.73 m² . Variables that were associated with most of these study outcomes were selected for construction of the final prediction model, a multivariable logistic regression model.

Results

Among the study cohorts, 10%-35% of living kidney donors had an eGFR <60 mL/min/1.73 m² and 3%-9% had an eGFR <50 mL/min/1.73 m² in the outcome-assessment period. Older age, male sex, higher body mass index, lower baseline eGFR, higher serum uric acid concentration, and the occurrence of postoperative acute kidney injury were included in the final prediction model. The model yielded acceptable discriminative power (AUC≥0.88) in both the development and validation cohorts. The calibration results were also acceptable (Hosmer-Lemeshow test, all P values but one were >0.05. A risk calculator for the four study outcomes was developed and published online (https://snuhnephrology.github.io/).

Conclusion

We constructed an easily accessible and useful risk prediction calculator for early post-donation kidney function.