Prediction of measured GFR after living kidney donation from pre-donation parameters
© The Author(s) 2022. Published by Oxford University Press on behalf of the ERA..
BACKGROUND: One of the challenges in living kidney donor screening is to estimate remaining kidney function after donation. Here we developed a new model to predict post-donation measured glomerular filtration rate (mGFR) from pre-donation serum creatinine, age and sex.
METHODS: In the prospective development cohort (TransplantLines, n = 511), several prediction models were constructed and tested for accuracy, precision and predictive capacity for short- and long-term post-donation 125I-iothalamate mGFR. The model with optimal performance was further tested in specific high-risk subgroups (pre-donation eGFR <90 mL/min/1.73 m2, a declining 5-year post-donation mGFR slope or age >65 years) and validated in internal (n = 509) and external (Mayo Clinic, n = 1087) cohorts.
RESULTS: In the development cohort, pre-donation estimated GFR (eGFR) was 86 ± 14 mL/min/1.73 m2 and post-donation mGFR was 64 ± 11 mL/min/1.73 m2. Donors with a pre-donation eGFR ≥90 mL/min/1.73 m2 (present in 43%) had a mean post-donation mGFR of 69 ± 10 mL/min/1.73 m2 and 5% of these donors reached an mGFR <55 mL/min/1.73 m2. A model using pre-donation serum creatinine, age and sex performed optimally, predicting mGFR with good accuracy (mean bias 2.56 mL/min/1.73 m2, R2 = 0.29, root mean square error = 11.61) and precision [bias interquartile range (IQR) 14 mL/min/1.73 m2] in the external validation cohort. This model also performed well in donors with pre-donation eGFR <90 mL/min/1.73 m2 [bias 0.35 mL/min/1.73 m2 (IQR 10)], in donors with a negative post-donation mGFR slope [bias 4.75 mL/min/1.73 m2 (IQR 13)] and in donors >65 years of age [bias 0.003 mL/min/1.73 m2 (IQR 9)].
CONCLUSIONS: We developed a novel post-donation mGFR prediction model based on pre-donation serum creatinine, age and sex.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:38 |
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| Enthalten in: |
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association - 38(2023), 1 vom: 23. Jan., Seite 212-221 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
van Londen, Marco [VerfasserIn] |
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| Links: |
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| Themen: |
AYI8EX34EU |
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| Anmerkungen: |
Date Completed 25.01.2023 Date Revised 02.02.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.1093/ndt/gfac202 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM342527460 |
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| 500 | |a Date Completed 25.01.2023 | ||
| 500 | |a Date Revised 02.02.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author(s) 2022. Published by Oxford University Press on behalf of the ERA. | ||
| 520 | |a BACKGROUND: One of the challenges in living kidney donor screening is to estimate remaining kidney function after donation. Here we developed a new model to predict post-donation measured glomerular filtration rate (mGFR) from pre-donation serum creatinine, age and sex | ||
| 520 | |a METHODS: In the prospective development cohort (TransplantLines, n = 511), several prediction models were constructed and tested for accuracy, precision and predictive capacity for short- and long-term post-donation 125I-iothalamate mGFR. The model with optimal performance was further tested in specific high-risk subgroups (pre-donation eGFR <90 mL/min/1.73 m2, a declining 5-year post-donation mGFR slope or age >65 years) and validated in internal (n = 509) and external (Mayo Clinic, n = 1087) cohorts | ||
| 520 | |a RESULTS: In the development cohort, pre-donation estimated GFR (eGFR) was 86 ± 14 mL/min/1.73 m2 and post-donation mGFR was 64 ± 11 mL/min/1.73 m2. Donors with a pre-donation eGFR ≥90 mL/min/1.73 m2 (present in 43%) had a mean post-donation mGFR of 69 ± 10 mL/min/1.73 m2 and 5% of these donors reached an mGFR <55 mL/min/1.73 m2. A model using pre-donation serum creatinine, age and sex performed optimally, predicting mGFR with good accuracy (mean bias 2.56 mL/min/1.73 m2, R2 = 0.29, root mean square error = 11.61) and precision [bias interquartile range (IQR) 14 mL/min/1.73 m2] in the external validation cohort. This model also performed well in donors with pre-donation eGFR <90 mL/min/1.73 m2 [bias 0.35 mL/min/1.73 m2 (IQR 10)], in donors with a negative post-donation mGFR slope [bias 4.75 mL/min/1.73 m2 (IQR 13)] and in donors >65 years of age [bias 0.003 mL/min/1.73 m2 (IQR 9)] | ||
| 520 | |a CONCLUSIONS: We developed a novel post-donation mGFR prediction model based on pre-donation serum creatinine, age and sex | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a living kidney donation | |
| 650 | 4 | |a renal function equations | |
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| 700 | 1 | |a Niznik, Robert S |e verfasserin |4 aut | |
| 700 | 1 | |a Mullan, Aidan F |e verfasserin |4 aut | |
| 700 | 1 | |a Bakker, Stephan J L |e verfasserin |4 aut | |
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| 700 | 1 | |a Rule, Andrew D |e verfasserin |4 aut | |
| 700 | 1 | |a de Borst, Martin H |e verfasserin |4 aut | |
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