Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories
Abstract Loss of kidney function is a substantial personal and public health burden. Kidney function is typically assessed as estimated glomerular filtration rate (eGFR) based on serum creatinine. UK Biobank provides serum creatinine measurements from study center assessments (SC, n = 425,147 baseli...
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Nature Portfolio
2025-01-01
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| author | Mathias Gorski Simon Wiegrebe Ralph Burkhardt Merle Behr Helmut Küchenhoff Klaus J. Stark Carsten A. Böger Iris M. Heid |
| author_facet | Mathias Gorski Simon Wiegrebe Ralph Burkhardt Merle Behr Helmut Küchenhoff Klaus J. Stark Carsten A. Böger Iris M. Heid |
| author_sort | Mathias Gorski |
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| description | Abstract Loss of kidney function is a substantial personal and public health burden. Kidney function is typically assessed as estimated glomerular filtration rate (eGFR) based on serum creatinine. UK Biobank provides serum creatinine measurements from study center assessments (SC, n = 425,147 baseline, n = 15,314 with follow-up) and emerging electronic Medical Records (eMR, “GP-clinical”) present a promising resource to augment this data longitudinally. However, it is unclear whether eMR-based and SC-based creatinine values can be used jointly for research on eGFR decline. When comparing eMR-based with SC-based creatinine by calendar year (n = 70,231), we found a year-specific multiplicative bias for eMR-based creatinine that decreased over time (factor 0.84 for 2007, 0.97 for 2013). Deriving eGFR based on SC- and bias-corrected eMR-creatinine yielded 454,907 individuals with ≥ 1eGFR assessment (2,102,174 assessments). This included 206,063 individuals with ≥ 2 assessments over up to 60.2 years (median 6.00 assessments, median time = 8.7 years), where we also obtained eMR-based information on kidney disease or renal replacement therapy. We found an annual eGFR decline of 0.11 (95%-CI = 0.10–0.12) versus 1.04 mL/min/1.73m2/year (95%-CI = 1.03–1.05) without and with bias-correction, the latter being in line with literature. In summary, our bias-corrected eMR-based creatinine values enabled a 4-fold increased number of eGFR assessments in UK Biobank suitable for kidney function research. |
| format | Article |
| id | doaj-art-96ff6769823d494d8e22b04becd27b16 |
| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-96ff6769823d494d8e22b04becd27b162025-02-02T12:21:05ZengNature PortfolioScientific Reports2045-23222025-01-0115111310.1038/s41598-025-85391-7Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectoriesMathias Gorski0Simon Wiegrebe1Ralph Burkhardt2Merle Behr3Helmut Küchenhoff4Klaus J. Stark5Carsten A. Böger6Iris M. Heid7Department of Genetic Epidemiology, University of RegensburgDepartment of Genetic Epidemiology, University of RegensburgInstitute of Clinical Chemistry and Laboratory Medicine, University Hospital RegensburgFaculty of Informatics and Data Science, University of RegensburgStatistical Consulting Unit StaBLab, Department of Statistics, Ludwig-Maximilians-UniversitätDepartment of Genetic Epidemiology, University of RegensburgDepartment of Nephrology, University Hospital RegensburgDepartment of Genetic Epidemiology, University of RegensburgAbstract Loss of kidney function is a substantial personal and public health burden. Kidney function is typically assessed as estimated glomerular filtration rate (eGFR) based on serum creatinine. UK Biobank provides serum creatinine measurements from study center assessments (SC, n = 425,147 baseline, n = 15,314 with follow-up) and emerging electronic Medical Records (eMR, “GP-clinical”) present a promising resource to augment this data longitudinally. However, it is unclear whether eMR-based and SC-based creatinine values can be used jointly for research on eGFR decline. When comparing eMR-based with SC-based creatinine by calendar year (n = 70,231), we found a year-specific multiplicative bias for eMR-based creatinine that decreased over time (factor 0.84 for 2007, 0.97 for 2013). Deriving eGFR based on SC- and bias-corrected eMR-creatinine yielded 454,907 individuals with ≥ 1eGFR assessment (2,102,174 assessments). This included 206,063 individuals with ≥ 2 assessments over up to 60.2 years (median 6.00 assessments, median time = 8.7 years), where we also obtained eMR-based information on kidney disease or renal replacement therapy. We found an annual eGFR decline of 0.11 (95%-CI = 0.10–0.12) versus 1.04 mL/min/1.73m2/year (95%-CI = 1.03–1.05) without and with bias-correction, the latter being in line with literature. In summary, our bias-corrected eMR-based creatinine values enabled a 4-fold increased number of eGFR assessments in UK Biobank suitable for kidney function research.https://doi.org/10.1038/s41598-025-85391-7NephrologyKidneyMedical ResearchEpidemiology |
| spellingShingle | Mathias Gorski Simon Wiegrebe Ralph Burkhardt Merle Behr Helmut Küchenhoff Klaus J. Stark Carsten A. Böger Iris M. Heid Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories Scientific Reports Nephrology Kidney Medical Research Epidemiology |
| title | Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories |
| title_full | Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories |
| title_fullStr | Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories |
| title_full_unstemmed | Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories |
| title_short | Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories |
| title_sort | bias corrected serum creatinine from uk biobank electronic medical records generates an important data resource for kidney function trajectories |
| topic | Nephrology Kidney Medical Research Epidemiology |
| url | https://doi.org/10.1038/s41598-025-85391-7 |
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