Suppr超能文献

来自英国生物银行电子病历的偏差校正血清肌酐为肾功能轨迹生成了重要的数据资源。

Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories.

作者信息

Gorski Mathias, Wiegrebe Simon, Burkhardt Ralph, Behr Merle, Küchenhoff Helmut, Stark Klaus J, Böger Carsten A, Heid Iris M

机构信息

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Statistical Consulting Unit StaBLab, Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany.

出版信息

Sci Rep. 2025 Jan 28;15(1):3540. doi: 10.1038/s41598-025-85391-7.

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/1.73m/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.

摘要

肾功能丧失是一项沉重的个人和公共卫生负担。肾功能通常根据血清肌酐,通过估算肾小球滤过率(eGFR)来评估。英国生物银行提供了来自研究中心评估的血清肌酐测量值(SC,基线时n = 425,147,随访时n = 15,314),而新兴的电子病历(eMR,“全科医生临床数据”)为纵向扩充这些数据提供了一个很有前景的资源。然而,基于电子病历和基于研究中心评估的肌酐值能否联合用于eGFR下降的研究尚不清楚。在按日历年比较基于电子病历和基于研究中心评估的肌酐值时(n = 70,231),我们发现基于电子病历的肌酐值存在逐年变化的乘性偏差,且该偏差随时间减小(2007年为0.84,2013年为0.97)。基于研究中心评估的肌酐值以及经偏差校正的基于电子病历的肌酐值得出的eGFR,纳入了454,907名有≥1次eGFR评估的个体(共2,102,174次评估)。这其中包括206,063名在长达60.2年中有≥2次评估的个体(中位数为6.00次评估,中位时间 = 8.7年),在此期间我们还获取了基于电子病历的肾脏疾病或肾脏替代治疗信息。我们发现,未进行偏差校正时eGFR的年下降率为0.11(95%置信区间 = 0.10 - 0.12),进行偏差校正后为1.04 mL/min/1.73m²/年(95%置信区间 = 1.03 - 1.05),后者与文献相符。总之,我们经偏差校正的基于电子病历的肌酐值使得英国生物银行中适用于肾功能研究的eGFR评估数量增加了4倍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a91/11775100/24feadd5da4f/41598_2025_85391_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验