基于血浆肌酐和CT扫描评估的肌肉量来估算肾小球滤过率的新方程的开发与验证：一项横断面研究
Development and validation of a new equation based on plasma creatinine and muscle mass assessed by CT scan to estimate glomerular filtration rate: a cross-sectional study.
作者信息
Stehlé Thomas, Ouamri Yaniss, Morel Antoine, Vidal-Petiot Emmanuelle, Fellahi Soraya, Segaux Lauriane, Prié Dominique, Grimbert Philippe, Luciani Alain, Audard Vincent, Haymann Jean Philippe, Mulé Sébastien, De Kerviler Eric, Peraldi Marie-Noëlle, Boutten Anne, Matignon Marie, Canouï-Poitrine Florence, Flamant Martin, Pigneur Frédéric
机构信息
Univ. Paris Est Créteil, Institut National de la Santé et de la Recherche Médicale (INSERM) U955, Institut Mondor de Recherche Biomédicale (IMRB), Créteil, France.
Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpitaux Universitaires Henri Mondor, Service de Néphrologie et Transplantation, Fédération Hospitalo-Universitaire « Innovative therapy for immune disorders », Créteil, France.
出版信息
Clin Kidney J. 2023 Jan 20;16(8):1265-1277. doi: 10.1093/ckj/sfad012. eCollection 2023 Aug.
BACKGROUND
Inter-individual variations of non-glomerular filtration rate (GFR) determinants of serum creatinine, such as muscle mass, account for the imperfect performance of estimated GFR (eGFR) equations. We aimed to develop an equation based on creatinine and total lumbar muscle cross-sectional area measured by unenhanced computed tomography scan at the third lumbar vertebra.
METHODS
The muscle mass-based eGFR (MMB-eGFR) equation was developed in 118 kidney donor candidates (iohexol clearance) using linear regression. Validation cohorts included 114 healthy subjects from another center (Cr-EDTA clearance, validation population 1), 55 patients with chronic diseases (iohexol, validation population 2), and 60 patients with highly discordant creatinine and cystatin C-based eGFR, thus presumed to have atypical non-GFR determinants of creatinine (Cr-EDTA, validation population 3). Mean bias was the mean difference between eGFR and measured GFR, precision the standard deviation (SD) of the bias, and accuracy the percentage of eGFR values falling within 20% and 30% of measured GFR.
RESULTS
In validation population 1, performance of MMB-eGFR was not different from those of CKD-EPI and CKD-EPI. In validation population 2, MMB-eGFR was unbiased and displayed better precision than CKD-EPI, CKD-EPI and EKFC (SD of the biases: 13.1 vs 16.5, 16.8 and 15.9 mL/min/1.73 m). In validation population 3, MMB-eGFR had better precision and accuracy {accuracy within 30%: 75.0% [95% confidence interval (CI) 64.0-86.0] vs 51.5% (95% CI 39.0-64.3) for CKD-EPI, 43.3% (95% CI 31.0-55.9) for CKD-EPICr2021, and 53.3% (95% CI 40.7-66.0) for EKFC}. Difference in bias between Black and white subjects was -2.1 mL/min/1.73 m (95% CI -7.2 to 3.0), vs -8.4 mL/min/1.73 m (95% CI -13.2 to -3.6) for CKD-EPI.
CONCLUSION
MMB-eGFR displayed better performances than equations based on demographics, and could be applied to subjects of various ethnic backgrounds.
背景
血清肌酐的非肾小球滤过率（GFR）决定因素（如肌肉量）的个体间差异导致估算肾小球滤过率（eGFR）方程的性能欠佳。我们旨在基于肌酐和通过第三腰椎水平的非增强计算机断层扫描测量的腰椎总肌肉横截面积开发一个方程。
方法
基于肌肉量的eGFR（MMB-eGFR）方程通过线性回归在118名肾脏供体候选者（碘海醇清除率）中开发。验证队列包括来自另一个中心的114名健康受试者（铬-乙二胺四乙酸清除率，验证人群1）、55名慢性病患者（碘海醇，验证人群2）以及60名肌酐和基于胱抑素C的eGFR差异很大的患者，因此推测这些患者具有非典型的肌酐非GFR决定因素（铬-乙二胺四乙酸，验证人群3）。平均偏差是eGFR与测量的GFR之间的平均差值，精密度是偏差的标准差（SD），准确度是eGFR值落在测量的GFR的20%和30%范围内的百分比。
结果
在验证人群1中，MMB-eGFR的性能与慢性肾脏病流行病学合作组（CKD-EPI）和慢性肾脏病流行病学合作组（CKD-EPI）的性能无差异。在验证人群2中，MMB-eGFR无偏差，且与CKD-EPI、CKD-EPI和欧洲肾脏协会-欧洲透析和移植协会（EKFC）相比显示出更好的精密度（偏差的SD：13.1对比16.5、16.8和15.9 mL/min/1.73 m²）。在验证人群3中，MMB-eGFR具有更好的精密度和准确度{30%以内的准确度：75.0%[95%置信区间（CI）64.0 - 86.0]，而CKD-EPI为51.5%（95% CI 39.0 - 64.3），CKD-EPICr2021为43.3%（95% CI 31.0 - 55.9），EKFC为53.3%（95% CI 40.7 - 66.0）}。黑人和白人受试者之间的偏差差异为 -2.1 mL/min/1.73 m²（95% CI -7.2至3.0），而CKD-EPI为 -8.4 mL/min/1.73 m²（95% CI -13.2至 -3.6）。
结论
MMB-eGFR比基于人口统计学的方程表现更好，并且可以应用于各种种族背景的受试者。
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