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在印度人口中评估种族中立的淋巴膜过率估计方程
Ashok Kumar Yadav1, Jaskiran Kaur1, Prabhjot Kaur2
1Department of Experimental Medicine and Biotechnology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Kidney international reports
|December 19, 2024
概括
较新的功能估计方程,包括无种族模型,无法准确预测印度人口的膜过率 (GFR). 需要进一步的研究来开发印度人的特定GFR方程,以确保准确的诊断和护理.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 生物标志物 生物标志物
- 流行病学 流行病学
背景情况:
- 淋巴膜过率 (GFR) 估计方程需要在不同种群中进行验证.
- 现有的基于肌的方程,如CKD-EPICr2009可能会高估印度人的GFR.
- 已经提出了使用肌素和囊素C的较新的无种族方程.
研究的目的:
- 评估印度人口中最近开发的无种族估计GFR (eGFR) 方程的性能.
- 为了比较各种eGFR方程与测量的GFR (mGFR) 的准确性.
主要方法:
- 包括慢性病患者和潜在的脏捐赠者.
- 使用尿清除胰岛素和IOhexol的血清除率来测量GFR.
- 对eGFR方程的评估 (CKD-EPICr(2021),CKD-EPICr-Cys(2021),CKD-EPICr(2009)等等) 是一个非常简单的方法. 使用偏差,精度和准确度指标 (RMSE,MAE,P30).
主要成果:
- 总共有412名受试者被录取,其中55%患有CKD.
- 基于肌素的EGFR方程显示了最高的偏差,显著高估了GFR.
- 基于赛斯塔丁C的方程显示了边际改善,但没有达到所需的准确度值 (P30 ≥80%).
结论:
- 在印度人中,种族中立的CKD-EPICr(2021)并没有超过较旧的CKD-EPICr(2009)等式.
- 对于开发和验证专门针对印度人口的新型eGFR方程的需求至关重要.
- 标准化mGFR测量对于个性化患者护理至关重要.
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