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基于模糊数学的方程来评估血液透析起始时机。

An Equation Based on Fuzzy Mathematics to Assess the Timing of Haemodialysis Initiation.

机构信息

Dalian Medical University Graduate School, Dalian, China.

Department of Nephrology, The First Affiliated Hospital of Dalian Medical University, Liaoning Province Translational Medicine Research Center of Kidney Disease, Dalian, China.

出版信息

Sci Rep. 2019 Apr 10;9(1):5871. doi: 10.1038/s41598-018-37762-6.

Abstract

In order to develop an equation that integrates multiple clinical factors including signs and symptoms associated with uraemia to assess the initiation of dialysis, we conducted a retrospective cohort study including 25 haemodialysis centres in Mainland China. Patients with ESRD (n = 1281) who commenced haemodialysis from 2008 to 2011 were enrolled in the development cohort, whereas 504 patients who began haemodialysis between 2012 and 2013 were enrolled in the validation cohort comprised. An artificial neural network model was used to select variables, and a fuzzy neural network model was then constructed using factors affecting haemodialysis initiation as input variables and 3-year survival as the output variable. A logistic model was set up using the same variables. The equation's performance was compared with that of the logistic model and conventional eGFR-based assessment. The area under the bootstrap-corrected receiver-operating characteristic curve of the equation was 0.70, and that of two conventional eGFR-based assessments were 0.57 and 0.54. In conclusion, the new equation based on Fuzzy mathematics, covering laboratory and clinical variables, is more suitable for assessing the timing of dialysis initiation in a Chinese ESRD population than eGFR, and may be a helpful tool to quantitatively evaluate the initiation of haemodialysis.

摘要

为了开发一种能够综合多种临床因素(包括与尿毒症相关的症状和体征)以评估开始透析时机的方程,我们进行了一项回顾性队列研究,该研究纳入了中国大陆的 25 个血液透析中心。纳入了 2008 年至 2011 年开始血液透析的 ESRD 患者(n=1281)作为开发队列,纳入了 2012 年至 2013 年开始血液透析的 504 例患者作为验证队列。使用人工神经网络模型选择变量,然后使用影响血液透析开始的因素作为输入变量,3 年生存率作为输出变量构建模糊神经网络模型。使用相同的变量建立逻辑模型。比较了该方程与逻辑模型和常规基于 eGFR 的评估方法的性能。该方程的自举校正接受者操作特征曲线下面积为 0.70,两个基于常规 eGFR 的评估方法的面积分别为 0.57 和 0.54。总之,基于模糊数学的新方程涵盖了实验室和临床变量,比 eGFR 更适合评估中国 ESRD 人群透析开始的时机,可能是一种有助于定量评估血液透析开始时机的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42b9/6458145/3055f346f12b/41598_2018_37762_Fig1_HTML.jpg

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