Department of Nephrology, The First Hospital of Jilin University, Changchun, 130021, Jilin, China.
Sci Rep. 2022 May 18;12(1):8296. doi: 10.1038/s41598-022-11964-5.
Renal biopsy is the gold standard for Immunoglobulin A nephropathy (IgAN) but poses several problems. Thus, we aimed to establish a noninvasive model for predicting the risk probability of IgAN by analyzing routine and serological parameters. A total of 519 biopsy-diagnosed IgAN and 211 non-IgAN patients were recruited retrospectively. Artificial neural networks and logistic modeling were used. The receiver operating characteristic (ROC) curve and performance characteristics were determined to compare the diagnostic value between the two models. The training and validation sets did not differ significantly in terms of any variables. There were 19 significantly different parameters between the IgAN and non-IgAN groups. After multivariable logistic regression analysis, age, serum albumin, serum IgA, serum immunoglobulin G, estimated glomerular filtration rate, serum IgA/C3 ratio, and hematuria were found to be independently associated with the presence of IgAN. A backpropagation network model based on the above parameters was constructed and applied to the validation cohorts, revealing a sensitivity of 82.68% and a specificity of 84.78%. The area under the ROC curve for this model was higher than that for logistic regression model (0.881 vs. 0.839). The artificial neural network model based on routine markers can be a valuable noninvasive tool for predicting IgAN in screening practice.
肾活检是 IgA 肾病（IgAN）的金标准，但存在一些问题。因此，我们旨在通过分析常规和血清学参数，建立一种非侵入性模型来预测 IgAN 的风险概率。共回顾性纳入 519 例经肾活检诊断的 IgAN 和 211 例非 IgAN 患者。采用人工神经网络和逻辑建模。确定接收者操作特征（ROC）曲线和性能特征，以比较两种模型的诊断价值。训练集和验证集在任何变量方面均无显著差异。IgAN 组和非 IgAN 组之间有 19 个显著不同的参数。经过多变量逻辑回归分析，发现年龄、血清白蛋白、血清 IgA、血清免疫球蛋白 G、估算肾小球滤过率、血清 IgA/C3 比值和血尿与 IgAN 的存在独立相关。根据上述参数构建了一个反向传播网络模型，并将其应用于验证队列，显示出 82.68%的敏感性和 84.78%的特异性。该模型的 ROC 曲线下面积高于逻辑回归模型（0.881 对 0.839）。基于常规标志物的人工神经网络模型可以成为筛选实践中预测 IgAN 的一种有价值的非侵入性工具。
