目的:探究国际IgAN预测工具在IgAN预后评估中的可行性。方法:以多因素Logistic回归分析影响患者预后的危险因素,将分析后的危险因素作为预测因素构建预测模型,检验构建模型的总体性能,并选取308例IgAN患者作为验证对象进行模型效能验证。回顾性分析内蒙古地区308例IgAN患者临床预后情况,根据患者的预后情况分为生存组、死亡组,分别应用国际IgAN预测工具与牛津病理分型模型评估预后的预测价值,对比国际IgAN预测工具与牛津病理分型模型评估检查情况及ROC曲线准确率AUC、特异度以及敏感度。结果:纳入的308例IgAN患者的预后不良比例为42.60 %;国际IgA预后预测模型的检出准确率明显高于牛津分型(χ2=18.422,P=0.001);对比牛津分型,国际IgA预后预测模型的AUC、敏感度、特异度均明显升高且差异具有统计学意义(P＜0.05)。结论:IgAN患者存在年龄、高血压疾病史、SBP、Pro、Scr、NLR、eGFR等多项影响预后因素,应为存在以上危险因素的患者制定针对性护理预防方案,基于IgAN患者预后影响因素建立的预测模型具有较高的临床敏感度、特异度,并且整体预测效能优于牛津分型,值得临床推广应用。
Objective: To explore the feasibility of international IgAN prediction tools in the prognosis evaluation of IgAN. Methods: Multivariate logistic regression analysis was used to analyze the risk factors affecting the prognosis of patients. The risk factors after analysis were used as predictors to construct a prediction model, and the overall performance of the model was tested.The clinical prognosis of 308 patients with IgAN in Inner Mongolia was retrospectively analyzed. According to the prognosis of patients, they were divided into survival group and death group. The predictive value of the prognosis was evaluated by the international IgAN prediction tool and the Oxford pathological classification model. The international IgAN prediction tool and the Oxford pathological classification model were used to evaluate the examination and ROC curve accuracy AUC, specificity and sensitivity. Results: The proportion of poor prognosis in 308 patients with IgAN was 42.60 %. The detection accuracy of the international IgA prognostic prediction model was significantly higher than that of the Oxford classification (χ2=18.422, P=0.001). Compared with the Oxford classification, the AUC, sensitivity and specificity of the international IgA prognostic prediction model were significantly increased and the difference was statistically significant (P＜0.05). Conclusion: IgAN patients are affected by age, history of hypertension, SBP, Pro, Scr, NLR, eGFR and other prognostic factors. Targeted nursing prevention programs should be formulated for patients with the above risk factors. The prediction model based on the prognostic factors of IgAN patients has high clinical sensitivity and specificity, and the overall prediction efficiency is better than Oxford classification, which is worthy of clinical application.
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