临床荟萃 ›› 2026, Vol. 41 ›› Issue (8): 716-724.doi: 10.3969/j.issn.1004-583X.2026.08.008

• 论著 • 上一篇    下一篇

慢性肾脏病5期血液透析患者认知功能障碍的影响因素分析及风险预测模型开发

宋旭芳(), 陈飞飞, 王林风   

  1. 平顶山市第一人民医院 肾脏病风湿免疫科, 河南 平顶山 467000
  • 收稿日期:2026-06-10 出版日期:2026-08-20 发布日期:2026-08-25
  • 通讯作者: 宋旭芳 E-mail:songxuff02@163.com

Analysis of factors associated with cognitive impairment in patients with stage 5 chronic kidney disease undergoing hemodialysis and development of a risk prediction model

Song Xufang(), Chen Feifei, Wang Linfeng   

  1. Department of Nephrology, Rheumatology, and Immunology, the First People's Hospital of Pingdingshan City, Pingdingshan 467000, China
  • Received:2026-06-10 Online:2026-08-20 Published:2026-08-25
  • Contact: Song Xufang E-mail:songxuff02@163.com

摘要:

目的 探讨慢性肾脏病5期血液透析患者认知功能障碍(cognitive impairment, CI)的影响因素,并构建风险预测模型。方法 纳入2022年11月-2025年11月就诊于平顶山市第一人民医院肾脏病风湿免疫科慢性肾脏病5期血液透析患者184例,按6∶2∶2比例分为建模组(训练集110例、测试集37例),内部验证集37例。依据CI筛查结果将患者分为CI组和no-CI组,采用单因素分析、LASSO回归、多因素logistic回归分析确定CI的影响因素,构建预测模型,并结合测试集数据验证预测效能。结果 184例中发生CI例数为60例,总体发生率为32.61%。经LASSO回归筛选26个变量后,多因素logistic回归分析确定年龄(OR=1.074)、受教育年限(OR=0.808)、透析龄 (OR=1.074)、血清白蛋白(OR=0.856)及β受体阻滞剂使用(OR=4.359)为CI独立影响因素(均P<0.05)。预测模型在训练集、验证集、测试集的AUC分别为0.922(95%CI:0.866~0.978)、0.943(95%CI:0.814~0.993)和0.933(95%CI:0.800~0.989),5折交叉验证模型平均AUC为0.909(95%CI:0.828~0.989);校准曲线显示,模型预测概率与实际概率高度一致(P>0.05);临床决策曲线,当决策阈值为0.080~0.320时,使用该模型进行决策能带来额外的临床净收益。结论 慢性肾脏病5期血液透析患者CI发生率较高,年龄增长、透析龄延长、β受体阻滞剂使用是其独立危险因素,受教育年限延长和血清白蛋白水平升高为保护因素。构建的预测模型区分度、校准度和临床实用性良好,可为早期识别CI高风险患者提供工具。

关键词: 尿毒症, 血液透析, 认知功能障碍, 影响因素, 列线图

Abstract:

Objective To investigate the factors associated with cognitive impairment (CI) in patients with stage 5 chronic kidney disease undergoing hemodialysis and to develop a risk prediction model. Methods A total of 184 patients with stage 5 chronic kidney disease undergoing hemodialysis, who were treated in the Department of Nephrology, Rheumatology, and Immunology of the First People's Hospital of Pingdingshan City from November 2022 to November 2025, were enrolled and randomly assigned in a 6∶2∶2 ratio to a modeling set (training set: 110 cases; test set: 37 cases) and an internal validation set (37 cases). Based on CI screening results, patients were divided into the CI group and the no-CI group. Univariate analysis, LASSO regression, and multivariate logistic regression were used to identify factors associated with CI, and a prediction model was developed. The predictive performance of the model was further validated using the test set. Results Among the 184 patients, 60 developed CI, with an overall incidence of 32.61%. After LASSO regression screening of 26 variables, multivariate logistic regression identified age (OR=1.074), years of education (OR=0.808), duration of dialysis (OR=1.074), serum albumin (OR=0.856), and use of beta-blockers (OR=4.359) as independent factors associated with CI (all P<0.05). The area under the curve (AUC) of the prediction model was 0.922 in the training set (95%CI: 0.866-0.978), 0.943 in the validation set (95%CI: 0.814-0.993), and 0.933 in the test set (95%CI: 0.800-0.989). The mean AUC of the model was 0.909 (95%CI: 0.814-0.993) on 5-fold cross-validation. The calibration curve showed high agreement between predicted and observed probabilities (P>0.05). According to the decision curve analysis, when the threshold probability ranged from 0.080 to 0.320, using this model for decision-making provided additional clinical net benefit. Conclusion The incidence of CI is relatively high in patients with stage 5 chronic kidney disease undergoing hemodialysis. Older age, longer duration of dialysis, and beta-blocker use are independent risk factors, whereas longer years of education and higher serum albumin levels are protective factors. The developed prediction model demonstrates good discrimination, calibration, and clinical utility, and may serve as a tool for early identification of patients at high risk of CI.

Key words: uremia, hemodialysis, cognitive impairment, influencing factors, nomogram

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