临床神经病学杂志2026，Vol.39Issue(3)：203-209,7.
帕金森病合并睡眠障碍的影响因素与风险预测模型构建
Influencing factors and risk prediction model construction for Parkinson's disease complicated with sleep disorders
摘要
Abstract
Objective To analyze the influencing factors of Parkinson's disease(PD)complicated with sleep disorders and to establish a risk prediction model.Methods Clinical data of 162 patients with PD admitted to our hospital from June 2021 to June 2023 were retrospectively collected and randomly divided into a development cohort(108 cases)and a validation cohort(54 cases)at a ratio of 2∶1.All patients were followed up for 6 months,and the development cohort was grouped according to the occurrence of sleep disorders,with general data compared between groups.Binary multivariate Logistic regression analysis was performed to identify influencing factors,establish regression equations,and construct a Nomogram prediction model.The efficacy and calibration of the model were verified using ROC and calibration curves.Results The incidence rates of sleep disorders in the development set and validation set were 52.78%and 53.70%,respectively.The Logistic regression model showed that disease duration,Hoehn-Yahr grade,TNF-α level,plasma homocysteine(Hcy)level,and daily levodopa equivalent dose(LEDD)were risk factors for PD complicated with sleep disorders(all P<0.05).The ROC curve showed that the Nomogram model predicted PD complicated with sleep disorders in the development set with an area under the curve(AUC)of 0.923,a sensitivity of 87.50%,and a specificity of 91.94%,while the AUC for the validation set was 0.907,with a sensitivity of 93.06%and a specificity of 87.33%.The Hosmer-Lemeshow test indicated no statistically significant differences between the probabilities of sleep disorders predicted by the Nomogram model and the actual probabilities in both the development set(χ2=0.587,P=0.198)and the validation set(χ2=0.833,P=0.124).Conclusions Disease duration,Hoehn-Yahr grade,plasma TNF-α level,plasma Hcy level,and LEDD are risk factors for PD complicated with sleep disorders.The risk prediction Nomogram model constructed based on these risk factors demonstrates good clinical performance in predicting the occurrence of sleep disorders in PD patients.关键词
帕金森病/睡眠障碍/Nomograms/危险因素Key words
Parkinson's disease/sleep disorders/Nomograms/risk factors分类
医药卫生引用本文复制引用
邓蓉,王翔..帕金森病合并睡眠障碍的影响因素与风险预测模型构建[J].临床神经病学杂志,2026,39(3):203-209,7.基金项目
荆门市科学技术研究与开发计划项目(2023YDKY158) （2023YDKY158）
