原发性帕金森病患者发生疼痛的影响因素及其风险预测列线图模型构建  

Influencing Factors of Pain in Patients with Primary Parkinson's Disease and Construction of Nomogram Model for Predicting Its Risk

作　　者：刘翠霞 周莉莉 朱德慧[1] LIU Cuixia;ZHOU Lili;ZHU Dehui(Department of Neurology,Huai'an Second People's Hospital,Huai'an 223000,China)

机构地区：[1]江苏省淮安市第二人民医院神经内科,223000

出　　处：《实用心脑肺血管病杂志》2024年第10期77-81,共5页Practical Journal of Cardiac Cerebral Pneumal and Vascular Disease

基　　金：江苏省卫生健康委2019年度医学科研立项项目(H2019030)。

摘　　要：目的探讨原发性帕金森病患者发生疼痛的影响因素,并构建其风险预测列线图模型。方法选取2021年1月—2023年4月淮安市第二人民医院收治的原发性帕金森病患者208例为研究对象。收集患者临床资料,根据疼痛发生情况将患者分为发生组与未发生组。采用多因素Logistic回归分析探讨原发性帕金森病患者发生疼痛的影响因素;采用R 3.6.3软件及rms程序包建立原发性帕金森病患者发生疼痛的风险预测列线图模型,并采用Hosmer-Lemeshow拟合优度检验、ROC曲线、临床决策曲线评价该列线图模型的准确性、区分度、临床有效性。结果208例原发性帕金森病患者中87例(41.83%)发生疼痛。两组性别、Hoehn-Yahr分期、左旋多巴等效剂量、帕金森病统一评分量表(UPDRS)Ⅰ评分、UPDRSⅢ评分、疲劳量表-14(FS-14)评分及焦虑、抑郁、嗅觉障碍、黑质回声增强、中缝核回声异常、睡眠障碍发生率比较,差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,性别[OR=2.237,95%CI(1.196~4.185)]、Hoehn-Yahr分期[OR=3.401,95%CI(1.623~7.128)]、抑郁[OR=2.756,95%CI(1.487~5.108)]、睡眠障碍[OR=2.264,95%CI(1.128~4.546)]是原发性帕金森病患者发生疼痛的独立影响因素(P<0.05)。以性别、Hoehn-Yahr分期、抑郁、睡眠障碍构建原发性帕金森病患者发生疼痛的风险预测列线图模型。Hosmer-Lemeshow拟合优度检验结果显示,该列线图模型的拟合程度较好(P>0.05)。ROC曲线分析结果显示,该列线图模型预测原发性帕金森病患者发生疼痛的AUC为0.775[95%CI(0.711~0.838)]。决策曲线分析结果显示,当阈值概率为0.13~0.85时,该列线图模型的净获益率>0。结论性别、Hoehn-Yahr分期、抑郁、睡眠障碍是原发性帕金森病患者发生疼痛的独立影响因素,基于上述因素构建的原发性帕金森病患者发生疼痛的风险预测列线图模型具有较高的准确性及一定区分度,能够为临Objective To explore the influencing factors of pain in patients with primary Parkinson's disease,and construct the nomogram model for predicting its risk.Methods A total of 208 patients with primary Parkinson's disease admitted to Huai'an Second People's Hospital from January 2021 to April 2023 were selected as the research subjects.The clinical data of the patients were collected,the patients were divided into occurrence group and non-occurrence group according to the occurrence of pain.Multivariate Logistic regression analysis was used to explore the influencing factors of pain in patients with primary Parkinson's disease.The nomogram model for predicting the risk of pain in patients with primary Parkinson's disease was constructed by using the R 3.6.3 software and rms package.Hosmer-Lemeshow goodness of fit test,ROC curve and decision curve were used to evaluate the accuracy,discrimination and clinical effectiveness.Results Among 208 patients with primary Parkinson's disease,87 cases(41.83%)experienced pain.There were significant differences in gender,Hoehn-Yahr stage,levodopa equivalent dose,Unified Parkinson's Disease Rating Scale(UPDRS)Ⅰscore,UPDRSⅢscore,Fatigue Scale-14(FS-14)score,and incidence of anxiety,depression,olfactory disorder,enhanced substantia nigra echo,abnormal raphe nucleus echo and sleep disorder between the two groups(P<0.05).Multivariate Logistic regression analysis showed that gender[OR=2.237,95%CI(1.196-4.185)],Hoehn-Yahr stage[OR=3.401,95%CI(1.623-7.128)],depression[OR=2.756,95%CI(1.487-5.108)]and sleep disorder[OR=2.264,95%CI(1.128-4.546)]were the independent influencing factors for pain in patients with primary Parkinson's disease(P<0.05).The nomogram model for predicting the risk of pain in patients with primary Parkinson's disease was constructed based on gender,Hoehn-Yahr stage,depression and sleep disorder.The results of Hosmer-Lemeshow goodness of fit test showed that the nomogram model fitted well(P>0.05).The results of ROC curve analysis showed that the AUC of the nomogra

关 键 词：帕金森病 疼痛 影响因素分析 列线图 

分 类 号：R742.5[医药卫生—神经病学与精神病学] R441.1[医药卫生—临床医学]