认知和运动功能预测孤立性快速眼球运动睡眠期行为障碍表型转化的临床价值

Clinical value of cognitive and motor function in predicting phenoconversion in patients with isolated rapid eye movement sleep behavior disorder

目的评价认知和运动功能在预测孤立性快速眼球运动睡眠期行为障碍(iRBD)患者向神经系统退行性疾病转化中的临床价值。方法收集自2018年10月至2022年6月就诊于天津医科大学总医院及空港医院神经内科的iRBD患者47例,对受试者的基线认知和运动功能进行全面评估:使用简易智能状态量表评估受试者的总体认知功能,使用Rey-Osterrieth复杂图形测验(临摹)评估受试者的视空间功能,使用听觉词语学习测验、Rey-Osterrieth复杂图形测验(回忆)评估受试者的记忆功能,使用连线测试和Stroop色词测验评估受试者的注意力与执行功能,使用波士顿命名测试评估受试者的语言功能,使用统一帕金森病评分量表第三部分、交替拍打测试和3 m步行测试评估受试者的运动功能,定期随访并记录iRBD患者向神经系统退行性疾病的转化情况。采用受试者工作特征曲线和广义线性Logistic模型回归分析识别iRBD疾病转化者的最佳认知和运动功能测试组合;采用Cox多因素回归分析预测iRBD向神经系统退行性疾病转化的独立危险因素。结果随访时间中位数为3年,2例iRBD患者失访,实际纳入分析例数为45例。随访过程中共有21例iRBD患者向神经退行性疾病转化,其中14例为运动表型,7例为认知表型。基线Rey-Osterrieth复杂图形测验(临摹)、连线测试A、交替拍打测试是识别iRBD表型转化者的最佳组合测试(敏感度90.0%,特异度87.5%,曲线下面积0.931,P<0.001);基线连线测试A、交替拍打测试是识别iRBD运动表型转化者的最佳组合测试(敏感度100.0%,特异度66.7%,曲线下面积0.872,P<0.001);连线测试A是识别iRBD认知表型转化者的最佳测试(敏感度83.3%,特异度91.7%,曲线下面积0.917,P<0.001)。Cox多因素回归分析结果显示连线测试A用时高于截断值(63.0 s)和交替拍打测试结果低于截断值(205.5次/min)是iRBD向神经退行性疾病转化的独立危险因素(HR=5.455,95%CI 1.243~23.941,P=0.025;HR=11.279,95%CI 1.485~85.646,P=0.019)。结论Rey-Osterrieth复杂图形测验(临摹)、连线测试A和交替拍打测试是识别iRBD表型转化者的最佳组合,连线测试A和交替拍打测试是识别iRBD运动表型转化者的最佳组合,连线测试A是识别iRBD认知表型转化者的最佳测试;连线测试A和交替拍打测试表现可独立预测iRBD向神经系统退行性疾病转化的风险。

Objective To evaluate the clinical value of cognitive and motor function in predicting conversion to neurodegenerative disorders in patients with isolated rapid eye movement sleep behavior disorder(iRBD).Methods Forty-seven patients with iRBD were collected from the Department of Neurology of Tianjin Medical University General Hospital and Tianjin Medical University General Hospital Airport Site during October 2018 and June 2022.All participants received comprehensive evaluations of cognitive and motor function at baseline.The visuospatial function was evaluated by Rey-Osterrieth Complex Figure Test(ROCF)-copy,the memory function was evaluated by Auditory Verbal Learning Test and ROCF-recall,the attention-executive function was evaluated by Trail Making Test(TMT)and Stroop Color-Word Test,and the language function was evaluated by Boston Naming Test.The motor function was evaluated by Unified Parkinson′s Disease Rating Scale-Ⅲ,Alternate-tap Test(ATT),and 3-meter Timed Up and Go Test.The iRBD patients with phenoconversion were identified during follow-up.Receiver operating characteristic curve and generalized linear model Logistic regression were applied to identify the optimal combination of cognitive and motor tests in distinguishing the converters from non-converters in patients with iRBD.Multivariate Cox regression analyses were applied to evaluate the independent risk factors in predicting conversion to neurodegenerative diseases in patients with iRBD.Results The median follow-up duration was 3 years.Forty-five iRBD patients were included in the analysis eventually,as 2 dropped out at follow-up.Twenty-one iRBD patients developed neurodegenerative disorders,with 14 presenting motor phenotype and 7 cognitive phenotype.Baseline ROCF-copy,TMT-A and ATT were best combination in identifying iRBD patients with phenoconversion[sensitivity:90.0%,specificity:87.5%,area under curve(AUC):0.931,P<0.001].Baseline TMT-A and ATT were best combination in identifying iRBD patients with motor phenotype conversion(sensitivity:100.0%,specificity:66.7%,AUC:0.872,P<0.001);Baseline TMT-A performed best in identifying iRBD patients with cognitive phenotype conversion(sensitivity:83.3%,specificity:91.7%,AUC:0.917,P<0.001).Multivariate Cox regression analysis showed that individuals with poorer performance of TMT-A(cut-off value:63.0 s)and ATT(cut-off value:205.5 taps/min)than the cut-off values at baseline had higher risks for developing to neurodegenerative disorders,with HR values of 5.455(95%CI 1.243-23.941,P=0.025)and 11.279(95%CI 1.485-85.646,P=0.019),respectively.Conclusions In iRBD,ROCF-copy,TMT-A and ATT served as optimum combination in predicting phenoconversion,whereas TMT-A and ATT served as optimum combination in predicting motor phenotype,and TMT-A performed best in predicting cognitive phenotype.The performance in TMT-A and ATT in iRBD could predict the risk of developing to neurodegenerative disorders independently.