From the Department of Neurology, Neuroscience Campus Amsterdam (K.T.E.O.D., D.S., H.W.B.), Department of Clinical Neurophysiology and Magnetoencephalography Center (A.H., C.J.S.), and Department of Clinical Epidemiology and Biostatistics (J.W.R.T.). VU University Medical Center, Amsterdam; Department of Clinical Neuropsychology (J.B.D.), VU University, Amsterdam; and Department of Psychology (B.A.S.), University of Amsterdam, the Netherlands.
Neurology. 2014 Jan 21;82(3):263-70. doi: 10.1212/WNL.0000000000000034. Epub 2013 Dec 18.
To assess the ability of neurophysiologic markers in conjunction with cognitive assessment to improve prediction of progression to dementia in Parkinson disease (PD).
Baseline cognitive assessments and magnetoencephalographic recordings from 63 prospectively included PD patients without dementia were analyzed in relation to PD-related dementia (PDD) conversion over a 7-year period. We computed Cox proportional hazard models to assess the risk of converting to dementia conveyed by cognitive and neurophysiologic markers in individual as well as combined risk factor analyses.
Nineteen patients (30.2%) developed dementia. Baseline cognitive performance and neurophysiologic markers each individually predicted conversion to PDD. Of the cognitive test battery, performance on a posterior (pattern recognition memory score < median; hazard ratio (HR) 6.80; p = 0.001) and a fronto-executive (spatial span score < median; HR 4.41; p = 0.006) task most strongly predicted dementia conversion. Of the neurophysiologic markers, beta power < median was the strongest PDD predictor (HR 5.21; p = 0.004), followed by peak frequency < median (HR 3.97; p = 0.016) and theta power > median (HR 2.82; p = 0.037). In combination, baseline cognitive performance and neurophysiologic measures had even stronger predictive value, with the combination of impaired fronto-executive task performance and low beta power being associated with the highest dementia risk (both risk factors vs none: HR 27.3; p < 0.001).
Combining neurophysiologic markers with cognitive assessment can substantially improve dementia risk profiling in PD, providing potential benefits for clinical care as well as for the future development of therapeutic strategies.
评估神经生理标志物与认知评估相结合，以提高对帕金森病（PD）向痴呆进展的预测能力。
对 63 名无痴呆的前瞻性 PD 患者的基线认知评估和脑磁图记录进行分析，以评估 7 年内与 PD 相关的痴呆（PDD）转化情况。我们计算了 Cox 比例风险模型，以评估认知和神经生理标志物在个体和联合危险因素分析中对痴呆转化的风险。
19 名患者（30.2%）发生痴呆。基线认知表现和神经生理标志物均单独预测向 PDD 的转化。在认知测试组合中，后项（模式识别记忆评分<中位数；风险比（HR）6.80；p=0.001）和额叶执行功能（空间跨度评分<中位数；HR 4.41；p=0.006）任务的表现最能预测痴呆转化。在神经生理标志物中，β功率<中位数是最强的 PDD 预测指标（HR 5.21；p=0.004），其次是峰频率<中位数（HR 3.97；p=0.016）和θ功率>中位数（HR 2.82；p=0.037）。联合使用时，基线认知表现和神经生理测量具有更强的预测价值，额叶执行功能障碍和低β功率的联合与最高的痴呆风险相关（两个危险因素与无危险因素相比：HR 27.3；p<0.001）。
将神经生理标志物与认知评估相结合，可以大大提高 PD 痴呆风险的评估，为临床护理以及未来治疗策略的发展提供潜在的益处。
