University of Pittsburgh School of Medicine, Department of Neurology, Pittsburgh, PA 15213, USA.
Mov Disord. 2012 Jul;27(8):988-95. doi: 10.1002/mds.24979. Epub 2012 Jun 14.
Changes in cardiovascular physiology in Parkinson's disease (PD) are common and may occur prior to diagnostic parkinsonian motor signs. We investigated associations of electrocardiographic (ECG) abnormalities, orthostasis, heart rate variability, and carotid stenosis with the risk of PD diagnosis in the Cardiovascular Health Study, a community-based cohort of older adults. ECG abnormality, orthostasis (symptomatic or asymptomatic), heart rate variability (24-hour Holter monitoring), and any carotid stenosis (≥1%) by ultrasound were modeled as primary predictors of incident PD diagnosis using multivariable logistic regression. Incident PD cases were identified by at least 1 of the following: self-report, antiparkinsonian medication use, and ICD-9. If unadjusted models were significant, they were adjusted or stratified by age, sex, and smoking status, and those in which predictors were still significant (P ≤ .05) were also adjusted for race, diabetes, total cholesterol, low-density lipoprotein, blood pressure, body mass index, physical activity, education level, stroke, and C-reactive protein. Of 5888 participants, 154 incident PD cases were identified over 14 years of follow-up. After adjusting models with all covariates, those with any ECG abnormality (odds ratio [OR], 1.45; 95% CI, 1.02-2.07; P = .04) or any carotid stenosis (OR, 2.40; 95% CI, 1.40-4.09; P = .001) at baseline had a higher risk of incident PD diagnosis. Orthostasis and heart rate variability were not significant predictors. This exploratory study suggests that carotid stenosis and ECG abnormalities occur prior to motor signs in PD, thus serving as potential premotor features or risk factors for PD diagnosis. Replication is needed in a population with more thorough ascertainment of PD onset.
帕金森病(PD)患者的心血管生理学变化较为常见,可能早于诊断性帕金森运动体征出现。我们研究了心电图(ECG)异常、直立性低血压、心率变异性和颈动脉狭窄与心血管健康研究中帕金森病诊断风险的相关性,该研究为基于社区的老年人群队列研究。使用多变量逻辑回归模型,将 ECG 异常、直立性低血压(有症状或无症状)、心率变异性(24 小时 Holter 监测)和任何颈动脉狭窄(≥1%)作为主要预测指标来预测 PD 的诊断。通过以下至少一种方法确定 PD 发病病例:自我报告、抗帕金森药物使用和 ICD-9。如果未经调整的模型具有统计学意义,则根据年龄、性别和吸烟状况进行调整或分层,如果预测指标仍然具有统计学意义(P ≤.05),则还根据种族、糖尿病、总胆固醇、低密度脂蛋白、血压、体重指数、身体活动、教育程度、中风和 C 反应蛋白进行调整。在 5888 名参与者中,154 名参与者在 14 年的随访中确诊为 PD。在调整了所有协变量的模型后,基线时存在任何 ECG 异常(比值比[OR],1.45;95%置信区间[CI],1.02-2.07;P =.04)或任何颈动脉狭窄(OR,2.40;95%CI,1.40-4.09;P =.001)的患者发生 PD 的风险更高。直立性低血压和心率变异性不是显著的预测指标。这项探索性研究表明,颈动脉狭窄和 ECG 异常早于 PD 运动体征出现,因此可作为 PD 诊断的潜在前驱特征或风险因素。需要在更全面确定 PD 发病的人群中进行复制研究。