Chen Kui, Du Kangshuai, Zhao Yichen, Gu Yongzhe, Zhao Yanxin
Department of Neurology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Front Aging Neurosci. 2021 Dec 20;13:762759. doi: 10.3389/fnagi.2021.762759. eCollection 2021.
Orthostatic hypotension (OH) in Parkinson's disease (PD) can lead to falls, impair quality of life, and increase mortality. A trajectory analysis of OH could be useful to predict and prevent the hypotension incidence early. The longitudinal data of 660 patients with PD with disease duration up to 12 years were extracted from an integrated PD database. We used latent class mixed modeling (LCMM) to identify patient subgroups, demonstrating trajectories of changes in orthostatic blood pressure (BP) over time. The optimal number of subgroups was selected by several criteria including the Bayesian Information Criterion. Baseline information comparison between groups and backward stepwise logistic regression were conducted to define the distinguishing characteristics of these subgroups and to investigate the predictors for BP trajectory. We identified three trajectories for each orthostatic change of systolic blood pressure (ΔSBP), namely, Class 1 (i.e., the increasing class) consisted of 18 participants with low ΔSBP that increased continuously during the follow-up; Class 2 (i.e., the low-stable class) consisted of 610 participants with low ΔSBP that remained low throughout the follow-up; and Class 3 (i.e., the high-stable class) consisted of 32 participants with high ΔSBP at baseline that was relatively stable throughout the follow-up. Several parameters differed among subgroups, but only male sex [odds ratio (OR) = 4.687, 95% confidence interval (CI) = 1.024-21.459], lower supine diastolic blood pressure (DBP) (OR = 0.934, 95% CI = 0.876-0.996), and lower level of total protein at baseline (OR = 0.812, 95% CI = 0.700-0.941) were significant predictors of an increasing ΔSBP trajectory. This study provides new information on the longitudinal development of ΔSBP in patients with PD with distinct trajectories of rapidly increasing, low-stable, and high-stable class. The parameters such as male sex, lower supine DBP, and lower total proteins help to identify the rapidly increasing class.
帕金森病（PD）中的直立性低血压（OH）可导致跌倒、损害生活质量并增加死亡率。对OH进行轨迹分析可能有助于早期预测和预防低血压的发生。从一个综合的PD数据库中提取了660例病程长达12年的PD患者的纵向数据。我们使用潜在类别混合模型（LCMM）来识别患者亚组，展示直立性血压（BP）随时间的变化轨迹。通过包括贝叶斯信息准则在内的多个标准选择亚组的最佳数量。进行组间基线信息比较和向后逐步逻辑回归，以定义这些亚组的区别特征并研究BP轨迹的预测因素。我们为收缩压（ΔSBP）的每次直立性变化确定了三条轨迹，即，第1类（即增加类）由18名参与者组成，其ΔSBP较低，在随访期间持续增加；第2类（即低稳定类）由610名参与者组成，其ΔSBP较低，在整个随访期间保持较低水平；第3类（即高稳定类）由32名参与者组成，其基线时ΔSBP较高，在整个随访期间相对稳定。几个参数在亚组之间存在差异，但只有男性[比值比（OR）=4.687，95%置信区间（CI）=1.024 - 21.459]、较低的仰卧位舒张压（DBP）（OR = 0.934，95% CI = 0.876 - 0.996）和基线时较低的总蛋白水平（OR = 0.812，95% CI = 0.700 - 0.941）是ΔSBP轨迹增加的显著预测因素。本研究提供了关于PD患者中具有快速增加、低稳定和高稳定类不同轨迹的ΔSBP纵向发展的新信息。诸如男性、较低的仰卧位DBP和较低的总蛋白等参数有助于识别快速增加类。
