左旋多巴
帕金森病
黑质
运动障碍
逻辑回归
接收机工作特性
回声
曲线下面积
心理学
内科学
医学
疾病
超声波
放射科
作者
Jiahui Yan,Kai Li,Yi-Lun Ge,Wen Li,Pu-Zhi Wang,Jing Hong,Jin‐Ru Zhang,Jing Chen,Fen Wang,Yaping Yang,Yingchun Zhang,Dan Li,Cheng‐Jie Mao,Chunfeng Liu
标识
DOI:10.1016/j.ultrasmedbio.2022.10.019
摘要
Levodopa-induced dyskinesia (LID) is a common motor complication in Parkinson disease (PD). Abnormal substantia nigra hyperechogenicity (SN+), detected by transcranial sonography (TCS), plays an important role in the differential diagnosis of PD. The purpose of this study was to investigate the predictive performance of quantitative SN+ evaluations for LID. Five hundred sixty-two individuals were included in our analysis, and 198 individuals were followed up. These individuals were divided into two groups at baseline: the PD with LID (PD+LID) group and the PD without LID (PD-LID) group. The association between total hyperechogenic area of the SN on both sides (SNT) and LID was analyzed by binary logistic analysis. A binary logistic regression model including SNT was applied to establish a model for discriminating LID. At baseline, 105 (18.7%) individuals were diagnosed with LID. The PD+LID group had a longer disease duration, shorter education duration, higher levodopa equivalent doses, greater disease severity and larger SNT. A model combining clinical features and SNT was further established with better efficiency (area under the receiver operating characteristic curve = 0.839). One hundred ninety-eight individuals were followed up; individuals with a larger SNT and a higher predicted probability were more likely to develop LID in our follow-up. Our study determined that quantitative TCS evaluation of SN echogenicity is useful in predicting LID in PD.
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