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一种源自Kinect的综合指数,用于评估帕金森病患者姿势异常的严重程度。

A summary index derived from Kinect to evaluate postural abnormalities severity in Parkinson's Disease patients.

作者信息

Hong Ronghua, Zhang Tianyu, Zhang Zhuoyu, Wu Zhuang, Lin Ao, Su Xiaoyun, Jin Yue, Gao Yichen, Peng Kangwen, Li Lixi, Pan Lizhen, Zhi Hongping, Guan Qiang, Jin Lingjing

机构信息

Neurotoxin Research Center, Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Neurological Department of Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.

IFLYTEK Suzhou Research Institute, Suzhou, China.

出版信息

NPJ Parkinsons Dis. 2022 Aug 2;8(1):96. doi: 10.1038/s41531-022-00368-x.

Abstract

Postural abnormalities are common disabling motor complications affecting patients with Parkinson's disease (PD). We proposed a summary index for postural abnormalities (IPA) based on Kinect depth camera and explored the clinical value of this indicator. Seventy individuals with PD and thirty age-matched healthy controls (HCs) were enrolled. All participants were tested using a Kinect-based system with IPA automatically obtained by algorithms. Significant correlations were detected between IPA and the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score (r = 0.369, p = 0.002), MDS-UPDRS-III total score (r = 0.431, p < 0.001), MDS-UPDRS-III 3.13 score (r = 0.573, p < 0.001), MDS-UPDRS-III-bradykinesia score (r = 0.311, p = 0.010), the 39-item Parkinson's Disease Questionnaire (PDQ-39) (r = 0.272, p = 0.0027) and the Berg Balance Scale (BBS) score (r = -0.350, p = 0.006). The optimal cut-off value of IPA for distinguishing PD from HCs was 12.96 with a sensitivity of 97.14%, specificity of 100.00%, area under the curve (AUC) of 0.999 (0.997-1.002, p < 0.001), and adjusted AUC of 0.998 (0.993-1.000, p < 0.001). The optimal cut-off value of IPA for distinguishing between PD with and without postural abnormalities was 20.14 with a sensitivity, specificity, AUC and adjusted AUC of 77.78%, 73.53%, 0.817 (0.720-0.914, p < 0.001), and 0.783 (0.631-0.900, p < 0.001), respectively. IPA was significantly correlated to the clinical manifestations of PD patients, and could reflect the global severity of postural abnormalities in PD with important value in distinguishing PD from HCs and distinguishing PD with postural abnormalities from those without.

摘要

姿势异常是影响帕金森病(PD)患者的常见致残性运动并发症。我们基于Kinect深度相机提出了一种姿势异常综合指数(IPA),并探讨了该指标的临床价值。纳入了70例PD患者和30例年龄匹配的健康对照者(HCs)。所有参与者均使用基于Kinect的系统进行测试,通过算法自动获得IPA。检测到IPA与运动障碍协会赞助的统一帕金森病评定量表(MDS-UPDRS)总分(r = 0.369,p = 0.002)、MDS-UPDRS-III总分(r = 0.431,p < 0.001)、MDS-UPDRS-III 3.13评分(r = 0.573,p < 0.001)、MDS-UPDRS-III - 运动迟缓评分(r = 0.311,p = 0.010)、39项帕金森病问卷(PDQ-39)(r = 0.272,p = 0.0027)以及伯格平衡量表(BBS)评分(r = -0.350,p = 0.006)之间存在显著相关性。区分PD患者与HCs的IPA最佳截断值为12.96,灵敏度为97.14%,特异度为100.00%,曲线下面积(AUC)为0.999(0.997 - 1.002,p < 0.001),调整后AUC为0.998(0.993 - 1.000,p < 0.001)。区分有姿势异常和无姿势异常的PD患者的IPA最佳截断值为20.14,灵敏度、特异度、AUC和调整后AUC分别为77.78%、73.53%、0.817(0.720 - 0.914,p < 0.001)和0.783(0.631 - 0.900,p < 0.001)。IPA与PD患者的临床表现显著相关,能够反映PD患者姿势异常的整体严重程度,在区分PD患者与HCs以及区分有姿势异常和无姿势异常的PD患者方面具有重要价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e50/9345864/cf74ed161034/41531_2022_368_Fig1_HTML.jpg

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