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_s = 0.369, p = 0.002), MDS-UPDRS-III total score (r_s = 0.431, p < 0.001), MDS-UPDRS-III 3.13 score (r_s = 0.573, p < 0.001), MDS-UPDRS-III-bradykinesia score (r_s = 0.311, p = 0.010), the 39-item Parkinson’s Disease Questionnaire (PDQ-39) (r_s = 0.272, p = 0.0027) and the Berg Balance Scale (BBS) score (r_s = −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.

姿势异常是影响帕金森病 (PD) 患者的常见运动并发症。我们提出了基于 Kinect 深度摄像头的姿势异常 (IPA) 汇总指标，并探讨了该指标的临床价值。招募了 70 名 PD 患者和 30 名年龄匹配的健康对照 (HC)。所有参与者都使用基于 Kinect 的系统进行测试，IPA 通过算法自动获得。IPA 与运动障碍协会赞助的统一帕金森病评定量表修订版 (MDS-UPDRS) 总分 ( r _s  = 0.369, p  = 0.002)、MDS-UPDRS-III 总分 ( r _s  = 0.431, p < 0.001), MDS-UPDRS-III 3.13 评分 ( r _s  = 0.573, p  < 0.001), MDS-UPDRS-III-运动迟缓评分 ( r _s  = 0.311, p  = 0.010), 39 项帕金森病问卷 (PDQ -39) ( r _s  = 0.272, p  = 0.0027) 和伯格平衡量表 (BBS) 得分 ( r _s  = -0.350, p  = 0.006)。IPA 区分 PD 和 HC 的最佳临界值为 12.96，灵敏度为 97.14%，特异性为 100.00%，曲线下面积 (AUC) 为 0.999 (0.997–1.002, p  < 0.001)，调整后的 AUC 为0.998 (0.993–1.000, p < 0.001)。IPA 区分有无姿势异常的 PD 的最佳临界值为 20.14，其敏感性、特异性、AUC 和调整后的 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），分别。IPA与PD患者的临床表现显着相关，可反映PD患者体位异常的总体严重程度，对区分PD与HCs、区分PD与体位异常具有重要价值。