2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Oculometric measures as a tool for assessment of clinical symptoms and severity of Parkinson’s disease

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Abnormalities of oculometric measures (OM) are widely described in people with Parkinson's disease (PD). However, knowledge of correlations between abnormal OM, disease severity and clinical assessment in PD patients is still lacking. To evaluate these correlations, PD patients (215 patients, mean age 69 ± 9.1 years, 79 females) with severe (H&Y > 3) and mild to moderate (H&Y ≤ 2) disease, and 215 age-matched healthy subjects were enrolled. All patients were evaluated using MDS-UPDRS and an oculometric test using computer vision and deep learning algorithms. Comparisons of OM between groups and correlations between OM and MDS-UPDRS scores were calculated. Saccadic latency (ms) was prolonged in patients with severe compared with mild to moderate disease (pro-saccades: 267 ± 69 vs. 238 ± 53, p = 0.0011; anti-saccades: 386 ± 119 vs. 352 ± 106, p = 0.0393) and in patients with mild to moderate disease versus healthy subjects (pro-saccades: 238 ± 53 vs. 220 ± 45, p = 0.0003; anti-saccades: 352 ± 106 vs. 289 ± 71, p < 0.0001). Error rate (%) was higher among patients with severe (64.06 ± 23.08) versus mild to moderate disease (49.84 ± 24.81, p = 0.0001), and versus healthy subjects (49.84 ± 24.81 vs. 28.31 ± 21.72, p = 0.00001). Response accuracy (%) was lower for patients with severe (75.66 ± 13.11) versus mild to moderate disease (79.66 ± 13.56, p = 0.0462), and versus healthy subjects (79.66 ± 13.56 vs. 90.27 ± 8.79, p < 0.0001). Pro- and anti-saccadic latency, error rate and accuracy were correlated with MDS-UPDRS scores (r = 0.32, 0.28, 0.36 and -0.30, respectively, p < 0.0001) and similar correlations were found with its axial subscore (R = 0.38, 0.29, 0.44, and -0.30, respectively, p < 0.0001). Several OM were different in patients under levodopa treatment. OM worsened as PD severity increases, and were correlated with MDS-UPDRS scores. Using OM can be implemented for PD patients’ assessment as a tool to follow disease progression.

          Related collections

          Most cited references39

          • Record: found
          • Abstract: found
          • Article: not found

          Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results.

          We present a clinimetric assessment of the Movement Disorder Society (MDS)-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The MDS-UDPRS Task Force revised and expanded the UPDRS using recommendations from a published critique. The MDS-UPDRS has four parts, namely, I: Non-motor Experiences of Daily Living; II: Motor Experiences of Daily Living; III: Motor Examination; IV: Motor Complications. Twenty questions are completed by the patient/caregiver. Item-specific instructions and an appendix of complementary additional scales are provided. Movement disorder specialists and study coordinators administered the UPDRS (55 items) and MDS-UPDRS (65 items) to 877 English speaking (78% non-Latino Caucasian) patients with Parkinson's disease from 39 sites. We compared the two scales using correlative techniques and factor analysis. The MDS-UPDRS showed high internal consistency (Cronbach's alpha = 0.79-0.93 across parts) and correlated with the original UPDRS (rho = 0.96). MDS-UPDRS across-part correlations ranged from 0.22 to 0.66. Reliable factor structures for each part were obtained (comparative fit index > 0.90 for each part), which support the use of sum scores for each part in preference to a total score of all parts. The combined clinimetric results of this study support the validity of the MDS-UPDRS for rating PD.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Parkinsonism: onset, progression, and mortality

            M Hoehn, M Yahr (1967)
            Neurology, 17(5), 427-427
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The basal ganglia and the cerebellum: nodes in an integrated network

              The basal ganglia and the cerebellum are considered to be distinct subcortical systems that perform unique functional operations. The outputs of the basal ganglia and the cerebellum influence many of the same cortical areas but do so by projecting to distinct thalamic nuclei. As a consequence, the two subcortical systems were thought to be independent and to communicate only at the level of the cerebral cortex. Here, we review recent data showing that the basal ganglia and the cerebellum are interconnected at the subcortical level. The subthalamic nucleus in the basal ganglia is the source of a dense disynaptic projection to the cerebellar cortex. Similarly, the dentate nucleus in the cerebellum is the source of a dense disynaptic projection to the striatum. These observations lead to a new functional perspective that the basal ganglia, the cerebellum and the cerebral cortex form an integrated network. This network is topographically organized so that the motor, cognitive and affective territories of each node in the network are interconnected. This perspective explains how synaptic modifications or abnormal activity at one node can have network-wide effects. A future challenge is to define how the unique learning mechanisms at each network node interact to improve performance.
                Bookmark

                Author and article information

                Contributors
                eitan@neuralight.ai
                Journal
                J Neural Transm (Vienna)
                J Neural Transm (Vienna)
                Journal of Neural Transmission
                Springer Vienna (Vienna )
                0300-9564
                1435-1463
                9 August 2023
                9 August 2023
                2023
                : 130
                : 10
                : 1241-1248
                Affiliations
                [1 ]GRID grid.413156.4, ISNI 0000 0004 0575 344X, Department of Neurology, Rabin Medical Center, , Movement Disorders Clinic, Beilinson Hospital, ; 4941492 Petach Tikva, Israel
                [2 ]GRID grid.12136.37, ISNI 0000 0004 1937 0546, Affiliated to Sackler Faculty of Medicine, , Tel Aviv University, ; Tel Aviv, Israel
                [3 ]NeuraLight LTD, 6713818 Tel Aviv, Israel
                Author information
                http://orcid.org/0000-0001-7102-1261
                Article
                2681
                10.1007/s00702-023-02681-y
                10480268
                37553460
                654c2ab0-bdcc-451d-98a1-0e3b6a9f6c1b
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 May 2023
                : 2 August 2023
                Categories
                Neurology and Preclinical Neurological Studies - Original Article
                Custom metadata
                © Springer-Verlag GmbH Austria, part of Springer Nature 2023

                digital clinical assessment,eye movement,saccades,machine learning,artificial intelligence

                Comments

                Comment on this article