Comparison of laboratory and daily-life gait speed assessment during on and off states in parkinson’s disease

Accurate assessment of Parkinson’s disease (PD) ON and OFF states in the usual environment is essential for tailoring optimal treatments. Wearables facilitate measurements of gait in novel and unsupervised environments; however, differences between unsupervised and in-laboratory measures have been reported in PD. We aimed to investigate whether unsupervised gait speed discriminates medication states and which supervised tests most accurately represent home perfor-mance. In-lab gait speeds from different gait tasks were compared to home speeds of 27 PD patients at ON and OFF states using inertial sensors. Daily gait speed distribution was expressed in percentiles and walking bout (WB) length. Gait speeds differentiated ON and OFF states in the lab and the home. When comparing lab with home performance, ON assessments in the lab showed moderate-to-high correlations with faster gait speeds in unsupervised environment (r = 0.69; p < 0.001), associated with long WB. OFF gait assessments in the lab showed moderate correlation values with slow gait speeds during OFF state at home (r = 0.56; p = 0.004), associated with short WB. In-lab and daily assessments of gait speed with wearables capture additional integrative aspects of PD, reflecting different aspects of mobility. Unsupervised assessment using wearables adds complementary information to the clinical assessment of motor fluctuations in PD.This research was funded by Keep Control from the EU’s Horizon 2020 (H2020) research and innovation program under the Marie Sklodowska-Curie (MSCA-ITN-ETN), grant number 721577. No other financial support and funding for the preceding twelve months are applied

Sleep disturbances in Parkinson's disease are associated with central parkinsonian pain

Introduction: Sleep disturbances and pain are common non-motor symptoms in Parkinson's disease (PD). This study aimed to explore the association between these two symptoms in a cohort of patients with PD. Materials and methods: The Parkinson's Disease Sleep Scale (PDSS-2) was used to identify sleep disturbances in a series of 229 PD patients. The identification and characterization of pain was performed by a semi-structured interview and by the application of the Ford classification and the Brief Pain Inventory (BPI). The Unified Parkinson's Disease Rating Scale-III, Hoehn & Yahr (H&Y), and Schwab and England Independence Scale were used to assess motor symptoms and functional independence in off and on conditions. The Hospital Anxiety and Depression Scale (HADS) and SF-36 were applied to screen for anxiety and depression and to evaluate the quality of life. Non-parametric tests were used for group comparisons and logistic regressions were applied to explore predictors of sleep disturbances. Results: Seventy-five (33%) patients had clinically relevant sleep disturbances (PDSS-2≥18) and 162 patients (71%) reported pain. Of those with pain, 38 (24%) had central parkinsonian pain. PD patients with sleep disturbances experienced more pain and had more severe motor symptoms, lower functional independence, more anxiety and depression symptoms, and worst quality of life. Among patients with pain, central parkinsonian pain was the subtype of pain with the highest odds of sleep disturbances, even when taking into account motor symptoms (H&Y off), motor fluctuations, intensity of pain (BPI), and symptoms of anxiety and depression (HADS). Conclusions: The association between pain and sleep disturbances in PD appears to be dependent on subtype of pain. The close relationship between central parkinsonian pain and sleep disturbances in PD raises the possibility of common pathophysiological mechanisms. A better understanding of the relationship between sleep disturbances and central parkinsonian pain may contribute to the development of new care strategies in PD patients.info:eu-repo/semantics/publishedVersio