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Background: Cognitive impairment is common in Parkinson’s disease (PD), with 80% cumulatively developing dementia (PDD). Objective: We sought to identify tests that are sensitive to change over time above normal ageing so as to refine the neuropsychological tests predictive of PDD. Methods: Participants with newly diagnosed PD (n = 211) and age-matched controls (n = 99) completed a range of clinical and neuropsychological tests as part of the ICICLE-PD study at 18-month intervals over 72 months. Impairments on tests were determined using control means (

The increasing prevalence of neurodegenerative conditions such as Parkinson’s disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments “off-line”. Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up before overt, irreparable change takes place? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD. This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.

Background: Delirium is a serious acute neuropsychiatric condition associated with altered attention and arousal. Objective: To evaluate simple bedside tests for attention and arousal to detect delirium in those with and without Parkinson’s disease (PD) and dementia. Methods: Participants from two prospective delirium studies were pooled comprising 30 with PD without cognitive impairment, 24 with Lewy body cognitive impairment (PD dementia or dementia with Lewy bodies), 16 with another dementia and 179 PD and dementia-free older adults. Participants completed standardised delirium assessments including tests of attention: digit span, Memorial Delirium Assessment Scale (MDAS) attention and months of the year backwards; and arousal: Glasgow Coma Scale (GSC), Observational Scale of Level of Arousal (OSLA), Modified Richmond Agitation Scale and MDAS consciousness. Delirium was diagnosed using the DSM-5 criteria. Results: On their first admission, 21.7%participants had prevalent delirium. Arousal measures accurately detected delirium in all participants (p

BACKGROUND: Patients with REM sleep behavior disorder (RBD) have a high risk of developing PD, and thus can be used to study prodromal biomarkers. RBD has been associated with changes in gait; quantifying these changes using wearable technology is promising; however, most data are obtained in clinical settings precluding pragmatic application.OBJECTIVE: We aimed to investigate if wearable-based real-world gait monitoring can detect early gait changes and discriminate individuals with RBD from controls, and explore relationships between real-world gait and clinical characteristics.METHODS: 63 individuals with RBD (66±10 years) and 34 controls recruited in the Oxford Parkinson's Disease Centre Discovery Study were assessed. Data were collected using a wearable device positioned on the lower back for 7 days. Real-world gait was quantified in terms of its Macrostructure (volume, pattern and variability (S2)) and Microstructure (14 characteristics). The value of Macro and Micro gait in discriminating RBD from controls was explored using ANCOVA and ROC analysis, and correlation analysis was performed between gait and clinical characteristics.RESULTS: Significant differences were found in discrete Micro characteristics in RBD with reduced gait velocity, variability and rhythm (p≤0.023). These characteristics significantly discriminated RBD (AUC≥0.620), with swing time as the single strongest discriminator (AUC=0.652). Longer walking bouts discriminated best between the groups for Macro and Micro outcomes (p≤0.036).CONCLUSIONS: Our results suggest that real-world gait monitoring may have utility as "risk" clinical marker in RBD participants. Real-world gait assessment is low-cost and could serve as a pragmatic screening tool to identify gait impairment in RBD.

Background: Urate and homocysteine are potential biomarkers for disease progression in Parkinson’s disease (PD). Baseline serum urate concentration has been shown to predict motor but not cognitive decline. The relationship between serum homocysteine concentration and cognitive and motor impairment is unknown. Objectives: The aim of this study was to examine the association between baseline serum urate and homocysteine, and prospective measures of disease progression and cognition over 54 months in early PD. Methods: 154 newly diagnosed PD participants and 99 age-matched controls completed a schedule of assessments at baseline, 18, 36 and 54 months. The Movement Disorders Society Unified Parkinson’s Disease Scale Part III (MDS-UPDRS III) was used to assess motor severity. The Montreal Cognitive Assessment (MoCA) was used to assess global cognition. Serum samples drawn at baseline were analysed for urate, homocysteine, red cell folate and vitamin B12 concentrations. Results: Baseline urate was 331.4±83.8 and 302.7±78.0μmol/L for control and PD participants, respectively (p = 0.015). Baseline homocysteine was 9.6±3.3 and 11.1±3.8μmol/L for controls and PD participants, respectively (p

Background Visual hallucinations (VHs) are common in Parkinson's disease (PD), with prevalence ranging from 27-50% in cross-sectional cohorts of patients with well-established disease. However, minor hallucinations may occur earlier in the disease process than has been previously reported. Objective We sought to categorise VHs in a cohort of newly diagnosed PD patients and establish their relationship to other clinical features. Methods Newly diagnosed PD participants (n = 154) were recruited as part of the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation in PD (ICICLE-PD) study. Participants completed the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III), Montreal Cognitive Assessment (MoCA) and Parkinson's Disease Questionnaire (PDQ-39) to assess motor severity, cognition and quality of life (QoL), respectively. VHs were classified using the North East Visual Hallucinations Inventory. Hierarchical regression was used to build predictive models of motor severity, QoL and cognition. Results 22% (n = 34) of participants experienced recurrent VHs with minor VHs being most frequently reported (64.7% of hallucinators). Complex VHs were present in 32.4% of hallucinating participants. Linear regression showed VHs predicted poorer PDQ-39 and MoCA scores (β= 0.201, p = 0.006 and β= - 0.167, p = 0.01, respectively) but not motor severity (p > 0.05). Conclusions Over a fifth of people with newly diagnosed PD reported recurrent VHs; minor hallucinations were the most common, although a small proportion reported complex VHs. Recurrent VHs were found to be a significant independent predictor of cognitive function and QoL but not motor severity. Our findings highlight the importance of screening for VHs at diagnosis.

Abnormal sleep may associate with cognitive decline in Parkinson's disease (PD). Furthermore, sleep dysfunction may associate with worse motor outcome. We hypothesised that PD patients with poor quality sleep would have greater progression in gait dysfunction, due to structural and functional overlap in networks subserving sleep and gait regulation. 12 PD patients and 12 age-matched controls completed longitudinal follow-up over 36 months. Poor sleep efficiency and greater sleep fragmentation correlated significantly with progression of step-width variability, a gait characteristic mediated by postural control, providing evidence that poor sleep in PD is associated with a more rapid deterioration in gait.

Background: Cognitive decline is a frequent complication of Parkinson’s disease (PD) and the identification of predictive biomarkers for it would help in its management. Objective: Our aim was to analyse whether senescence markers (telomere length, p16 and p21) or their change over time could help to better predict cognitive and motor progression of newly diagnosed PD patients. We also compared these senescence markers to previously analysed markers of inflammation for the same purpose. Methods: This study examined the association of blood-derived markers of cell senescence and inflammation with motor and cognitive function over time in an incident PD cohort (the ICICLE-PD study). Participants (154 newly diagnosed PD patients and 99 controls) underwent physical and cognitive assessments over 36 months of follow up. Mean leukocyte telomere length and the expression of senescence markers p21 and p16 were measured at two time points (baseline and 18 months). Additionally, we selected five inflammatory markers from existing baseline data. Results: We found that PD patients had shorter telomeres at baseline and 18 months compared to age-matched healthy controls which also correlated to dementia at 36 months. Baseline p16 levels were associated with faster rates of motor and cognitive decline over 36 months in PD cases, while a simple inflammatory summary score at baseline best predicted cognitive score over this same time period in PD patients. Conclusion: Our study suggests that both inflammatory and senescence markers (p16) are valuable predictors of clinical progression in PD patients.

Recent guidance by the National Institute for Health and Care Excellence (NICE) focuses on the management of people with multimorbidity, including Parkinson's disease (PD). To date there has been little exploration of this in neurodegenerative diseases. This study aimed to explore the associations between multimorbidity, motor severity and quality of life (QoL) in early PD. Regression analyses determined whether multimorbidity was significantly associated with disease severity and QoL. Multimorbidity was a small but significant predictor of QoL in people with incident PD, but not motor severity, suggesting that they may benefit from a tailored multidisciplinary approach to care.

We evaluated the association between mild cognitive impairment (MCI) subtypes and quality of life (QoL) in 219 newly diagnosed Parkinson's disease (PD) patients without dementia. Participants completed neuropsychological tests of attention, executive function, visuospatial function, memory, and language, and reported QoL using the Parkinson's Disease Questionnaire. Impairments were most common in executive function, memory and attention. MCI subtypes were classified according to Movement Disorder Society Task Force criteria. More severe cognitive impairment was associated with poorer quality of life (p = 0.01), but subtype of impairment was not (p0.10), suggesting that the nature of cognitive impairment is less significant than its severity.