Cognitive profile and determinants of poor cognition in people without dementia in Parkinson's disease.

Background: The Montreal Cognitive Assessment (MoCA) has been recommended as a cognitive screening tool for clinical practice and research in Parkinson's disease (PD), yet no normative data have been published for MoCA in PD without dementia. Methods: We undertook a pooled secondary analysis of data from two studies (one cross-sectional design and one clinical trial) conducted in the East of England region. All participants were aged 18 years or over, met UK Brain Bank criteria for PD and did not have clinical dementia. Cognitive status was assessed using MoCA at baseline in both studies. The influences of age, gender, disease duration, medication load (LEDD) and mood (HADS) on cognition were examined using regression analysis. Results: Data from 101 people with PD without dementia were available (mean age 71 years, 66% men). Median (IQR) MoCA was 25(22, 27). Age was found as the only predictor of MoCA in this sample. People aged over 71 had poorer MoCA (Beta=0.6 (95%CI 0.44, 0.82)) and an increased odds of MoCA <26 (Beta=0.29 (95%CI 0.12, 0.70)) as well as poorer scores on several MoCA sub-domains. Conclusion: We present the normative data for MoCA in people with PD without clinical dementia. Age appeared to be the only associated factor for lower level of cognition, suggestive of Mild cognitive impairment in PD (PD-MCI) in PD without clinical diagnosis of dementia.

Priority setting partnership to identify the top 10 research priorities for the management of Parkinson's disease.

OBJECTIVES: This priority setting partnership was commissioned by Parkinson's UK to encourage people with direct and personal experience of the condition to work together to identify and prioritise the top 10 evidential uncertainties that impact on everyday clinical practice for the management of Parkinson's disease (PD). SETTING: The UK. PARTICIPANTS: Anyone with experience of PD including: people with Parkinson's (PwP), carers, family and friends, healthcare and social care professionals. Non-clinical researchers and employees of pharmaceutical or medical devices companies were excluded. 1000 participants (60% PwP) provided ideas on research uncertainties, 475 (72% PwP) initially prioritised them and 27 (37% PwP) stakeholders agreed a final top 10. METHODS: Using a modified nominal group technique, participants were surveyed to identify what issues for the management of PD needed research. Unique research questions unanswered by current evidence were identified and participants were asked to identify their top 10 research priorities from this list. The top 26 uncertainties were presented to a consensus meeting with key stakeholders to agree the top 10 research priorities. RESULTS: 1000 participants provided 4100 responses, which contained 94 unique unanswered research questions that were initially prioritised by 475 participants. A consensus meeting with 27 stakeholders agreed the top 10 research priorities. The overarching research aspiration was an effective cure for PD. The top 10 research priorities for PD management included the need to address motor symptoms (balance and falls, and fine motor control), non-motor symptoms (sleep and urinary dysfunction), mental health issues (stress and anxiety, dementia and mild cognitive impairments), side effects of medications (dyskinesia) and the need to develop interventions specific to the phenotypes of PD and better monitoring methods. CONCLUSIONS: These research priorities identify crucial gaps in the existing evidence to address everyday practicalities in the management of the complexities of PD.

The use of carer assisted adherence therapy for people with Parkinson's disease and their carers (CAAT-PARK): study protocol for a randomised controlled trial.

BACKGROUND: Pharmacological intervention is essential for managing the symptoms of Parkinson's disease. Adherence to medication regimens however is a major problem. Poor adherence leads to significant motor deterioration and inadequate symptom control. This results in poor quality of life. Whilst interventions to improve medication adherence have shown considerable benefit in other chronic conditions, the efficacy of such treatments in Parkinson's disease is less well researched. Many people with Parkinson's disease require substantial support from spouse/caregivers. This often extends to medication taking. Consequently, spouse/caregiver's support for timely medication management is paramount. We aim to investigate the benefit of a novel intervention, Carer Assisted Adherence Therapy, for improving medication adherence and quality of life in people with Parkinson's disease. Adherence therapy may help to optimise the efficacy of anti-parkinsonian agents, subsequently improving clinical outcomes. METHODS/DESIGN: A parallel, randomised controlled trial will be conducted to investigate whether carer assisted adherence therapy is effective for improving medication adherence and quality of life. We aim to recruit 40 patient/carer pairs into each group. Participants will be randomly assigned by the Clinical Research Trials Unit at the University of East Anglia. Adherence therapy is a brief cognitive-behavioural approach aimed at facilitating a process of shared decision making. The central theory is that when patients make shared choices with a professional they are more likely to continue with those choices because they are personally owned and meaningful. Outcomes will be rates of adherence and quality of life, determined by the Morisky Medication Adherence Scale-4 and the Parkinson's disease Questionnaire-39 respectively. Assessments will take place post randomisation, immediately post intervention and 12-weeks post randomisation. Primary outcomes are adherence and quality of life at 12-week follow-up. Efficacy will be determined using intention-to-treat analysis. Independent samples t-tests will compare mean changes between groups from baseline to follow-up. Per protocol analysis will be conducted based on individuals with no major protocol deviation. Where imbalances in baseline characteristics are identified, an adjusted analysis will be performed using a regression model. Analysis will be masked to treatment allocation. TRIAL REGISTRATION: ISRCTN: ISRCTN07830951.