Physical Health Monitoring Following Risperidone Prescription in Dementia: Development of Empirically Informed Patient-Centred Guidance to Detect Treatment-Emergent Side Effects

Research question: What are the most appropriate and feasible clinical parameters for monitor during antipsychotic treatment for people with dementia? Background: Antipsychotic drugs like risperidone are the only licensed treatment for severe agitation and aggression in dementia. While avoiding starting unnecessary prescriptions is important to minimise harm it does not fully address safety management because there is still stroke risk for those people where prescriptions are clinically indicated. Given some prescriptions are necessary, it follows that careful clinical monitoring during use is needed. However, while there is NICE guidance on physical health monitoring during antipsychotic prescription for people with schizophrenia there is none for antipsychotic use in dementia. We will address this gap by analysing individual-participant level clinical trial data to identify which clinical markers are associated with risk of antipsychotic-induced stroke. We will contextualise these findings with qualitative research to ensure our outputs are patient-focused and relevant for both health and social care. Aims and Objectives: We will develop dementia-specific physical health monitoring guidance for patients, clinicians, family members and social care workers. To do this we aim to: Identify physical health monitoring priorities, and views and attitudes towards the best ways of communicating outcomes from risk prediction models. Determine the associations between changes in clinical monitoring measures after antipsychotic initiation and subsequent stroke risk. Assess the potential for dynamic models of stroke risk for dementia patients, based on time-updated monitoring measures. Methods: Work package 1 (WP1): interviews with people with dementia, carers, and clinicians explore feasible clinical parameters, key side effects, effective communication of risk predictions, and situations where monitoring may be inappropriate. Recruitment focuses on ethnoculturally diverse and underserved groups, including care homes specializing in learning disabilities. Data will be analysed using Framework Analysis to identify themes across participant groups. WP2: Analysis of individual-level data from six RCTs (N=1,287) of risperidone for dementia. Time-dependent Cox regression and joint longitudinal-survival models will examine relationships between clinical markers (e.g., blood pressure) and stroke risk, enabling dynamic prediction. WP3: Stakeholder workshops using co-design methods to refine guidance. This guidance will be retrospectively tested against real-world CPRD data to ensure feasibility and scalability, addressing barriers to implementation in routine care. Timelines: Ethics approval WP1 (month 4). Interview and focus groups completed (month 11). Data acquisition from YODA (month 3). Preparation of data (month 6). Drafting and publication of analysis protocol (month 9). Analysis (month 12). Co-produced new guidance completed (month 14). Impact and Dissemination: By the end of this project, we will have co-produced evidence-based outputs (e.g., updates to prescribing resources and new decision aids) that can be implemented within NHS Trusts and social care immediately. In PPI work informing this project we have also learned that care home staff are central to prescribing decisions in some areas of social care, so we will also ensure guidance is suitable for their needs and implementation in social care is factored into development. These resources will be free to use and made available online.