Many people living with dementia experience sleep disturbance and there are no known effective treatments. Non-pharmacological treatment options should be the first-line sleep management. For family carers, relatives’ sleep disturbance leads to interruption of their sleep, low mood and breakdown of care. Our team developed and delivered DREAMS START (Dementia RElAted Manual for Sleep; STrAtegies for RelaTives), a multimodal non-pharmacological intervention, showing it to be feasible and acceptable. The aim of this randomised controlled trial is to establish whether DREAMS START is clinically cost-effective in reducing sleep disturbances in people living with dementia living at home compared with usual care.

We will recruit 370 participant dyads (people living with dementia and family carers) from memory services, community mental health teams and the Join Dementia Research Website in England. Those meeting inclusion criteria will be randomised (1:1) either to DREAMS START or to usual treatment. DREAMS START is a six-session (1 hour/session), manualised intervention delivered every 1–2 weeks by supervised, non-clinically trained graduates. Outcomes will be collected at baseline, 4 months and 8 months with the primary outcome being the Sleep Disorders Inventory score at 8 months. Secondary outcomes for the person with dementia (all proxy) include quality of life, daytime sleepiness, neuropsychiatric symptoms and cost-effectiveness. Secondary outcomes for the family carer include quality of life, sleep disturbance, mood, burden and service use and caring/work activity. Analyses will be intention-to-treat and we will conduct a process evaluation.

London—Camden & Kings Cross Ethics Committee (20/LO/0894) approved the study. We will disseminate our findings in high-impact peer-reviewed journals and at national and international conferences. This research has the potential to improve sleep and quality of life for people living with dementia and their carers, in a feasible and scalable intervention.

ISRCTN13072268.

To identify factors associated with malnutrition (undernutrition and overnutrition) and determine appropriate cut-off values for mid-arm circumference (MAC) and calf circumference (CC) among community-dwelling Indian older adults.

Data from the first wave of harmonised diagnostic assessment of dementia for Longitudinal Ageing Study in India (LASI-DAD) were used. Various sociodemographic factors, comorbidities, geriatric syndromes, childhood financial and health status were included. Anthropometric measurements included body mass index (BMI), MAC and CC.

Nationally representative cohort study including 36 Indian states and union territories.

4096 older adults aged >60 years from LASI DAD.

The outcome variable was BMI, categorised as low (2), normal (18.5–22.9 kg/m²) and high (>23 kg/m²). The cut-off values of MAC and CC were derived using ROC curve with BMI as the gold standard.

902 (weighted percentage 20.55%) had low BMI, 1742 (44.25%) had high BMI. Undernutrition was associated with age, wealth-quintile and impaired cognition, while overnutrition was associated with higher education, urban living and comorbidities such as hypertension, diabetes and chronic heart disease. For CC, the optimal lower and upper cut-offs for males were 28.1 cm and >31.5 cm, respectively, while for females, the corresponding values were 26 cm and >29 cm. Similarly, the optimal lower and upper cut-offs for MAC in males were 23.9 cm and >26.9 cm, and for females, they were 22.5 cm and >25 cm.

Our study identifies a high BMI prevalence, especially among females, individuals with higher education, urban residents and those with comorbidities. We establish gender-specific MAC and CC cut-off values with significant implications for healthcare, policy and research. Tailored interventions can address undernutrition and overnutrition in older adults, enhancing standardised nutritional assessment and well-being.

To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system.

Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention.

Kaiser Permanente Northern California, a large integrated health system with 4.2 million members.

Current smokers aged ≥18 hospitalised for any reason.

EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015).

Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits.

The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%).

An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Stroke is a major cause of death and disability worldwide, frequently resulting in persistent cognitive deficits among survivors. These deficits negatively impact recovery and therapy engagement, and their treatment is consistently rated as high priority by stakeholders and clinicians. Although clinical guidelines endorse cognitive screening for poststroke management, there is currently no gold-standard approach for identifying cognitive deficits after stroke, and clinical stroke services lack the capacity for long-term cognitive monitoring and care. Currently, available assessment tools are either not stroke-specific, not in-depth or lack scalability, leading to heterogeneity in patient assessments.

To address these challenges, a cost-effective, scalable and comprehensive screening tool is needed to provide a stroke-specific assessment of cognition. The current study presents such a novel digital tool, the Imperial Comprehensive Cognitive Assessment in Cerebrovascular Disease (IC3), designed to detect both domain-general and domain-specific cognitive deficits in patients after stroke with minimal input from a health professional. To ensure its reliability, we will use multiple validation approaches, and aim to recruit a large normative sample of age-matched, gender-matched and education-matched UK-based controls. Moreover, the IC3 assessment will be integrated within a larger prospective observational longitudinal clinical trial, where poststroke cognition will be examined in tandem with brain imaging and blood biomarkers to identify novel multimodal biomarkers of recovery after stroke. This study will enable deeper cognitive phenotyping of patients at a large scale, while identifying those with highest risk of progressive cognitive decline, as well as those with greatest potential for recovery.

This study has been approved by South West—Frenchay Research Ethics Committee (IRAS 299333) and authorised by the UK’s Health Research Authority. Results from the study will be disseminated at conferences and within peer-reviewed journals.

NCT05885295. Stage: Pre-results.