To develop and validate a model to predict cognitive decline within 12 months for home care clients without a diagnosis of dementia.
We included all adults aged ≥ 18 years who had at least two interRAI Home Care assessments within 12 months, no diagnosis of dementia and a baseline Cognitive Performance Scale score ≤ 1. The sample was randomly split into a derivation cohort (75%) and a validation cohort (25%). Significant cognitive decline was defined as an increase (deterioration) in Cognitive Performance Scale scores from ‘0’ or ‘1’ at baseline to a score of ≥ 2 at the follow-up assessment.
Using the derivation cohort, a multivariable logistic regression model was used to predict cognitive decline within 12 months. Covariates included demographics, disease diagnoses, sensory and communication impairments, health conditions, physical and social functioning, service utilisation, informal caregiver status and eight interRAI-derived health index scales. The predicted probability of cognitive decline was calculated for each person in the validation cohort. The c-statistic was used to assess the model's discriminative ability. This study followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guidelines.
A total of 6796 individuals (median age: 82; female: 60.4%) were split into a derivation cohort (n = 5098) and a validation cohort (n = 1698). Logistic regression models using the derivation cohort resulted in a c-statistic of 0.70 (95% CI 0.70, 0.73). The final regression model (including 21 main effects and 8 significant interaction terms) was applied to the validation cohort, resulting in a c-statistic of 0.69 (95% CI 0.66, 0.72).
interRAI data can be used to develop a model for identifying individuals at risk of cognitive decline. Identifying this group enables proactive clinical interventions and care planning, potentially improving their outcomes. While these results are promising, the model's moderate discriminative ability highlights opportunities for improvement.
Self-harm represents a significant public health concern and is a common reason for contact with urgent and emergency care (UEC) services among young people. Although young people frequently interact with multiple components of the urgent care system following self-harm, there is limited system-level evidence describing patterns of service use, transitions between services and repeat emergency department (ED) attendance. An improved understanding of how young people use UEC services after self-harm is needed to inform the design of more effective and appropriate care pathways.
This protocol describes a prospective cohort study using an extract from the Centre for URgent and Emergency care research database (CUREd+) research database, which comprises routinely collected, linked healthcare data from the National Health Service 111 (NHS 111), ambulance services, urgent care centres, walk-in centres and EDs across Yorkshire and the Humber, England. The study population will include young people aged ≤25 years presenting to UEC services between April 2019 and March 2022 with self-harm coded as the reason for attendance. Analyses will describe the prevalence of self-harm presentations across UEC settings, quantify the proportion of NHS 111 and ambulance contacts resulting in ED attendance within 24 hours and examine factors associated with ED reattendance at 3 and 12 months. Mixed-effects logistic regression models will be used to account for repeated attendances, confounding variables and temporal variation, including changes related to the COVID-19 pandemic. Anticipated analysis period: January 2026–January 2027.
Ethical approval has been granted by the University of Leeds (MREC 22-079 Amd1) and the University of Sheffield (Ref 068194). The CUREd+ research database operates under Research Ethics Committee approval (23/YH/0079) and Confidentiality Advisory Group approval (18/CAG/0126). Individual consent is not required as all data are pseudonymised at source. Findings will be disseminated through peer-reviewed publications, conference presentations and public-facing outputs coproduced with patient and public involvement groups.
Frequent use of emergency departments (EDs) places a considerable burden on healthcare systems. Although frequent attenders are known to have complex physical, mental health and social needs, national-level evidence on their characteristics and patterns of attendance remains limited. This study aimed to provide a comprehensive, population-level description of frequent ED attendance in England, with a focus on age-based subgroups.
Retrospective cohort study.
EDs in England via the Hospital Episode Statistics and the Emergency Care Dataset data linked with primary care prescribing and mortality data, between March 2016 and March 2021.
The dataset received from National Health Service Digital contained approximately 150 million ED attendances by 30 million adult (>18 years) patients over the time period April 2016 to March 2021. A random sample of 5 million people was used for this analysis.
The primary outcome was the number of attendances in each financial year by frequent attenders compared with the remaining patients, split by age bands. Patients were classified as frequent attenders if they had ≥5 or ≥10 ED attendances within a rolling 12-month period. Secondary outcomes included demographic, diagnostic and prescribing characteristics, as well as the number of different ED sites visited.
A Gaussian mixture model was used to identify age-based subgroups. Descriptive statistics were used to summarise key features; 95% CIs were reported where applicable. Among 3.91 million unique adult ED attenders, there were 8.7 million attendances. Of these, 222 160 individuals (5.7%) had ≥5 attendances in a year, accounting for 12.6% of total attendances. A trimodal age distribution was identified, with three distinct peaks corresponding to ages 18–34, 35–64 and 65+. Frequent attenders were more likely to live in deprived areas and have a history of psychotropic or analgesic prescribing. Mental health diagnoses and polypharmacy were particularly common in the younger and middle-aged groups. Multisite attendance was uncommon, with over 80% of frequent attenders using only one ED site annually.
This national analysis reveals a trimodal age pattern among frequent ED attenders, with differing clinical and socio-demographic profiles across age groups. These findings highlight the need for age-tailored approaches to managing high-intensity ED use and inform targeted service development.