Andrew Clegg

Theme Lead

Andy is a Clinical Senior Lecturer in the Academic Unit for Ageing and Stroke Research, University of Leeds, and is an Honorary Consultant Geriatrician at Bradford Teaching Hospitals, with research interests in frailty, delirium and dementia. Andy is chief investigator for an NIHR Programme Grant to evaluate personalised care planning for older people with frailty; the NIHR HTA-funded Home-based Extended Rehabilitation for Older People (HERO) trial, and for the Community Ageing Research 75+ (CARE 75+) multi-site cohort study. Andy led the development, validation and implementation of NICE recommended electronic Frailty Index (eFI) using data from around 1million UK patients (ResearchOne and THIN primary care research databases), which resulted in major impact on NHS policy.

Andrew Clegg's latest projects

The INCLUDE study: Development of methods to identify digitally excluded older people, and tailoring of interventions to meet their digital needs

Background Older people are more likely to be ‘digitally excluded’. This refers to them not using the internet, so missing out on things that could be helpful to their well-being...

Development and national implementation of eFI-2

Currently, the UK and international guidelines support routine identification of frailty in primary care to enable timely and targeted care for older people. Our Older people with Frailty theme lead,...

Cross-ARC expansion of CARE75+ cohort study

The Community Ageing Research (CARE75+) Study is a longitudinal cohort study that recruits older people (≥ 75 years) via General Practices across England. The study is hosted at Bradford Teaching...

Andrew Clegg's latest publications

An automation framework for clinical codelist development validated with UK data from patients with multiple long-term conditions

Differences in the risk of frailty based on care receipt, unmet care needs and socio-economic inequalities: A longitudinal analysis of the English Longitudinal Study of Ageing

Primary care prediction of hip and knee replacement 1–5 years in advance using Temporal Graph-based Convolutional Neural Networks (TG-CNNs)

Frailty in randomized controlled trials of glucose-lowering therapies for type 2 diabetes: An individual participant data meta-analysis of frailty prevalence, treatment efficacy, and adverse events

The uncertainties and questions of care home residents, relatives and staff as a basis for evidence-based improvement and research

Developing prediction models for electrolyte abnormalities in patients indicated for antihypertensive therapy: evidence-based treatment and monitoring recommendations

Other Team members

Emmanuel Nwofe

Research Associate

Lin Gong

Research Fellow

Amirah Akhtar

Research Associate