Clinical Academic Training

Projects

Projects by topic

Clinical Radiology

Cerebrovascular reactivity assessed using fMRI and transcranial Doppler ultrasound in acute intracerebral haemorrhage (ICH) - multimodal integration for post ICH cerebrovascular assessment

Supervisor: Dr Jatinder Minhas ([email protected])

This NIHR ACF offers a unique opportunity for a clinical radiology trainee to sit at the interface between stroke medicine, advanced neuroimaging and clinical physiology. Importantly, this trainee will be afforded an opportunity to learn and develop within the internationally recognised Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM) Research Group – providing growth in our magnetic resonance imaging (particularly functional MRI (fMRI) scanning) offer in addition to using established modalities like transcranial Doppler ultrasonography. Novel studies are ongoing: Ischaemic Lesions in Acute Intracerebral Haemorrhage (CHALLENGE-ICH) and there is opportunity to draw on training the PI (Minhas) is gaining at the University of Oxford to deliver fMRI scans in Leicester. With newly appointed specialist staff, a neuroradiologist with a strong academic interest (Swienton) and exceptional infrastructure afforded by the cardiac imaging academic team (McCann) – now is an excellent time for multi-modality research to address key mechanistic questions in acute intracerebral haemorrhage care.

The trainee would have access to formal training as part of the Leicester Transcranial Doppler Ultrasound course, fMRI training from experts in Leicester, Nottingham and Oxford and engaged supervision to enable a competitive doctoral Fellowship submission to a major funder. The group has a strong track record of supporting trainees through the NIHR Walport pathway to senior academic positions.

Weight loss interventions for the reversal of stage B heart failure in people living with multiple long-term conditions

Supervisor: Professor Gerry McCann ([email protected])

Heart failure (HF) affects over 1million people in the UK and the prognosis is worse than for most cancers. Obesity is an independent risk factor for HF and often co-exists with other long-term conditions such as T2D; hypertension, atrial fibrillation and kidney disease; all of which increase HF risk. Stage B HF exists when there is evidence of structural or functional cardiac abnormalities but before symptoms arise and represents an opportunity to intervene to reduce the risk of HF developing.

Working closely with the Leicester Diabetes Centre and the lifestyle theme of the NIHR Leicester BRC, Prof McCann has been conducting trials of weight loss (with low calorie meal replacement plan[MRP] and pharmacological interventions/combinations) in diabetes. The ACF will undertake a systematic review and a network meta-analysis to assess the most effective interventions for ameliorating stage B HF. The ACF will be given access to trial data (including MRI and echocardiography) of patients with T2D and stage BH to assess the effects of reverse cardiac remodelling by Liraglutide (GLP-1RA); low-calorie MRP; dapagliflozin (SGLT2i); exercise training and Tirzepatide (GLP-1RA/ GIP RA).

The ACF will join a dynamic, diverse and growing research group with an outstanding track record in developing clinical academics.

Attention-Guided Multi-View Deep Learning Model for Ankle Fracture Detection and localization in Large-Scale UK Radiograph Data

Supervisor: Mr Jitendra Mangwani ([email protected])

An innovative deep learning model is proposed to improve detection and localization of ankle fractures using large-scale UK radiograph data. This approach aims to reduce diagnostic errors and support rapid, explainable clinical decisions in high-demand settings.

Model architecture and function: The model uses a shared feature extractor backbone common to all radiographic views, followed by two branches: a classification branch for binary fracture detection and a localisation branch producing interpretable overlays highlighting fracture regions.

Technical design details: Feature maps extracted by the shared encoder are combined with view embedding vectors and processed through cross-view attention fusion for classification, while view-specific decoders with attention modules generate segmentation masks or heatmaps for clinical interpretation.

Clinical impact and potential: The project targets emergency and orthopaedic professionals, addressing a known diagnostic challenge with a scalable, clinically informed approach that may lead to intellectual property with significant global commercial potential.

Characterising the heterogeneity of Tuberculosis

Supervisor: Dr Pranabashis Haldar ([email protected])

Although a disease caused by a single family of pathogens, a hallmark of Tuberculosis (TB) is the variability with which it causes disease in humans. This is a key reason why elimination strategies have remained unsuccessful despite availability of effective antibiotic therapy.

Our programme of research investigates the phenotypic patterns and underlying biological mechanisms of heterogeneity in human infection with Mycobacterium tuberculosis. Our work encompasses studies examining different clinical patterns of disease, heterogeneity of TB risk in those with evidence of the infection and variability in the response to treatment, Using state of the imaging methods and recruitment of longitudinal cohorts, we aim to understand the biological basis of these differences.

Potential candidates will join a diverse group o researchers with scope to consider a breadth of project types, including clinically focussed, data driven (including imaging), or laboratory based studies (to be discussed). The projects will be deliverable within the time course of an ACF rotation and provide outcomes to support a doctoral fellowship application- including supporting pilot data for a larger research study, submitted abstracts to national and international conferences, and one or more publications (either completed or in process).

Endocrinology and Diabetes

A systematic review of target trial emulations for SGLT2 inhibitors: robustness of methods and estimated clinical outcomes

Supervisor: Professor Clare Gillies ([email protected])

Target trial emulation (TTE) uses observational data, such as electronic health records, to mimic the protocol of a hypothetical randomised controlled trial. TTE has emerged as an important framework for generating real-world evidence on the effectiveness and safety of sodium-glucose cotransporter-2(SGLT2) inhibitors.

While numerous observational studies have applied TTE methods to evaluate SGLT2 inhibitors across cardiovascular, kidney and metabolic outcomes, the methodological quality and robustness of these studies have not been systematically assessed. This systematic review aims to identify and synthesisetarget trial emulation studies examining SGLT2 inhibitors in adults, summarising their reported clinical outcomes, including cardiovascular events, kidney disease progression, heart failure, mortality and safety outcomes.

A second objective is to critically evaluate the design, conduct and reporting of TTE methods, including specification of eligibility criteria, treatment strategies, assignment procedures, follow-up, outcome definitions, handling of confounding, causal estimands and sensitivity analyses.

By assessing both clinical findings and methodological rigour, this review will provide insights into the reliability of current evidence and inform best practice for future target trial emulations in cardio-kidney-metabolic research.

A systematic review and meta-analysis of group-based and self-management education interventions for type 2 diabetes

Supervisor: Professor Clare Gillies ([email protected])

Building on the previous systematic reviews, this project will provide an updated and comprehensive synthesis of the evidence on group-based diabetes self-management education (DSME) for adults with type 2 diabetes mellitus.

Previous research has identified improvements in glycaemic control, diabetes knowledge and self-management outcomes associated with group-based education interventions. Substantial new evidence has emerged since the last substantial systematic review in this area published in 2012, including studies evaluating structured education programmes, digital and hybrid delivery models, culturally tailored interventions, and long-term clinical outcomes. The proposed review will systematically identify and synthesise randomised and non-randomised studies published since the previous review, assessing the effectiveness of group-based DSME compared with usual care or alternative educational approaches.

Primary outcomes will include glycated haemoglobin (HbA1c), diabetes-related complications, healthcare utilisation, quality of life, and patient-reported outcomes. Secondary outcomes will include diabetes knowledge, self-efficacy, medication adherence, and behavioural risk factor modification. Where appropriate, meta-analyses will be conducted to provide updated pooled estimates of effectiveness.

The methodological quality and risk of bias of included studies will be assessed using contemporary appraisal tools. This review will inform clinicians, policymakers and guideline developers regarding the current effectiveness of group-based DSME and identify priorities for future programme development and research in type 2 diabetes care

Preventing Gestational Diabetes Through Early Pregnancy Dietary Intervention: A Mechanistic Study

Supervisor: Dr Claire Meek ([email protected])

Gestational diabetes mellitus (GDM) affects one in six pregnancies worldwide and increases the risk of pregnancy complications, future type 2 diabetes and cardiovascular disease for both mothers and their children. However, the biological mechanisms underlying GDM remain incompletely understood. This project aims to identify whether dietary interventions in early pregnancy can modify metabolism and reduce the risk of developing GDM.

Embedded within DODGE Diabetes, an MRC-funded mechanistic trial investigating the effects of dietary interventions on body composition, metabolism and glucose regulation during pregnancy, the project will address three key questions:

• How does body fat change during pregnancy in women at high risk of GDM?

• How do body fat and metabolism influence blood glucose levels during pregnancy?

• How do women experience dietary interventions, and what helps or hinders adherence?

• Key activities:

(1) systematic review of body composition and metabolic adaptation in pregnancy.

(2) analyses of DODGE trial data, related to body composition, dietary and physical activity.

(3) a qualitative interview study exploring women's experiences of dietary interventions.

The project will provide training in clinical trials, evidence synthesis, nutritional epidemiology, body composition research and qualitative methods, providing a strong platform for a future doctoral fellowship in diabetes prevention and maternal metabolic health.

Novel technology for diabetes in pregnancy: Continuous Ketone Monitoring (CKM) in the DOMINO Cohort

Supervisor: Dr Claire Meek ([email protected])

Women with type 1 diabetes continue to experience suboptimal pregnancy outcomes despite recent advances in diabetes technology. This project will generate foundational evidence on the role of continuous ketone monitoring (CKM) in pregnancy, informing the future development of CKM-guided interventions to prevent diabetic ketoacidosis (DKA) and improve maternal and neonatal outcomes.

Methods: CKM will be embedded in the DOMINO study, a multicentre prospective cohort evaluating continuous ketone monitoring (CKM) in pregnant women with type 1 diabetes.

The project will address key questions:

• What is the existing evidence linking maternal ketone exposure with perinatal outcomes?

• What factors influence ketone production in pregnancy?

• How acceptable is continuous ketone monitoring to women with type 1 diabetes?

Activities and skills developed:

(1) A systematic review and meta-analysis of maternal ketone exposure and pregnancy outcomes.

(2) Longitudinal analyses of CKM, continuous glucose monitoring (CGM), dietary, physical activity and insulin-delivery data from the DOMINO cohort.

(3) A qualitative interview study exploring women's experiences and views of CKM.

The project will provide training in evidence synthesis, epidemiology, longitudinal cohort analysis, high-frequency sensor data, qualitative research, mixed-methods methodology, patient and public involvement, scientific writing and grant development, providing an excellent platform for progression to a PhD and a future academic career in diabetes or pregnancy research.

MIND-MET: Implementing prophylactic GLP-1 treatment during antipsychotic initiation in acute psychiatric care

Supervisors: Professor David Webb ([email protected]) | Dr Hari Subramaniam ([email protected]) | Dr Michelle Hadjiconstantinou ([email protected])

Despite growing efficacy and safety data supporting glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for antipsychotic-induced weight gain (AIWG), an important gap remains in how and when to implement these treatments within psychiatric services. Clinical trials suggest that GLP-1 RAs reduce metabolic risk without disrupting psychiatric stability in outpatients, but whether they can be introduced prophylactically during an acute admission is unknown. There is little implementation science evidence addressing the clinical workflows required for safe and effective initiation in this setting.

This project will deliver a single-centre pilot study (n=15-20) generating integrated mixed-methods evidence on feasibility, uptake, weight trajectory, tolerability and safety. GLP-1 RA obesity pharmacotherapy will be initiated in adult inpatients with capacity to consent who are starting antipsychotic treatment. Relevant regulatory and governance approvals will be obtained, and treatment will be monitored within an established multidisciplinary framework. Qualitative work and a systematic review will explore lived experiences of AIWG and GLP-1 RAs, alongside staff perspectives on integrated care models.Findings will inform a larger multicentre study and a subsequent fellowship application.

The project directly addresses the 2026 NIHR James Lind Alliance priority on using GLP-1 medicines to prevent or manage psychiatric-medication-associated weight gain.

Weight loss interventions for the reversal of stage B heart failure in people living with multiple long-term conditions

Supervisor: Professor Gerry McCann ([email protected])

The ACF will join a dynamic, diverse and growing research group with an outstanding track record in developing clinical academics.

Protecting skeletal muscle during pharmacological weight loss: the role of protein supplementation

Supervisor: Dr Dimitris Papamargaritis ([email protected])

Medications targeting the GLP-1 receptor, including GLP-1/GIP receptor agonists, are highly effective treatments for obesity and type 2 diabetes, producing substantial and clinically meaningful weight loss. However, weight loss may also be accompanied by reductions in skeletal muscle mass. Whether nutritional strategies can help preserve muscle during pharmacological weight loss remain an important unanswered question.

The ACF will be embedded within an ongoing platform trial at the Leicester Diabetes Centre and will contribute to two existing study arms: tirzepatide with protein supplementation and tirzepatide with placebo supplementation.

The project will provide the ACF with experience in clinical trial delivery alongside detailed physiological and mechanistic investigation of skeletal muscle during pharmacological weight loss.

Specifically, the ACF will:

• Contribute to participant recruitment, assessment and data collection.

• Undertake medical and protein supplementation reviews under appropriate supervision.

• Receive training in, and assist with, skeletal muscle biopsy procedures where appropriate.

• Contribute to physiological phenotyping and assessment of muscle health.

• Analyse and interpret data from blood samples, skeletal muscle tissue and dietary records.

• Undertake evidence synthesis and systematic reviews relating to protein, skeletal muscle and pharmacological weight loss.

• Analyse existing datasets, including real-world evidence and pooled data from clinical trials conducted at the Leicester Diabetes Centre.

Towards precision obesity medicine: examining heterogeneity in treatment response to pharmacological and lifestyle weight management interventions

Supervisor: Dr Dimitris Papamargaritis ([email protected]) | Professor Thomas Yates ([email protected]) | Scott Willis ([email protected]) | Dr Greg Biddle ([email protected])

Obesity is a chronic, heterogeneous disease, and substantial variation exists in the weight and cardiometabolic benefits achieved through pharmacological and lifestyle treatments. Understanding why some individuals respond more favourably than others is increasingly important as obesity therapeutics expand and treatment choices become more complex.

Identifying phenotypes associated with treatment response and non-response could support more personalised approaches to weight management. This project will investigate heterogeneity in response to pharmacological, lifestyle and combined obesity interventions, identifying predictors and phenotypes associated with greater or lesser weight and cardiometabolic benefits.

It will combine primary experimental and secondary data analysis approaches, such as:

1. Adaptive platform trials: Working within the first-of-its-kind obesity-specific adaptive platform trials to identify sociodemographic, physiological and clinical predictors of weight and cardiometabolic responses to pharmacological, lifestyle and combined interventions.

2. Existing intervention studies: Secondary analyses of pharmacological and lifestyle weight-loss trials to identify phenotypes of differential treatment benefit.

3. Real-world evidence: Target trial emulation using large-scale datasets (e.g. CPRD, TriNetX) to investigate predictors of effectiveness and longer-term clinical outcomes of obesity therapies.

The ACF will gain training in clinical trials, epidemiology, advanced quantitative methods and real-world evidence, providing a strong platform for a future doctoral fellowship in precision obesity medicine.

A whole-person approach to tailored weight management in adults with type 1 diabetes and obesity

Supervisors: Professor Pratik Choudhary ([email protected]) | Dr Dimitris Papamargaritis ([email protected]) | Dr Lauren O’Mahoney ([email protected]) | Dr Jonah Thomas ([email protected])

More than 50% of individuals living with type 1 diabetes (T1D) are now also living with obesity. Management of obesity is made more complex due to the insulin treatment required, which also has the side effect of increasing the risk of hypoglycaemia.

Previous data has also suggested that those with T1D are less physically active compared with those without diabetes. There is a need to better understand and characterise differences in glucose metrics, physical activity and sleep in individuals with T1D and obesity to develop tailored weight-management interventions. This project will take a whole-person approach to obesity in T1D, combining clinical research with wearable technology to explore health, lifestyle and behavioural factors. It will use established databases to examine the relationship between CGM, activity, and sleeps metrics and between individuals living with T1D and obesity whilst giving the opportunity to recruit and collect primary data from individuals using CGM and activity trackers.

The aims of this project are:

1. To characterise the 24-hour movement behaviours and cardiometabolic profile of adults with T1D and obesity.

2. To explore associations between 24-hour movement behaviours and whole-person health and lifestyle profiles in adults with T1D and obesity.

Real-world effectiveness of medications in early-onset type 2 diabetes

Supervisors: Professor Melanie Davies ([email protected]) | Dr Jonathan Goldney ([email protected]) | Dr Carlos Wong ([email protected])

Weight-lowering medications may be a particularly relevant treatment option for younger people, as excess adiposity is a key driver of early-onset type 2 diabetes. However, it remains unclear whether the effectiveness, safety and use of newer weight- and glucose-lowering therapies differ between people with early- and later-onset type 2 diabetes, or how medication-taking behaviours affect the risk of diabetes-related complications.

Using data from CPRD and TriNetX, the aims of this project are to:

• explore effectiveness and safety of newer medications in early-onset vs. later-onset type 2 diabetes

• investigate associations between clinical inertia and medication-taking behaviours with age at type 2 diabetes diagnosis and risk of complications

• conduct a target trial emulation study to explore whether early initiation of newer weight- and glucose-lowering therapies improves outcomes compared to other glucose-lowering therapies

The ACF will join an internationally recognised research group at the Diabetes Research Centre, and will sit within the Lifestyle research theme of the NIHR Leicester Biomedical Research Centre, also working closely the Data Innovation for Multiple Long Term Conditions and Ethnic Health theme.They will experience a range of clinical trials and other research methods (e.g. qualitative and quantitative research, evidence synthesis/reviews and analyses of real world evidence). We will provide all suitable training to conduct this research project. Over the course of their fellowship, the ACF will be ideally placed and well supported in developing a future fellowship program towards a PhD in a related area.

Understanding perceptions of wearable technologies and associations with psychosocial outcomes in early-onset type 2 diabetes

Supervisors: Professor Melanie Davies ([email protected]) | Dr Michelle Hadjiconstantinou ([email protected]) | Professor Pratik Choudhary ([email protected])

Early-onset type 2 diabetes (EOT2D) is associated with a substantial clinical and psychosocial burden. Wearable technologies, such as continuous glucose monitoring (CGM), may support self-management and improve glycaemic outcomes in this population, but attitudes towards wearable technologies are poorly understood. Furthermore, little is known about the relationship between wearable technologies and psychosocial wellbeing (including diabetes distress and stigma). Understanding perspectives about the use of wearable technologies, and whether CGM-derived outcomes interact with psychosocial outcomes could inform more person-centred approaches to EOT2D care.

The aims of the project are to: • Understand perceptions of wearable technologies and associations with psychosocial outcomes • qualitatively and quantitatively assess attitudes of people with EOT2D towards wearable diabetes technologies (glucose monitors, activity trackers, insulin pumps) • using pooled data from clinical trials conducted at the Leicester Diabetes Centre, explore associations between continuous glucose monitor-derived outcomes and stigma and distress in people with EOT2D.

The ACF will join an internationally recognised research group at the Diabetes Research Centre, and will sit within the Lifestyle research theme of the NIHR Leicester Biomedical Research Centre, also working closely the Data Innovation for Multiple Long Term Conditions and Ethnic Health theme. They will experience a range of clinical trials and other research methods (e.g. qualitative and quantitative research, evidence synthesis/reviews and analyses of real world evidence). We will provide all suitable training to conduct this research project. Over the course of their fellowship, the ACF will be ideally placed and well supported in developing a future fellowship program towards a PhD in a related area.

24-h physical behaviours and glycaemic outcomes in early-onset type 2 diabetes

Supervisors: Professor Melanie Davies ([email protected]) | Professor Pratik Choudhary ([email protected]) | Professor Thomas Yates ([email protected])

Early-onset type 2 diabetes is associated with a particularly severe clinical phenotype, while traditional models of care may not adequately address the complex needs and lifestyles of younger people. The M3 study therefore developed a new model of care tailored to this population. However, it remains unclear how the model affects 24-hour physical behaviours, how these behaviours relate to glycaemic responses, and whether its effects differ across key high-risk groups.

Using data collected during the M3 trial and pooled data across early-onset diabetes cohorts within Leicester Diabetes Centre trials, the aims of the project are to:

• investigate 24-h physical behaviour patterns and how these change in response to pharmacological and lifestyle interventions

• explore temporal associations between accelerometer-assessed 24-h physical behaviours and continuous glucose monitor-derived glycaemic responses

• conduct sub-group analyses for key outcomes in populations of interest (e.g., women of childbearing age, ethnicity-based high-risk groups, lower socioeconomic status and deprivation)

The ACF will join an internationally recognised research group at the Diabetes Research Centre and will sit within the Lifestyle research theme of the NIHR Leicester Biomedical Research Centre. We will provide all suitable training to conduct this research project. Over the course of their fellowship, the ACF will be ideally placed and well supported in developing a future fellowship program towards a PhD in a related area.

General Practice

Designing an Equitable Primary Care Pathway for Obesity Management (MLTC)

Supervisor: Professor Samuel Seidu ([email protected])

Obesity is a major public health challenge in the UK, disproportionately affecting individuals in socioeconomically deprived communities and ethnic minority groups. Despite growing clinical need, access to effective obesity care remains uneven. This project proposes the co-design of a primary care obesity management pathway that explicitly addresses health inequalities, using a dual approach: big data analysis and local service design.

First, we will conduct large-scale data analysis using national electronic health records to identify patterns in obesity prevalence, referral rates, and treatment uptake across different demographic, ethnic, and socioeconomic groups. This will inform the identification of key inequality gaps and priority populations.

In parallel, we will collaborate with local stakeholders, GPs, public health leads, community organizations, and people living with obesity to co-develop a locally tailored care pathway. This will focus on early identification, culturally sensitive interventions, referral to weight management services, and long-term support.

The final output will be a scalable, equity-informed primary care model that integrates data-driven insights with real-world feasibility, with the potential to inform national guidelines and support targeted commissioning to reduce obesity-related disparities.

Cluster-informed care for multiple long-term conditions(MLTC): evidence synthesis and co-design

Supervisor: Dr Harini Sathanapally ([email protected])

Multiple long-term conditions (MLTC) defined as the co-existence of two or more chronic conditions in a single individual, are a growing challenge in healthcare systems worldwide, and linked to poorer outcome. Interventional research into this topic has mainly targeted a single condition within a population with MLTC, or focused on specific comorbidity pairs. Some trials have tested organisational or patient-centred models of care, but overall effects on outcomes have been limited. In parallel, epidemiological work has identified reproducible disease clusters—such as cardiometabolic and mental health–pain groupings—that are associated with higher treatment burden; however, these clusters are yet to contribute to intervention design. This project will combine a scoping review with a co-design exercise to address this gap.

The review will map and compare MLTC interventions, including condition-focused, generalised, and any cluster-focused approaches, and synthesise outcomes such as quality of life, treatment burden, and healthcare use. Building on these findings, a co-design process with patients, carers, and clinicians will explore how interventions could be tailored to common clusters of MLTC, generating a prototype model of care that reflects both evidence and lived experience. Together, this work will create a foundation for future feasibility testing of cluster-informed, patient-centred approaches to MLTC.

Improving Cardiovascular Outcomes through Precision Adherence Testing (MLTC)

Supervisors: Dr Pankaj Gupta ([email protected]) | Professor Prashanth Patel ([email protected]) | Professor Ian Squire ([email protected])

We are a world-leading research group in the biochemical assessment of medication adherence using LC-MS/MS-based Chemical Adherence Testing (CAT), based at University Hospitals of Leicester and the National Centre for Adherence Testing (NCAT). Our pioneering work is directly embedded in NHS clinical care and underpins national and international guidelines (ESC/ESH, ACC). We have published more than 40 original articles and a have an established track record of delivering clinical research.

We invite a motivated Academic Clinical Fellow (ACF) to join our well-established translational programme, focusing on cardiovascular adherence in heart failure and renal disease populations where non-adherence drives preventable risk.

The ACF will contribute to answer the following questions

Can CAT improve outcomes in chronic cardiovascular diseases such as heart failure and renal disease?
Why are patients non adherent?

The research will entail

Feasibility studies embedding CAT in specialist clinics.
Qualitative and implementation science research exploring why patients do not take prescribed treatments.
Co-designing and evaluating behavioural and system-level interventions to improve outcomes.

Our group has trained multiple clinical academics; two recent PhD students won national prizes for innovation and impact in adherence science. Fellows will benefit from strong mentorship, access to rich data, and opportunities to shape NICE-facing, practice-changing research.

General Psychiatry

A systematic/narrative review on the attitude of individuals with severe mental illness (SMI) towards weight gain

Supervisor: Dr Hari Subramaniam ([email protected])

This systematic review will synthesise qualitative evidence on the attitudes and views of SMI patients on weight gain relating to multiple factors.

Using a narrative approach, the review will examine how patients perceive, interpret, and respond to medication-related weight changes, including the perceived trade-offs between mental health stability and physical health risks. It will explore themes such as body image, stigma, quality of life, treatment adherence, and interactions with healthcare providers.

By integrating findings across qualitative studies, the review aims to provide a nuanced understanding of patient perspectives to inform more patient-centred prescribing practices and support strategies.

Description and documentation of health inequalities, physical health burdens and health co-morbidities within SMI (severely mentally ill) populations in Leicester, Leicestershire & Rutland and a comparison with available regional and national data (MLTC)

Supervisors: Dr Hari Subramaniam ([email protected]) | Dr Bharathy Kumaravel ([email protected]) | Professor Elizabeta Mukaetova Ladinska ([email protected])

Our understanding of the current cardiovascular health status and the role of multimorbidity and frailty in patients with severe mental illness (SMI) and how this relates to outcomes in this high-risk group is not known. Interventions which improve the cardiovascular health and multimorbidity issues of these SMI patients are urgently required. However, up-to-date data are needed to design and tailor interventions specifically for this group, given the challenges associated with managing CVD in SMI. 70% of these early deaths are related to poor physical health, rather than mental health problems (1,4). The presence of multimorbidity, frailty and cardiovascular disease lead to significant health burdens in people with SMI from a relatively young age and a higher service burden over the life course, thereby implying the need for a targeted and different approach in the management of physical health burdens in patients with SMI.

The project aims to quantify the prevalence of documented cardiovascular conditions, the extent of multimorbidity and the burden of frailty in people with SMI across the city of Leicester, Leicestershire and Rutland from secondary care-based Clozapine clinics and Depot antipsychotic drug administration clinic and by using primary care data registers to provide meaningful and robust estimates across LLR (Leicester, Leicestershire and Rutland) that can then be compared with available regional and national data. Documenting these health inequalities and health burdens may lead to the development of appropriate and targeted interventions in collaboration between the provider organisations to help manage and minimise such burdens and risks developing interventions that may include the possible development of a joint cardiovascular and metabolic in reach clinic to people on long term antipsychotic drugs.

MIND-MET: Implementing prophylactic GLP-1 treatment during antipsychotic initiation in acute psychiatric care

Supervisors: Professor David Webb ([email protected]) | Dr Hari Subramaniam ([email protected]) | Dr Michelle Hadjiconstantinou ([email protected])

The project directly addresses the 2026 NIHR James Lind Alliance priority on using GLP-1 medicines to prevent or manage psychiatric-medication-associated weight gain.

Understanding the pathways to implementation and scaling for integrated CKD care

Supervisors: Dr Matthew Graham-Brown ([email protected]) | Dr Rupert Major ([email protected])

We have developed a comprehensive clinical program to deliver care for patients with CKD in primary care which is has been commissioned and is being scaled across the UK.

The program is called LUCID. To complement this clinical program we have developed a staff and patient training and self-management program called My Kidneys & Me. This program takes a blended approach with in person and online staff and patient education and access to a digital self-management program. The program has been tested in a clinical trial and is being rolled out in implementation studies across the UK.

This project will support the evaluation of these studies, using relevant theories and frameworks from the field of implementation science, but supporting the evaluation of SAIL-CKD, a type 3 hybrid implementation trial of nearly 7000 patients in primary care.

General Surgery

Evaluating differences in the operating theatre learning experiences between neurotypical and neurodiverse medical students

Supervisor: Dr David Bowrey ([email protected])

Neurodiversity, particularly ADHD and ASD, is becoming more prevalent, especially following the COVID-19 pandemic. Consequently, tertiary healthcare education institutions facilitate an increasing number of neurodiverse students. Outside of scoping reviews suggesting the need for empirical research on the topic, little is known on how neurodiversity influences the learning experiences of these students. More studies are needed, particularly for students in the operating theatre which can be a challenging learning environment regardless of neurodiversity status.

This project involves the undertaking of semi-structured interviews from a purposeful sample of neurotypical and neurodiverse medical students on their surgical placements to evaluate differences in the learning experience, with an aim to improve the engagement with, and educational value of this opportunity. The ACF will join this project and develop research skills in systematic review, qualitative interviews, reflexive thematic analysis and reporting of qualitative analysis data.

The experience from this study will allow the ACF to apply for further funding evaluating the impact and influences of neurodiversity within the wider healthcare setting, including which adaptations and reasonable adjustments are required to best facilitate effective and inclusive education. This would also set the groundwork for further investigation into neurodiversity with the postgraduate training arena.

Reducing side-effects and improving long-term outcomes after breast cancer treatment through AI and intervention

Supervisors: Mr Tim Rattay ([email protected]) | Ms Monika Kaushik ([email protected])

Surgery and radiotherapy at Leicester have a track record in survivorship research and the investigation of long-term effects of treatment. Thankfully, breast cancer survival in the UK is high. Our research is designed to help breast cancer survivors achieve the best possible long-term outcomes with minimal treatment side-effects, and it is supported by the NIHR Leicester Biomedical Research Centre cancer theme, bringing together academics at the University of Leicester and clinicians from University Hospitals of Leicester (UHL) NHS Trust.

With major funding from Innovate UK and Horizon Europe, we access to large follow-up cohorts with available clinical, treatment, genomic, toxicity and survival data, and we are currently involved in a multi-national study of testing an AI application to predict side-effects from surgery and radiotherapy to inform breast cancer patients of their individual risk, with the PRE-ACT-01 randomized-controlled trial of an integrated app for lymphoedema prediction after axillary surgery and regional nodal irradiation.

The successful applicant will extend this work to identify patients at risk of breast cancer-related lymphoedema who might benefit from prophylactic lymphovascular surgery. As prophylactic procedures are unlikely to be beneficial or cost-effective for all patients, the first step is to accurately identify those at highest risk of developing lymphoedema. The ACF will review and validate prediction models for lymphoedema as part of PRE-ACT-01 and collect further data from UHL patient cohorts, to ensure the prediction model can be applied reliably to the local population. The next step will be to co-design an interventional study of lymphovascular surgery in high-risk patients at the time of their initial breast cancer surgery and prior to radiotherapy jointly with patients and stakeholders.

The ACF will have the opportunity to collaborate with other researchers from across the University, in particular the Schools of Psychology, Computer Science and Mathematics, and Biosciences. The supervisory team have an established track record of hosting ACFs, MD/PhD students, and research fellows, and full research training and support will be provided.

Utilising Patient Derived Explants from Colorectal Cancer Patient Surgical Resections to Investigate Precision Therapies

Supervisor: Mr Franscois Runau ([email protected]) | Dr Gareth Miles ([email protected])

Project: Preclinical models that can accurately predict outcomes in the clinic are much sought after in the field of cancer drug discovery and development. Existing models such as organoids and patient-derived xenografts have many advantages, but they suffer from the drawback of not contextually preserving human tumour architecture. This is a particular problem for the preclinical testing of immunotherapies, as these agents require an intact tumour human-specific microenvironment for them to be effective. PDEs involve the ex vivo culture of fragments of freshly resected human tumours that retain the histological features of original tumours. Working closely with clinicians in the Colorectal Surgery and Oncology Departments we have established a working PDE model in Colorectal Cancer.

Place: The Leicester Cancer Research Centre are globally recognised leaders in the development of PDEs in multiple cancers, including breast and endometrial – with recent publications in Nature Scientific Reports. We have a team of research scientists and eminent professors in translational research with a proven record of supervising candidates to completing PhDs and supporting them into future academic careers.

Person: We are seeking an individual who demonstrates exceptional motivation, ambition, and diligence to take a leading role in the development and application of PDEs in colorectal cancer.

Haematology

Liquid biopsy for T-cell lymphoma

Supervisor: Dr Matt Ahearne ([email protected])

Our group leverage computational tools to identify tumour specific sequences from circulating cell-free DNA. Circulating tumour DNA (ctDNA) analysis from a simple blood test enables rapid lymphoma diagnosis, molecular stratification, and real-time tracking of clonal dynamics during therapy. We have demonstrated feasibility (PMID: 32484856, 39157626) and in collaboration with Leicester Molecular Diagnostics, are advancing our assay into a validated clinical test. A new funded sub-study of HistioNode will launch in 2026 as part of the MRC Rare Disease Platform.

Alongside standard sequencing, we are adopting cutting-edge native sequencing using Nanopore technology, which offers several advantages for rapid ctDNA detection and characterisation. The ACF will assess mutational, methylation, and copy number changes in ctDNA, correlating results with clinicopathological and radiological data. This work will use samples from the UK T-cell lymphoma biobank, with planned European expansion, and from the MRC HistioNode project.

Opportunities exist to collaborate with Leicester’s Research Centre for Artificial Intelligence, Data Analytics and Modelling, applying machine learning to enhance ctDNA detection using public cancer datasets.

The research plan can be tailored to the Fellow’s interests and skills (wet and/or dry lab). Data generated will support the ACF in securing PhD funding, with the ultimate goal of integrating ctDNA assays into precision medicine lymphoma trials and routine clinical care.

Determinants of response to immunotherapeutic strategies in aggressive lymphomas

Supervisor: Dr Harriet Walter ([email protected])

Targeting of tumour antigens with T cell engagers is a recognised cancer treatment strategy in B cell malignancies. Whilst CD20xCD3 bispecific antibodies and CD19 CAR T-cell therapies have transformed clinical outcome in relapsed/refractory disease, the clinical determinants of response and optimal sequencing strategies remain unknown. Multiple studies are ongoing to assess activity in combination and in earlier treatment settings.

Additional studies are required to understand how target antigen expression affects response and how antigen loss through cell surface remodelling and/or mutations can result in resistance. Importantly, the tumour cell surface is central to interactions with the microenvironment and is thus key to diagnosis, biological understanding, and revealing new strategies for immunotherapeutic strategies.

Aligning to existing workflows and outputs from the Dyer/Walter/Ahearne laboratory, the Fellow will explore longitudinal dynamic changes in target antigen expression during treatment using multi-omic approaches. The following methodologies will be applied:

Multicolour flow cytometry
Unbiased cell surface proteomics
Imaging of the immune synapse
RNA sequencing
WES

The Fellow will also have the opportunity to leverage through acquisition and application of computational skill pre collected datasets, datasets generated through wet lab experimental studies and clinical datasets aligning with the Fellow’s specific skills, experience and interest.

Bioimpedance In Pregnancy and Labour: A fluid balance concept study

Supervisor: Professor Tommy Mousa ([email protected])

This is a prospective, proof of concept study to assess the use of BIA (Bioscan touch i8) as a simple non-invasive bed-side test during pregnancy, labour and after delivery to assess maternal hydration status and body fluid balance.

Maternal cardiovascular adaptation evolves during the course of pregnancy to accommodate the growing foetus. There is a 30% increase in global arterial compliance and stroke volume increases due to the plasma expansion and increasing total blood volume. Indirect methods have been used to assess body fluids during pregnancy, labour and postpartum period.

Bio-electrical impedance analysis (BIA) measures whole body (or regional) impedance by means of an electric current transmitted at different frequencies. New techniques allow measurement of total body water with separation into extracellular and intracellular water. Current evidence suggests that BIA may provide useful information not only in different well-established patient groups (renal dialysis, malnutrition), but also in critically ill patients with burns, trauma and sepsis undergoing fluid resuscitation.

The aim of the current project is to assess the use of BIA as a simple non-invasive bed-side test during pregnancy, labour and after delivery to assess maternal hydration status and body fluid balance. We propose to use it in women delivering by caesarean section, having severe pre-eclampsia, major postpartum haemorrhage.

Medical Oncology

Multidimensional Liquid Biopsy Profiling for Prediction and Characterisation of Resistance to Cancer Immunotherapy and Guided Combined Therapies (CTPI)

Supervisor: Dr Sam Khan ([email protected])

Background: Accurate assessment of glenoid morphology, particularly retroversion, is critical for optimal implant positioning in reverse shoulder arthroplasty (RSA). Glenoid retroversion has been associated with increased complication rates, implant loosening, and poorer functional outcomes if not properly addressed. While preoperative CT imaging is widely used, variation exists in methods for measuring retroversion, and its influence on surgical planning remains underexplored.

Aim: This study aims to quantify glenoid retroversion using standardized CT scan analysis in patients indicated for RSA in the local shoulder arthroplasty database and to evaluate the impact of varying degrees of retroversion on proposed surgical plans, including augmentation strategies and implant selection.Methods: A retrospective cross-sectional study will be conducted using preoperative shoulder CT scans from patients scheduled for RSA using the local shoulder arthroplasty database at a tertiary orthopaedic centre. Glenoid version will be measured using validated 2D and 3D reconstruction techniques. Correlation with proposed surgical plans (standard vs augmented baseplates, reaming angles, correction strategies) will be assessed through multidisciplinary surgical planning meetings.

Expected Outcomes: The study will identify thresholds of retroversion influencing surgical planning decisions, percentage of shoulder with significant retroversion and provide data to support standardised CT-based planning protocols. This will enhance preoperative decision-making and may reduce intraoperative uncertainty and improve long-term outcomes in RSA.

Impact: Results will inform future prospective studies and support the development of image-guided planning tools, aligning with NIHR ACF and ACL projects and NHS goals for improving surgical precision and patient-specific orthopaedic care.

Generating a 3D human tissue model to aid development of lung cancer treatment and prevention agents (CTPI)

Supervisor: Dr Sam Khan ([email protected])

Our group focuses on the preclinical and clinical development of cancer treatment and preventive therapies. Assessing the influence of drug interventions on the immune system in preclinical models remains challenging. Commonly used models have limitations which impact on translation to a clinical setting; Patient-derived organoids rely on cellular disassociation, which destroys the tumour microenvironment; Patient-derived xenografts are undertaken in immunocompromised mice, and replacement of the human stroma with mouse stroma is often observed which may influence drug activity and humanised mouse xenograft systems offer intact immune systems but are expensive, slow to develop and have engraftment limitations. To overcome these limitations and complement existing pre-clinical assays, we hope to culture and maintain patient tissues in short term cultures, termed patient-derived explants (PDEs). We are interested in how lung cancer treatment and prevention agents can modulate key cancer related pathways.

Understanding drivers of treatment response and resistance in patients with mesothelioma (CTPI)

Supervisors: Dr Maurice Dungey ([email protected]) | Professor Dean Fennell ([email protected])

Mesothelioma is a rare cancer associated with asbestos exposure and unfortunately prognosis is very poor. Leicester is an internationally recognised centre for Mesothelioma research. Recent large investigator-led clinical trials from our lab include: MiST 1-5, NERO, CONFIRM, VIM. We are due to open a new platform trial named SELECT Meso, a molecularly-stratified phase II trial for patients with relapsed mesothelioma. This is due to open later in 2025.

Working with bioinformaticians within our group the ACF will develop skills in analysing whole-exome and RNA sequencing, gut microbiome, spatial transcriptomics and proteomics and correlating these with clinical outcomes (treatment response, survival, toxicity).

In addition, we have access to the state-of-the-art AI volumetrics tool ARTIMES. This allows novel assessment of how the tumour develops in 3D. This can be retrospectively applied to our previous trials and used prospectively in the SELECT Meso cohort. Volumetrics combined with detailed assessment of tumour biology will give us unique perspectives into clinical response. Why do some cancers grow quicker than others?

The successful ACF would be able to work across multiple projects with a particular focus in the area they choose.

Determinants of response to immunotherapeutic strategies in aggressive lymphomas (CTPI)

Supervisor: Dr Harriet Walter ([email protected])

Multicolour flow cytometry
Unbiased cell surface proteomics
Imaging of the immune synapse
RNA sequencing
WES

Utilising Patient Derived Explants from Colorectal Cancer Patient Surgical Resections to Investigate Precision Therapies (CTPI)

Supervisor: Mr Franscois Runau ([email protected]) Dr Gareth Miles ([email protected])

Person: We are seeking an individual who demonstrates exceptional motivation, ambition, and diligence to take a leading role in the development and application of PDEs in colorectal cancer.

Beyond eGFR: Optimising cancer treatment and reducing kidney complications in onco-nephrology

Supervisors: Dr Maurice Dungey ([email protected]) | Dr Katherine Hull [email protected] | Dr Haresh Selvaskandan ([email protected])

The relationship between cancer and kidney disease is complex and remains poorly understood. People living with chronic kidney disease (CKD) are at increased risk of cancer due to a combination of factors, including the underlying disease process, immunocompromise, and exposure to immunosuppressive and cytotoxic therapies. Conversely, access to cancer treatments may be limited for individuals with CKD due to concerns regarding reduced kidney function, dialysis dependence, or the presence of autoimmune disease.

Individuals receiving treatment for cancer are at risk of acute kidney injury, which may lead to CKD or the need for acute or long-term kidney replacement therapy. Onco-nephrology aims to address the intersection between kidney disease and cancer care yet remains underrepresented in research and clinical practice. In routine care, kidney function is typically assessed using the estimated glomerular filtration rate (eGFR), derived from serum creatinine, age and sex. Important determinants of kidney function, including muscle mass, frailty and comorbidity, are not fully captured by this measure. Similarly, risks of acute kidney injury, kidney disease progression and disease relapse are not routinely incorporated into treatment decision-making.

This project will explore whether broader assessments of kidney health can improve access to cancer treatments and identify individuals at increased risk of kidney-related complications. Using a mixed-methods approach, the research will combine retrospective analysis of real-world data with qualitative evaluation of current clinical pathways and decision-making.

Renal Medicine

Identifying translational biomarkers for precision medicine in IgA nephropathy

Supervisors: Dr Chee Kay Cheung ([email protected]) | Professor Jon Barratt ([email protected])

IgA nephropathy (IgAN) is a leading cause of progressive chronic kidney disease and kidney failure worldwide. Recent advances have resulted in novel therapies targeting various steps in its pathogenesis, creating opportunities for a precision medicine approach.

This project will utilise biorepository samples from ongoing or completed Phase 2 and Phase 3 industry and academic sponsored studies, including SPARTAN, PRO-IGAN, NEFEXPLORE (led by Leicester), that investigate new treatments for IgAN.

The aims are to evaluate effects on clinical outcomes (e.g. proteinuria, kidney function), pharmacokinetics, and to identify novel biomarkers of kidney injury and response to treatment in blood, urine, and repeat kidney biopsies, using a multi-omic approach.

The ACF will gain hands-on training in clinical trial methodology and execution, and biomarker discovery utilising several laboratory and imaging techniques.

The ACF will be based in the Mayer Laboratories for IgAN, supported by a large multidisciplinary team of clinician and post-doctoral scientists.

Previous NIHR ACFs from our group have been successfully awarded personal fellowships (MRC, Wellcome Trust, KRUK) to continue their studies towards a higher degree.

This is an opportunity to gain experience in translational research and experimental medicine studies, and to develop skills to become an independent clinical investigator in renal medicine.

Using digital spatial transcriptomics to identify markers for responsiveness to treatment with novel agents for glomerular diseases

Supervisor: Dr Haresh Selvaskandan ([email protected])

The acceptance of proteinuria reduction as a clinical trial end point has resulted in several new medications being approved over the last 5-6 years for glomerular diseases.Most of the trials informing these medications had similar inclusion and exclusion criteria. While the availability of new treatments is promising, they do not work universally and there are currently no tools to allow clinicians to match individual treatments with patients most likely to respond to them.

This project will look at kidney biopsies taken from patients just before they were initiated on novel therapies, and explore differences using digital spatial transcriptomics between those who responded to treatment compared to those who did not.The project will be conducted in the Mayer IgAN laboratories, which has extensive experience with this methodology.

The project will aim to identify markers for treatment responsiveness to support precision medicine approaches in glomerular diseases.

Closing the kidney diagnosis gap: data-enabled earlier detection of glomerular and diabetic kidney disease through LUCID

Supervisors: Dr Rupert Major ([email protected]) | Professor Jon Barratt ([email protected]) | Nil Sanganee ([email protected])

Chronic kidney disease (CKD) is common in diabetes and glomerular disorders, but diagnosis is often delayed because albuminuria and haematuria are incompletely tested, interpreted and acted upon. Earlier recognition is increasingly important as disease-specific and cardiovascular-kidney-metabolic therapies can prevent kidney failure and cardiovascular events.

LUCID is Leicester's digitally enabled model linking population health management, primary care and specialist reviews and is a Health Innovation Network national programme. This project will determine how routinely collected data can identify people with possible glomerular or diabetic kidney disease earlier and support proportionate investigation.

The fellow will:

1. use retrospective primary and secondary care data to describe testing, diagnostic delay and inequalities

2. develop and internally validate a clinically interpretable electronic case-finding algorithm using laboratory, diagnostic and prescribing data

3. co-design a prototype referral or virtual-review pathway with patients and clinicians, assessing feasibility, acceptability and potential yield

The work will combine epidemiology, prediction modelling and mixed-methods implementation research. The scope will be tailored to the fellow's speciality: renal trainees may emphasise glomerular disease phenotypes, while endocrinology trainees may focus on albuminuria and atypical kidney disease in diabetes. The project will generate preliminary data, a publishable analysis and a doctoral fellowship proposal for prospective evaluation within LUCID.

Understanding the pathways to implementation and scaling for integrated CKD care

Supervisors: Dr Matthew Graham-Brown ([email protected]) | Dr Rupert Major ([email protected])

We have developed a comprehensive clinical program to deliver care for patients with CKD in primary care which is has been commissioned and is being scaled across the UK.

The use of potassium binders to facilitate guideline directed medical therapy in kidney disease and heart failure

Supervisor: Professor James Burton ([email protected])

Hyperkalaemia is common in patients admitted to hospital with heart failure and chronic kidney disease and is associated with adverse outcomes. It frequently leads clinicians to reduce or discontinue guideline-directed medical therapies, including renin–angiotensin–aldosterone system inhibitors and mineralocorticoid receptor antagonists. Although these treatments improve cardiovascular and kidney outcomes, their use is limited by the risk of recurrent hyperkalaemia. Newer potassium binders offer a potential strategy to control serum potassium and enable patients to start, continue or optimise beneficial therapy, but evidence for their use during and after hospital admission remains limited.

This project will evaluate the management of hyperkalaemia in hospitalised patients and investigate how potassium binders could support safe optimisation of guideline-directed therapy. It will characterise current clinical pathways, prescribing decisions, biochemical monitoring, treatment persistence, readmissions and cardiovascular and kidney outcomes. The work will build on an existing industry-funded study of potassium-binder use in hospital, providing access to an established clinical programme, expertise and opportunities for collaborative research.

By integrating renal medicine, heart failure, clinical pharmacology and therapeutics, the fellowship will generate evidence to inform patient selection, prescribing and monitoring. It will also provide training in clinical research, pharmacoepidemiology and industry partnership, supporting development of a definitive interventional study.

Understanding the clinical utility of regular symptom screening using Patient Reported Outcome Measures (PROMs) in the dialysis population

Supervisor: Professor James Burton ([email protected])

Dialysis patients have an incredibly high symptom burden, reporting at least 6 and as many as 20 different symptoms. These symptoms are intrusive and affect life participation, as well as being associated with increased rates of depression, hospital admission and mortality. The SONG-HD study (Standard Outcomes in Nephrology) clearly identified symptom management as of critical importance to patients, caregivers, clinical staff and commissioners of care, but despite this, incorporation of tools that assess the range and impact of symptoms is not routine.

The reasons behind this are multifaceted. Using itch as an example; even though as many as 40% of dialysis patient report moderate to severe itch, with a significant impact on life, 17% of patients do not report this symptom to anyone and nephrologists estimate the number to be <5%. Working with an industry funded PhD student on the incorporation of patient reported outcome measures (PROMs) into routine care in commercial dialysis centres, this project will assess:

1. The routine use of PROMs (including electronic PROMs) to assess symptom burden and their acceptability to patients and staff

2. Ways to ensure the clinical information collected is easily available to the clinical decision maker for review

3. Ongoing use of PROMs to assess response to treatment and evolving symptom burden

4. The relevance of symptom clusters and optimum treatment for multiple symptoms

PROM-HD: Embedding Symptom-Based Assessment in Haemodialysis Care

Supervisor: Professor James Burton ([email protected])

People receiving dialysis experience intrusive symptoms that affect activities, emotional wellbeing, treatment engagement, hospitalisation and survival. Despite their importance to patients, dialysis reviews remain dominated by biochemical and process measures. Symptoms may therefore be overlooked, under-reported or managed inconsistently.

This project will contribute to an NIHR Programme Development Grant investigating whether dialysis care can move towards symptom-based evaluation and management. Working with patients, caregivers and multidisciplinary teams, the ACF will examine the feasibility and acceptability of incorporating patient-reported outcome measures, including electronic PROMs, into routine care.

The project will address the following objectives:

1. Establish methods and frequency of symptom-data collection.

2. Determine how results can be displayed and made available to clinical decision-makers during consultations.

3. Explore how identified symptoms trigger assessment, treatment or referral, and how repeated PROMs can measure response.

4. Investigate the relevance of symptom clusters and approaches to managing multiple concurrent symptoms.

5. Identify barriers to implementation, including workload, digital exclusion and health inequalities.

Using mixed qualitative and quantitative methods, the project will generate evidence to refine the intervention, care pathway and implementation strategy. Findings will provide feasibility outcomes and patient-informed intervention components for evaluation within a subsequent NIHR programme grant application across dialysis settings.

Improving Cardiovascular Outcomes through Precision Adherence Testing

Supervisors: Dr Pankaj Gupta ([email protected]) | Professor Prashanth Patel ([email protected]) | Professor Ian Squire ([email protected])

The ACF will contribute to answer the following questions

Can CAT improve outcomes in chronic cardiovascular diseases such as heart failure and renal disease?
Why are patients non adherent?

The research will entail

Feasibility studies embedding CAT in specialist clinics.
Qualitative and implementation science research exploring why patients do not take prescribed treatments.
Co-designing and evaluating behavioural and system-level interventions to improve outcomes.

Beyond eGFR: Optimising cancer treatment and reducing kidney complications in onco-nephrology

Supervisors: Dr Katherine Hull ([email protected]) | Dr Maurice Dungey ([email protected]) | Dr Haresh Selvaskandan ([email protected])

Exploring Women's Health in Chronic Kidney Disease: Impact, Detection and Lived Experience

Supervisors: Dr Katherine Hull ([email protected]) | Professor James Burton ([email protected])

Chronic kidney disease (CKD) is a global public health concern and is the only major non-communicable disease associated with a continuing rise in age-adjusted mortality. People living with CKD experience a high symptom burden, polypharmacy, reduced quality of life, substantial multi-morbidity, and frequent healthcare utilisation. Many women are living with CKD worldwide. Although the burden is greatest among women aged 50 years and older, prevalence is increasing among women of reproductive age.

Chronic kidney disease has wide-ranging implications for women's health, including increased cardiovascular risk, infertility and adverse pregnancy outcomes.In some women, reproductive or pregnancy-related complications may represent the first opportunity for CKD detection. The interactions between CKD, reproductive health, perimenopause and menopause remain poorly understood and underrepresented in research. This project will use a mixed methods approach to explore the impact, detection and progression of CKD in women.

Areas of interest include infertility, perimenopausal and menopausal health, opportunities for CKD detection during routine healthcare encounters, and women's experiences of reproductive, maternity and kidney care services.

Obstetrics and Gynaecology

Personalising uterine cancer management

Supervisor: Dr Esther Moss ([email protected])

Uterine cancer is the most common gynaecological malignancy in the UK and despite the majority of patients being diagnosed at an early stage, mortality rates are rising. There is a need to develop more personalised treatments with the aim of improving patient outcomes.

Patient derived explants are a preclinical tool that preserve the tumour and immune microenvironment and enable tumour responses to drug therapy, including chemotherapy, immunotherapy and novel drugs, to be investigated. the explants enable pathways and mechanisms of action to be explored increasing our understanding of uterine cancers.

Bioimpedance In Pregnancy and Labour: A fluid balance concept study

Supervisor: Professor Tommy Mousa ([email protected])

Preventing Gestational Diabetes Through Early Pregnancy Dietary Intervention: A Mechanistic Study

Supervisor: Dr Claire Meek ([email protected])

• How does body fat change during pregnancy in women at high risk of GDM?

• How do body fat and metabolism influence blood glucose levels during pregnancy?

• How do women experience dietary interventions, and what helps or hinders adherence?

• Key activities:

(1) systematic review of body composition and metabolic adaptation in pregnancy.

(2) analyses of DODGE trial data, related to body composition, dietary and physical activity.

(3) a qualitative interview study exploring women's experiences of dietary interventions.

Novel technology for diabetes in pregnancy: Continuous Ketone Monitoring (CKM) in the DOMINO Cohort

Supervisor: Dr Claire Meek ([email protected])

Methods: CKM will be embedded in the DOMINO study, a multicentre prospective cohort evaluating continuous ketone monitoring (CKM) in pregnant women with type 1 diabetes.

The project will address key questions:

• What is the existing evidence linking maternal ketone exposure with perinatal outcomes?

• What factors influence ketone production in pregnancy?

• How acceptable is continuous ketone monitoring to women with type 1 diabetes?

Activities and skills developed:

(1) A systematic review and meta-analysis of maternal ketone exposure and pregnancy outcomes.

(2) Longitudinal analyses of CKM, continuous glucose monitoring (CGM), dietary, physical activity and insulin-delivery data from the DOMINO cohort.

(3) A qualitative interview study exploring women's experiences and views of CKM.

Paediatrics

Asthma diagnosis and deep phenotyping in children with preschool wheeze

Supervisors: Dr Erol Gaillard ([email protected]) | Professor Dominic Shaw ([email protected])

The problem:

Severe wheezing attacks are one of the commonest reasons for emergency department attendance and hospitalisation in children younger than 5 years. This is a significant health care burden in the UK and worldwide. Our current strategies of management of preschool wheezing disorders are ineffective. Better diagnosis and understanding of the pathophysiology of preschool asthma to develop more effective treatments is an important unmet need.

Unmet need: Diagnosis and biomarkersA key problem is the lack of a diagnostic test because young children are rarely able to perform spirometry. Breath volatile organic compounds can be obtained non-invasively and portable oscillometry are both promising new technology in preschool children. Oscillometry measures airway resistance and impedance and an increase in both parameters is associated with asthma. The test is quick, non-invasive and importantly does not require any effort on the part of the child.

Additionally, further phenotyping is required to establish the best way to treat preschool children. Many do not respond to corticosteroids. Objective biomarkers and the assessment of treatable traits including allergic sensitisation, and an assessment of airway infections are needed.

Research plan: Observational study recruiting children with acute preschool wheeze from children’s ED or in the outpatient clinic, obtain breath samples and oscillometry measurements pre and post bronchodilator and phenotype severe preschool wheeze on the basis of nasal swab and blood biomarkers and study of airway infection to pave the way for a clinical trial.

The ACF will also be expected to complete a systematic review.

Prospective analysis of extent of worry in parents and carers attending emergency care settings about their child.

Supervisor: Professor Damian Roland ([email protected])

While the incidence of serious illness in children is very low; emergency care attendances continue to climb and this creates a challenge to recognise those children in need of ongoing treatment.

Serious case review often demonstrates that parents and carers have raised concerns about their child prior to being discharged from emergency care settings. This concern is reported to be either dismissed or ignored by health care professionals.

Research previously undertaken at the Leicester Royal Infirmary Children’s Emergency Department has demonstrated that 10% of those children with the lowest risk of illness on arrival are thought to be the most unwell the parent has ever seen that child. This may partly explain why health care professionals are perceived to, or do actually, dismiss parental concern.

In this work the ACF will undertake a prospective evaluation of parental concern at arrival in the Children’s Emergency Department and for seven days afterwards. The aim to understand how concerns changes over time and if a more precise lexicology can be development when parents and carers communicate with health care professionals.

Congenital diaphragmatic hernia

Supervisor: Dr David Lo ([email protected])

Congenital diaphragmatic hernia (CDH) is a life-threatening congenital anomaly, with an incidence of approximately 1:2,500 live births. Mortality rate remains around 40–50% and in follow-up studies, multiple complications including pulmonary damage, cardiovascular disease, gastro-intestinal disease, failure to thrive, neurocognitive defects and musculoskeletal abnormalities have been described.

Despite this, there is no consensus on how these children should be monitored long-term. Previous follow up studies have also been based on small case series’ and there is limited longitudinal data beyond the first 3-5 years of life.

Objectives:

To describe the current follow-up arrangements for CDH in UK tertiary paediatric centres
To explore long term outcomes relating to CDH in children using a large primary care database linked to hospital data

Methods:

Survey study of UK tertiary centres
Epidemiological study using routinely collected health data

Rationale:

Identify whether there are differences/inequalities in the way children with CDH are managed in the UK.
Describe long-term prognosis of children with CDH from birth to early adulthood
The above information will be utilised to inform the development of consensus guidance for the follow-up of children with CDH

Exploring Weather Events Affecting The Health and Emergency intensive care admissions of children using Routine data: the WEATHER study

Supervisor: Dr Sarah Seaton ([email protected])

Please note we can offer alternative research projects that fit within our research agenda. Background: Climate change and air pollution pose a significant global challenge, disproportionately affecting the health and lives of children.1 Despite lifelong exposure, little is known about how weather impacts children, even though air pollution, which is closely linked with weather, harms every organ in the body.

Each year there are ~18,000 admissions to paediatric intensive care units (PICU) in the UK. Many of the children admitted to PICU have multiple lifelong conditions. Every admission to PICU for over 20 years has been collected by the Paediatric Intensive Care Audit Network (PICANet: SS is co-PI of PICANet).2

This data can be linked with weather and pollution information from The Met Office. Admissions to PICU have a strong seasonal variation with higher rates of emergency respiratory admissions in winter, leading to severe capacity issues within the NHS. Despite this, there has been limited research exploring the impact of weather and pollution on children admitted to PICU.2, 3

Aim: To explore the association between weather events on emergency admissions to PICU Research questions: (1) Has there has been a changing impact of (a) weather and (b) air pollution on the rate and severity of illness in children admitted to PICU and their outcomes over time? (2) What are the projections of future PICU need under different scenarios of future climate change?

Patient and parent experience of connective tissue disorder, vascular healthcare and their research priorities

Supervisors: Professor Thanos Saratzis ([email protected]) | Dr Dimitrios Vlastos ([email protected]) | Dr Tom Withers ([email protected])

Heritable connective tissue disorders (CTD) are a group of diseases that that affect connective tissue and a significant proportion of them result in poor vascular health. There is no known cure, they are lifelong and limiting. In the paediatric population the main vascular pathology this group present with are aneurysms and aortic dissections which if they require surgery are major operations with a high mortality rate. It is possible for CTD patients to reduce the probability of needing vascular surgery and the risk of surgery by living a healthy life in a healthy environment and maintaining good blood pressure control by health living and medication adherence. Currently healthy living and blood pressure control interventions in vascular patients focus on older adults and are not appropriate for the paediatric population.

This aims of this project will be:

To establish patient and parent research priorities in paediatric vascular disease.
To summarise the patient and parent experience of paediatric CTD care.

Semi-structured interviews will be undertaken with two groups: paediatric CTD patients and their parents. Interviews will be stopped when data saturation has been reached, approximately 10 per group. The data will be analysed thematically.

Palliative Medicine

Understanding the clinical utility of regular symptom screening using Patient Reported Outcome Measures (PROMs) in the dialysis population

Supervisor: Professor James Burton ([email protected])

The SONG-HD study (Standard Outcomes in Nephrology) clearly identified symptom management as of critical importance to patients, caregivers, clinical staff and commissioners of care, but despite this, incorporation of tools that assess the range and impact of symptoms is not routine. The reasons behind this are multifaceted. Using itch as an example; even though as many as 40% of dialysis patient report moderate to severe itch, with a significant impact on life, 17% of patients do not report this symptom to anyone and nephrologists estimate the number to be <5%.

Working with an industry funded PhD student on the incorporation of patient reported outcome measures (PROMs) into routine care in commercial dialysis centres, this project will assess:

The routine use of PROMs (including electronic PROMs) to assess symptom burden and their acceptability to patients and staff
Ways to ensure the clinical information collected is easily available to the clinical decision maker for review
Ongoing use of PROMs to assess response to treatment and evolving symptom burden
The relevance of symptom clusters and optimum treatment for multiple symptoms

A Machine Learning Approach to Chronic Pain: From Data Imputation to Genetic Discovery

Supervisor: Dr Richard Packer ([email protected])

This academic post offers a unique opportunity for a clinician to tackle a major global health challenge: chronic pain. With current therapies often having substantial side effects and problematic addictive properties, there is an urgent need to better understand the underlying causes of this significant morbidity burden.

This project will build on our established expertise in using electronic healthcare records from large cohort studies to conduct powerful genetic research. We are now moving to advance the field in two key areas: first, we will use machine learning and AI to impute missing data, thereby increasing case numbers and statistical power for genetic discovery. Second, we will leverage your clinical training and our cutting-edge methods to develop clinically meaningful phenotypes that distinguish between impactful, resolving, and persistent pain.

By using these refined phenotypes to conduct genetic studies on large datasets, we will seek to uncover novel genetic factors that contribute to the development of chronic pain. This work will provide critical insights, ultimately offering a clear translational pathway to new therapies and improved patient care.

Plastic Surgery

Reducing side-effects and improving long-term outcomes after breast cancer treatment through AI and intervention

Supervisors: Mr Tim Rattay ([email protected]) | Ms Monika Kaushik ([email protected])

Public Health

Estimating health effects of environmental hazards, including climate change, air pollution and transport noise

Supervisor: Professor Anna Hansell ([email protected])

Environmental factors such as climate change, air pollution and environmental noise have important impacts on health at population level and in individual patients. However, there remain many gaps in the evidence base including how these hazards impact on clinical care, both individually and combined. The University of Leicester is internationally recognised for its research into environmental health impacts, through its Centre for Environmental Health and Sustainability (CEHS), which hosts the National Institute of Health Research (NIHR) Health Protection Research Unit in Chemical Threats and Hazards. CEHS also leads the Environment Theme in the Leicester Biomedical Research Centre.

The ACF would join a multidisciplinary team of environmental health experts to conduct epidemiological analyses using national (e.g. UK Biobank) and local (e.g. University Hospitals of Leicester admissions, EXCEED cohort) data. They would receive bespoke training in biostatics, healthcare data analysis, geographical information systems and environmental exposure assessment, and develop policy implications of their work linking with the HPRU and UKHSA; also with local government including through our existing partnerships with Leicestershire Country Council, Leicester City Council and Northwest Leicestershire Council.

Investigating the effects of green space on health in Leicester, Leicestershire and Rutland

Supervisors: Dr Catherine John ([email protected]) | Dr Bharathy Kumaravel ([email protected])

Research shows that the environment plays a critical role in health. Air pollution, noise, and extreme temperatures can have major negative effects. However, exposure to green space (such as parks, gardens and countryside) is linked to reduced mortality[1] and improved health, through mechanisms including stress reduction, physical activity and social cohesion[2,3]. A recent local citizens’ assembly identified green space as a key research priority, with potential to inform public health and disease prevention policy.

EXCEED is a Leicester-based longitudinal cohort study with individual-level environmental data and linked health outcomes from primary and secondary care.

In this project, you will:

Conduct a literature review on green space and health;
Analyse associations between green space metrics and health outcomes in Leicester, Leicestershire and Rutland using EXCEED and other resources;
Explore variation in these associations by age, sex, ethnicity, and deprivation.

The project can be tailored to your interests and skills. You will gain expertise in quantitative data management and analysis, supported by a multi-disciplinary team spanning public health, statistics, and epidemiology.

You will have opportunities for involvement in participant and public involvement and engagement.You will be encouraged to develop a fellowship proposal for further research on this or other epidemiological questions.

Equity in population genomics: understanding the role of social and genetic diversity in precision prevention

Supervisors: Dr Richard Packer ([email protected]) | Dr Catherine John ([email protected])

Background Large-scale genomic studies such as UK Biobank and All Of Us are transforming our understanding of disease mechanisms and risk. The government’s 10 Year Plan envisages routine use of genomic risk prediction throughout the NHS by 2035.

However, benefits may not be equitably distributed. Individuals from non-European ancestry groups are underrepresented in many genomic studies, and genetic risk interacts with social, behavioural and environmental factors. Consequently, the accuracy, interpretation and implementation of genomic risk prediction may differ between populations and settings.

Understanding these issues is essential to ensure that genomic medicine addresses, rather than widens, health inequalities. Aim To investigate how genetic susceptibility to respiratory disease interacts with modifiable risk factors across diverse populations, and to assess the implications for equitable implementation, governance and public health impact of genomic risk prediction.

Objectives

1. Model interaction effects of genetic risk and selected social/environmental factors on lung function, across ancestry groups.

2. Evaluate how underrepresentation may influence interaction analyses.

3. Examine the resulting clinical, public health and policy implications for genomic risk prediction and population health interventions.

This project will provide training in epidemiology, genomics, data management and programming, as well as public health policy and public engagement in research.

Designing an Equitable Primary Care Pathway for Obesity Management

Supervisor: Professor Samuel Seidu ([email protected])

Estimating the genetic prevalence and carrier frequency of autosomal recessive diseases in the UK

Supervisors: Dr Mahmoud Fassad ([email protected]) | Professor Pradeep Vasudevan ([email protected]) | Mr Mervyn Thomas ([email protected])

About 300 million people live with rare diseases worldwide, imposing a global burden and regarded as an emerging public health priority. To date, there are over 7000 types of rare diseases. 80% of rare diseases are due to genetic causes and the majority of them follow autosomal recessive inheritance.

Understanding the incidence/prevalence of rare diseases help to appreciate their public health impact. Subsequently, this will support therapeutic development, public health policy and allocating resources for research and clinical practice. Moreover, estimating carrier frequency would support genetic counselling and empower families to take informed decisions about their reproductive options.

UK biobank is the world’s most comprehensive dataset of biological, health and lifestyle information. It contains genomic data of 500,000 participants. We aim to apply population genetics tools based on Hardy-Weinberg theorem along with both frequentist and Bayesian statistics to calculate genotypes frequency of autosomal recessive diseases; supporting more robust estimation of genetic prevalence and carrier frequency of recessive diseases in the UK.

There are several databases of reported human variations and their classifications based on their pathogenicity and causing diseases e.g. ClinVar, LOVD and HGMD. Unfortunately, the majority of the reported variants are considered of unknown clinical significance imposing a challenge to interpretation of genomic data. We aim to develop gene-specific models for variant classification based on the disease mechanism, observed allele frequency of known pathogenic variants and in silico pathogenicity prediction tools. Estimating the allele frequency of the known and predicted pathogenic variants will be used as an input into the Hardy-Weinberg equation to calculate carrier frequency and genetic prevalence of recessive diseases.

Findings will inform genetic counselling, reproductive decision-making, and public health policy, while also guiding future therapeutic and screening initiatives. The project is supported by strong in-house expertise in statistical genetics and access to UK Biobank resources.

Cluster-informed care for multiple long-term conditions(MLTC): evidence synthesis and co-design

Supervisor: Dr Harini Sathanapally ([email protected])

Screening, precision medicine and enhanced management pathways for people affected by vascular disease

Supervisors: Professor Matt Bown ([email protected]) | Professor Thanos Saratzis ([email protected])

The University of Leicester Vascular Surgery Group has a broad portfolio of research across all aspects of vascular surgery and cardiovascular risk management, including screening. Successful candidates will be able to choose research projects aligned to the following themes:

Cardiovascular risk: Supported by a large NIHR funding award, in this project we will adapt and develop a cardiovascular risk management toolkit for people with vascular disease. Working with clinicians, health psychologists, economists and others we will create a person-centred risk management intervention that can be rolled out across the NHS.

Precision medicine: We have specific expertise in genetic studies of abdominal aortic aneurysm and are now using the results of this work to see if giving people personalised genetic risk scores can be used to improve the uptake of screening programmes, and/or potentially be used to extend screening programmes to women who currently don’t get offered screening.

Clinical management: Inpatient research is based around reducing the risks of surgery. This ranges from research into new blood tests to make sure people are on the right medicines, using alternative contrast agents intra-operatively and testing new surgical devices, in a continuing cycle of improving perioperative care for people with vascular diseases.

Description and documentation of health inequalities, physical health burdens and health co-morbidities within SMI (severely mentally ill) populations in Leicester, Leicestershire & Rutland and a comparison with available regional and national data.

Supervisors: Dr Hari Subramaniam ([email protected]) | Dr Bharathy Kumaravel ([email protected]) | Professor Elizabeta Mukaetova Ladinska ([email protected])

Enhancing Early Detection of Glomerular Disease through Integrated Care: A LUCID+ Study

Supervisors: Dr Rupert Major ([email protected]) | Professor Jon Barratt ([email protected])

Background: Glomerular disease is a leading cause of chronic kidney disease (CKD) and end-stage kidney failure, yet diagnosis is often delayed. The NHS Long Term Plan emphasise early detection and personalised prevention. LUCID (Leicester, Leicestershire and Rutland CKD Integrated Care Delivery) integrates kidney care across primary and secondary services. The advent of novel therapies for glomerular disease in the last five years has made early detection an imperative. Expanding LUCID to focus on earlier identification of glomerular disease has the potential to improve outcomes and reduce inequities.

Aims:To develop and evaluate integrated care pathway for earlier detection of glomerular disease supported by novel data-driven tools.

Objectives:

Map current diagnostic pathways for proteinuria and haematuria in primary care.
Develop and test a data tool within existing clinical systems to flag patients at risk of glomerular disease.
Assess the impact on case detection using retrospective and prospective data.

Methods:

Mixed-methods approach:

Electronic care data retrospective analysis to identify missed opportunities
Co-design of an electronic risk flagging tool for LUCID

Impact:This project will inform a new LUCID pathway for glomerular disease, supporting earlier diagnosis, slowing progression, and aligning with national priorities for integrated, preventative care.

Understanding the pathways to implementation and scaling for integrated CKD care

Supervisors: Dr Matthew Graham-Brown ([email protected]) | Dr Rupert Major ([email protected])

We have developed a comprehensive clinical program to deliver care for patients with CKD in primary care which is has been commissioned and is being scaled across the UK.

Trauma and Orthopaedics

Development of Phage Therapy for the Treatment of Prosthetic Joint Infections

Supervisor: Dr Melissa Haines ([email protected])

Prosthetic Joint Infections (PJIs) are costly to the NHS – approximately £36,000 per infection, and they are difficult-to-treat in the long-term. A new collaboration between the University Hospitals of Leicester Orthopaedics Department and the Leicester Centre for Phage Research aims to support the development of promising alternative treatment options.

Bacteriophages (phages) are a potential alternative treatment for infections caused by bacteria. The clinical use of phages to treat infections is known as phage therapy. Phages are currently being explored globally and the demand for phage therapy is increasing, in countries such as Australia, Belgium, France, Georgia, Poland and the USA.

This project aims to bridge the gap between laboratory research/compassionate use and use within the NHS. The Leicester Centre for Phage Centre has successfully built clinical collections for urinary tract infections, COPD, and C. diff infection. This project will involve building a collection of clinical bacterial strains taken from PJIs, laboratory experiments to find and assess the phages for effective killing of the PJIs from clinical isolate collection, and analysis of implant-associated biofilm breakdown. The resultant phage collection will have the potential to be used clinically.

Artificial intelligence prediction of clinically important stiffness following elbow fracture: development and external validation of a risk-stratification model.

Supervisor: Mr Harvinder Singh ([email protected])

Background and Rationale Post-traumatic elbow stiffness is a common and potentially disabling complication following elbow fracture. Loss of elbow movement affects activities of daily living, work and quality of life, and may lead to prolonged rehabilitation or further surgery. Current approaches to identifying patients at high risk are largely based on injury pattern and clinical judgement, with limited ability to provide an individualised prediction of outcome. An artificial intelligence (AI)-enabled prediction model integrating patient, injury, treatment and early recovery characteristics could identify patients at greatest risk of clinically important elbow stiffness.

Early identification could enable targeted rehabilitation and closer follow-up, while avoiding unnecessary intervention in patients likely to recover normally. Research Question Can an AI-based prediction model accurately identify patients at high risk of clinically important elbow stiffness following elbow fracture?

Objectives To develop an AI/machine-learning model predicting clinically important elbow stiffness after elbow fracture. To identify the clinical, radiological and treatment factors associated with poor recovery. To externally validate the prediction model in a separate patient cohort. To assess whether the model could support risk-stratified rehabilitation and future interventional trials.

Study Design Prospective observational cohort study, preceded by retrospective model development using routinely collected clinical and imaging data. Population Adults (≥18 years) presenting with an acute elbow fracture, including distal humerus, proximal ulna/olecranon and radial head fractures, with or without associated dislocation.

Exclusion: previous major elbow dysfunction, pathological fracture, neurological injury preventing assessment, or inability to complete outcome assessment. Imaging Standardised radiographs and, where clinically indicated, CT scans. AI-based image analysis will explore fracture morphology, displacement and other imaging characteristics associated with stiffness.

Primary Outcome Clinically important elbow stiffness at 4 months, defined using a pre-specified patient-centred functional threshold and elbow range-of-motion criteria. Analysis A machine-learning prediction model will be developed using the retrospective dataset and internally validated using bootstrapping/cross-validation.

Model performance will be assessed using: discrimination (area under the ROC curve), calibration, sensitivity and specificity, positive and negative predictive values and decision-curve analysis. The model will then undergo external temporal/geographical validation using prospectively recruited patients from participating centres. Model interpretability will be incorporated to identify clinically meaningful predictors rather than treating the AI model as a "black box".

Predicting poor recovery after shoulder trauma: development and external validation of a personalised risk-stratification model.

Supervisor: Mr Harvinder Singh ([email protected])

Background and Rationale Shoulder trauma is common and encompasses proximal humerus fractures, shoulder dislocation, fracture-dislocation and other significant injuries. Although most patients improve with appropriate conservative or surgical management and rehabilitation, a substantial proportion develop persistent pain, stiffness, weakness and functional limitation. Current treatment pathways generally use injury characteristics to guide management but have limited ability to identify, at an early stage, which individual patients are likely to experience poor recovery.

NIHR-funded research has demonstrated the importance of avoiding unnecessary treatment and optimising rehabilitation following musculoskeletal trauma. However, routine interventions may not benefit all patients equally. A clinically useful prediction model could identify patients at high risk of poor recovery early after injury, enabling targeted rehabilitation and closer follow-up while allowing low-risk patients to follow less intensive pathways.

Research Question Can patient, injury, imaging and early recovery characteristics be combined to accurately predict poor functional recovery following shoulder trauma? Aim To develop and externally validate a prediction model that identifies patients at risk of persistent pain, disability and failure to return to normal function following shoulder trauma.

Objectives Identify clinical, demographic, injury, imaging and early recovery factors associated with poor outcome. Develop and internally validate a prediction model for poor recovery. Externally validate the model in a prospective multicentre cohort. Determine whether the model could support risk-stratified rehabilitation and future interventional trials.

Study Design A prospective observational cohort study, preceded by retrospective model development using routinely collected clinical and imaging data. Population Adults presenting with significant shoulder trauma, including: proximal humerus fractures; shoulder dislocation; fracture-dislocation; and selected other significant shoulder injuries.

Patients with pre-existing severe shoulder dysfunction, pathological fractures or inability to complete outcome assessment will be excluded.

Attention-Guided Multi-View Deep Learning Model for Ankle Fracture Detection and localization in Large-Scale UK Radiograph Data (D)

Supervisor: Mr Jitendra Mangwani ([email protected])

Gastroentology

FACILITATE-ENDO: Developing and evaluating a competency framework for in-situ endoscopy simulation facilitators

Supervisor: Dr Farhad Peerally ([email protected])

In-situ simulation represents a powerful approach for enhancing patient safety and developing individual and team competencies in endoscopy units. However, the absence of standardised competencies and structured training for simulation facilitators poses significant challenges to the effectiveness, quality assurance, and scalability of these educational interventions.

Our research group brings substantial expertise in translational patient safety research, such as the SCALE-ENDO study, which translates real-world safety incidents into in-situ simulation scenarios. Through this work, we have identified facilitator development as pivotal for translating simulation-based research into measurable gains in patient safety and training.

This ACF project will develop and evaluate a comprehensive competency framework for endoscopy simulation facilitators. Under the team’s supervision and alongside national collaborators, the project will be guided to develop a project which may include (depending on the interest and availability of the ACF):

Systematic review of existing simulation faculty frameworks
Video analysis of recorded expert facilitation using qualitative methods (e.g. conversational analysis)
Delphi consensus methodology with stakeholders
Development and evaluation of training materials

The ACF will join an established research team with strong connections to national endoscopy training academies and the British Society of Gastroenterology. Hosted within SAPPHIRE (Social science, APPlied Healthcare and Improvement Research), the appointee will be supported in developing their simulation facilitation and relevant research skills.

Clinical Education Research

SMILE: Supporting Medical Interactions through Learning-Enhanced digital communication

Supervisor: Professor Jeremy Howick ([email protected])

Problem: One in 10 patient safety incidents is caused by poor communication, Within the NHS, this problem is intensified by two trends:

AI and other technology are increasingly used to help communicate with patients.
In the UK, and in particular in the plural city of Leicester, the growing number of patients without English as their first language, necessitates the use of translators.

Yet, research on (1) how to optimize the use of AI for communication (2) how to express empathy via translators, is underdeveloped.

Methods: This fellowship will focus on one of the abovementioned gaps. The project will begin with a systematic review to map the evidence base and highlight potential interventions. This will be followed by qualitative research exploring the experiences of patients, clinicians, and other stakeholders. Finally, findings will inform an implementation study, such as a pilot trial, to test real-world solutions.

Patient safety for final year medical students: Healthcare Teams Observations for Patients Safety (HTOPS)

Supervisors: Professor Elizabeth Anderson ([email protected]) | Mr Leyshon Griffiths ([email protected])

Context: Our translational research was supported in 2017 with a Wellcome Trust grant, to explore aviation’s approach to in-situ observations for safe practice. We designed an app for learning in-practice.1 We have shown that the app supports observational learning to prepare medical students for safe practice (PhD dissertation submission December 2025). Our literature review identified that tools to support patient safety learning in practice, are rare.2 With the current emphasis of safety in the NHS, Leicester medical school has a national solution, using HTOPS, to better prepare Resident Doctors for safe practice.

Pedagogics Research Project: You will train final year medical students to use the app and measure the impact on their learning while assessing the impact on practice.

Methodology: Mixed methods, using surveys and focus groups of participating students and clinical-educators

Outputs: This will offer an ACF the opportunity to:

Integrate HTOPS into final year preparation for practice: Learning about curriculum integration and innovation for patient safety and gain teaching experience.

Conduct Research: Supported by experts in the medical school who have published in this area

Disseminate the findings: The work is timely, will result in conference outputs and an academic paper. The outcomes will be required by other schools leading to a package for transferability. The GMC are likely to be very interested in the outputs of this project.

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Projects

Projects by topic

Clinical Radiology

Cerebrovascular reactivity assessed using fMRI and transcranial Doppler ultrasound in acute intracerebral haemorrhage (ICH) - multimodal integration for post ICH cerebrovascular assessment

Weight loss interventions for the reversal of stage B heart failure in people living with multiple long-term conditions

Attention-Guided Multi-View Deep Learning Model for Ankle Fracture Detection and localization in Large-Scale UK Radiograph Data

Characterising the heterogeneity of Tuberculosis

Endocrinology and Diabetes

A systematic review of target trial emulations for SGLT2 inhibitors: robustness of methods and estimated clinical outcomes

A systematic review and meta-analysis of group-based and self-management education interventions for type 2 diabetes

Preventing Gestational Diabetes Through Early Pregnancy Dietary Intervention: A Mechanistic Study

Novel technology for diabetes in pregnancy: Continuous Ketone Monitoring (CKM) in the DOMINO Cohort

MIND-MET: Implementing prophylactic GLP-1 treatment during antipsychotic initiation in acute psychiatric care

Weight loss interventions for the reversal of stage B heart failure in people living with multiple long-term conditions

Protecting skeletal muscle during pharmacological weight loss: the role of protein supplementation

Towards precision obesity medicine: examining heterogeneity in treatment response to pharmacological and lifestyle weight management interventions

A whole-person approach to tailored weight management in adults with type 1 diabetes and obesity

Real-world effectiveness of medications in early-onset type 2 diabetes

Understanding perceptions of wearable technologies and associations with psychosocial outcomes in early-onset type 2 diabetes

24-h physical behaviours and glycaemic outcomes in early-onset type 2 diabetes

General Practice

Designing an Equitable Primary Care Pathway for Obesity Management (MLTC)

Cluster-informed care for multiple long-term conditions(MLTC): evidence synthesis and co-design

Improving Cardiovascular Outcomes through Precision Adherence Testing (MLTC)

General Psychiatry

A systematic/narrative review on the attitude of individuals with severe mental illness (SMI) towards weight gain

Description and documentation of health inequalities, physical health burdens and health co-morbidities within SMI (severely mentally ill) populations in Leicester, Leicestershire & Rutland and a comparison with available regional and national data (MLTC)

MIND-MET: Implementing prophylactic GLP-1 treatment during antipsychotic initiation in acute psychiatric care

Understanding the pathways to implementation and scaling for integrated CKD care

General Surgery

Evaluating differences in the operating theatre learning experiences between neurotypical and neurodiverse medical students