Sheffield Children's Hospital projects

Projects:

Phenotypic characterisation and association with immune dysfunction in children with a raised total IgE presenting to a tertiary paediatric service

Main Supervisor

Dr Eleanor Minshall (eleanor.minshall@nhs.net)

Second Supervisor

Dr Fiona Shackley (fiona.shackley@nhs.net)

Other Supervisors

Professor Cork

Aim and Objectives

This study aims to identify the sub group of children with atopic dermatitis and riased IgE to review whether chidlren who meet the criteria for immune fuction screening have had an immune evaluation and to look at this cohorts response to available ezcema treatments Validated scoring systems have been developed to identify individuals likely to have an immune defects associated with hyper IGE however there is limited data on the utilisation of current HIE or DOCK 8 scoring systems in a non selected UK paediatric population with a raised total Ig E > 1000. We propose a retrospective survey to review this
2. New biologic treatments such as dupilumab are now recognised to improve eczema and reduced IgE . As part of a retrospective case note review process we would hope to identify which children have responded well to specifically to specific biologic treatment and whether an elavated igE might identify a a subset of children children in our current cohort who might benefit from biologic treatment

Objectives : A retrospective case note review is planned identifying Chidlren with an IGE level > 1000 Ku/l who have presented to our dermatology or allergy clinics over a 10 year period
 

Research Methodology

Report for IgE levels > 1000 Ku/L in Children aged between 0 -18 years at the time of blood sampling will be obtained form the Immunolgoy laboratory at Sheffield teaching hospitals

Case notes will be reviewed to assess clinical phenotype including atopic disease, infection risk, immunological assessment and severity and systemic treatment of their excema

A data collection tool will be developed by the student with support from the supervising consultants including data routinely collected on the HIHR_ HIE score

Pharmacy records will be reviewed to collect data on systemic treatment used to manage eczema

Patients who are identified as being at potential risk of of an immune defect will have a further clinical review organised and investigations as indicated

Expected Outcome

Develop guidance to identify chidlren who merit further immune or genetic investigations
Validate the use of the HIE and DOK8 scoring systems in our paediatric population
Idnetify any children who might merit furtehr immune function or genetic investigation who have not had this done already
Identify where a Raised IgE may be a marker for suitability for dupliumab use in severe atopic eczema

Type of Project

Clinical project - based in the clinical environment with patients/including service evaluation

Additional Training

Ability to attend paediatric allergy immunolgoy and dermatology clinics
Trianing in Skin prick testing and managment of food allergies
Managment of atopic eczema and use of scoring systems

AI to measure distal radius fracture displacement and development of software algorithm

Main Supervisor

Mr Sanjeev Madan (s.madan@sheffield.ac.uk)

Second Supervisor

Professor Reza Saatchi (r.saatchi@shu.ac.uk)

Aim and Objectives

1. Primary objective is to measure displacement and angulation of distal radius fractures and develop AI tool to measure it and validate it.
2. Secondary objective is to use the AI method developed to measure deformity in bones using similar method and develop a software programme.

Research Methodology

We will retrospectively look at 500 anonymised distal radius fractures in Antero-Posterior (AP) and lateral view. We will measure the displacement and angulation using PACs as ground truth (GT).
We will put four points on distal radius fragment and four points on proximal radius fragment as reference points and use these to develop machine learning algorithm for AI to measure displacement and angulation in both AP and lateral views.

Expected Outcome

We will validate this tool with GT as gold standard and measure its accuracy using statistical methods. Our aim is to make an AI tool that is accurate, easy to use to measure displacement. Future aim will be to develop an app for measuring deformities of limb bones and segments and also mechanical axis alignment of whole body.
There has been significant recent interest in AI to detect and measure fractures.
Deep Learning (DL) and AI has been used to measure deformity and classify fractures.

Type of Project

Lab/Bench Project - primarily working in a lab environment

Additional Training

Students will be allowed to come to operation theatre and scrub, assist and learn basic surgical skills. They will attend clinics to learn examination skills and attend ward rounds. They will have access to weekly Friday morning departmental teaching for 3.5 hours comprising Orthopaedic and radiology MDT, Pre-operative and post-operative case discussions of all elective and trauma cases treated weekly in the department, and complex case discussions. They will have access to Research and Innovation department of Sheffield Children's Hospital and will get help from sheffield Hallam University for statistics and technical aspects of the project.

A digital application to support sick day management in type 1 diabetes

Main Supervisor

Dr Neil Wright (neil.wright1@nhs.net)

Second Supervisor

Dr Elspeth Ferguson (elspethferguson@nhs.net)

Other Supervisors

Dr Astha Soni

Aim and Objectives

Primary objectives: To demonstrate that using the app in sick-day scenarios results in correct insulin doses being calculated.

Secondary objectives: To demonstrate that using the app improved confidence in managing sick days. Secondly to determine how acceptable using the app is to our participants and thirdly to gain qualitative views on managing sick-days amongst young people with T1DM and their parents.

Research Methodology

We plan to recruit two groups of participants (one group of adolescents with type 1 diabetes and one group of parents/guardians of younger children with diabetes), from our diabetes clinics at Sheffield children's hospital to our study. This will be a randomised cross-over trial with participants completing questions on hypothetical scenarios relating to sick-day management on two separate occasions. On one occasion traditional methods will be used for support and on the other occasion the app will be used for support.

The student will be expected to recruit participants from clinic and conduct the sessions where participants will complete the questionnaires. The student will also complete a number of qualitative interviews in a small subset of participants exploring their views around managing sick days. Support will be given where required in qualitative interviewing techniques.

Following data collection the student will analyse the data and present the findings in their thesis. It is hoped the findings from this study, if demonstrating the app is accurate and acceptable, will lead to a larger study with real world use of the app.

Expected Outcome

The project is expected to provide evidence as to whether the app is safe and effective. If this is found to be the case it is hoped this will lead to a larger study with real world use of the app.

Type of Project

Clinical project - based in the clinical environment with patients/including service evaluation

Additional Training

Students will be supported in learning qualitative research methods required for the structured interviews. Support will be given for statistical analysis if required but statistical methods are likely to fall within the remit of the statistical course.

Identifying factors associated with azithromycin resistance in nasal microbiome in children.

Main Supervisor

Dr Kelechi Ugonna (k.ugonna@nhs.net)

Second Supervisor

Dr Fiona Shackley (fiona.shackley@nhs.net)

Other Supervisors

Dr Simon Hardman

Aim and Objectives

The primary objective will be to identify what the level of azithromycin resistance in nasal flora of children without respiratory co-morbidity and compare it with the level we have already observed in children with protracted bacterial bronchitis
The secondary objective will be to identify demographic features, prescribing patterns (in both primary and secondary care), and clinical factors in both groups that may be associated with azithromycin resistance.

Research Methodology

The student will prospectively recruit 20 children without respiratory co-morbidity between the ages of 1 and 7 years old. They will perform a single nasal swab and they will analyse this swab for microbiology and antimicrobial resistance. This will be compared to similar data already obtained for patients who have a diagnosis of bacterial bronchitis.
The student will then undertake a study to identify detailed clinical and prescribing history in both patient groups to see if there are any factors that are related to increased azithromycin resistance in these study groups.

Expected Outcome

Our research group has already identified that patients with bacterial bronchitis (even those who have not been treated with Azithromycin) have a really high rate of resistance to this antibiotic.
We would like to identify whether this rate is higher than the background rate of our population and we would further like to identify whether there are any clinical, demographic and prescribing factors that are associated with this resistance.

Type of Project

Clinical project - based in the clinical environment with patients/including service evaluation

Additional Training

This will be a clinical project involving recruiting children and performing nasal swabs. The student will also benefit from being shown how to analyse nasal swabs for microbiology and also antibiotic resistance.
In addition, the student will be able to attend and sit in on paediatric respiratory clinics for their experience.