Doctor Kirsty Fletton is a Medical Scientist working at the Observational and Pragmatic Research Institute (OPRI). She is primarily involved with the work with ISAR, the International Severe Asthma Registry, with a focus on high risk asthma. She has a passion for research in respiratory medicine and strives to support advancement in patient care through ISAR projects and collaboration with leading global experts in asthma. She graduated from the University of Liverpool with an MBChB and prior to her role as medical scientist obtained experience in clinical medicine working in the NHS for 5 years, with a subsequent 3 years in the private sector.
Spotlight: Luke Daines
Luke’s current research seeks to improve the accuracy with which a diagnosis of asthma can be made in clinical practice. He was awarded a Chief Scientist Office Clinical Academic Fellowship (2017) for “deriving and validating a clinical prediction rule for the diagnosis of asthma in primary care”.
His latest study aimed to derive and validate a prediction model to support primary care clinicians assess the probability of an asthma diagnosis in children and young people, aged under 25 years old. The derivation dataset was created from the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to electronic health records (n=11,972 participants). The prediction model was derived using logistic regression. External validation was conducted using electronic health records from the Optimum Patient Care Research Database (OPCRD; n=2670 participants). Discrimination in the external validation dataset was good (c-statistic 0.85, 95% CI 0.83–0.88) but calibration was poor (calibration slope 1.22, 95% CI 1.09–1.35) which may be because some predictors were infrequently coded in health records.
See further:
@ljdaines on Twitter
Systematic Review of Previous Models
Patient Views of Diagnosis Tools
Spotlight: Arif Budiarto
Arif Budiarto is a dedicated PhD student in the field of Medical Informatics at the prestigious University of Edinburgh. With a passion for AI in healthcare, Arif’s current research focuses on developing a machine learning model that aids clinicians in predicting patients at high risk of asthma attacks. By harnessing the power of AI and leveraging the abundant healthcare data available, Arif aims to contribute to the advancement of personalized and effective healthcare services. Through their work, Arif strives to make a positive impact in the field of medical informatics and improve patient outcomes.
Spotlight: Amy Chan
Amy is a senior clinical academic pharmacist at the School of Pharmacy, University of Auckland, and working clinically in primary care. She also holds an honorary post at the Centre of Behavioural Medicine, University College London. Amy has specific research interests in digital health interventions and using big data to explore relationships between different risk factors and health outcomes. Amy has nearly 15 years’ experience in the public health service, where she led the clinical pharmacy service. She also provides consultancy to charities, medical research organisations, and non-government organisations. Amy is currently the global lead for workforce transformation with the International Pharmaceutical Federation (FIP), and the Commonwealth Pharmacists’ Association (CPA) Research Lead. Amy is a member of the global Respiratory Effectiveness Group (REG), Open Digital Health and leads a workstream for ERS CONNECT Clinical Research Collaboration – Moving multiple digital innovations towards connected respiratory care: addressing the over-arching challenges of whole systems implementation.
Spotlight: Laura Bonnett
Laura is a Medical Statistician primarily interested in the development and validation of clinical prediction models for people with recurrent conditions such as epilepsy and asthma. She is based in the Department of Health Data Science at the University of Liverpool. Laura’s work has informed the Driving and Vehicle Licensing Agency’s regulations on time off driving for people with a first-ever seizure, and driving during and after anti-seizure medication withdrawal. This work has now also underpinned European Union policy on driving. Laura is a Chartered Statistician and a committed STEM (Science, Technology, Engineering & Mathematics) Ambassador. As part of these roles, she has developed statistical outreach activities which can be used by anyone with an interest in the area at a variety of events such as careers fairs, science festivals and STEM clubs (www.rss.org.uk/hands-on).
Spotlight: Holly Tibble
For those of you who haven’t yet met me, hello! I am a Chancellor’s Fellow at the University of Edinburgh, working on improving methods for risk prediction modelling (primarily in asthma) and developing pathways for integration into primary care practice. Prior to Edinburgh, I worked at the University of Melbourne in mental health care, health in the justice system, and medico-legal complaints (quite a bizarre hodge-podge, but such is ECR research funding!) My background is as a statistician, but my passion is getting actionable insights from data. My motivation for starting this network was so that we can find mutually-beneficial routes to improving our research and getting closer to widespread patient benefit.
Welcome to RespiRisk!
RespiRisk is an online hub for the respiratory risk prediction modeling community in the UK. I hope that this space will allow us to collaborate, to share papers and results, and to promote relevant events and resources.
The hub started in 2023 in the form of a quarterly email blast, but by relocating here it is my hope that it will be easier to access updates and resources.
Thank you for being here!
Holly Tibble
