Award Title: Development of a clinical decision aid for the differential diagnosis of transient loss of consciousness
Funder: Department of Health and Social Care

Abstract: BACKGROUND: Transient loss of consciousness (TLOC) – defined as spontaneous disruption of consciousness not due to head trauma and with complete recovery – has a lifetime prevalence of 50%. It is one of the commonest neurological complaints in primary and emergency care. Over 90% of TLOC is due to either syncope, epilepsy or dissociative seizures (DS, also known as  Psychogenic Nonepileptic Seizures ). The rapid and accurate distinction of these diagnoses is vital to allow appropriate further management but at least 20-30% of patients are not managed optimally or misdiagnosed. We have previously demonstrated that, in patients with established diagnoses of epilepsy, syncope, or DS, an automated classifier using only information from 36 questions based on patient experience and lay witness reports (the initial Paroxysmal Event Profile, iPEP) could accurately diagnose 86.0% of patients (with 100% sensitivity and 91.7% specificity for syncope)  AIMS: To calibrate the iPEP for discrimination between syncope, epilepsy, and DS in patients newly presenting with TLOC, validate its performance in an independent sample, and to explore acceptability of the use of such a tool to people with TLOC and witnesses.  METHODS: Nested qualitative-quantitative prospective single-centre development and validation of the iPEP in patients presenting to Emergency Departments, syncope or epilepsy clinics with first presentations of TLOC, with semi-structured interviews conducted with a purposive sample of participants from the quantitative study. The iPEP will be calibrated using a previously-described procedure for variable selection and training of Random Forest (RF) classifiers, and validated with assessment of overall classification accuracy, alongside sensitivity, specificity, positive and negative predictive values, and area under receiver-operating curve for each of the three target diagnoses. Performance will be evaluated against a benchmark set by results from previous research in patients with established diagnoses of epilepsy, syncope, and DS.  OUTPUTS: Results will be submitted for publication in academic and professional literature. If performance from feasibility can be replicated in validation, the iPEP will be suitable to begin process of registration as a medical device for implementation in clinical pathways to minimise inappropriate referrals and treatment, streamline patient pathways, and enable earlier ordering of appropriate investigations to ensure prompt and appropriate diagnosis and management. If pilot performance could be replicated in this population and proportional savings from current estimated costs of misdiagnosis achieved, this could potentially save £63.9 million of annual UK healthcare expenditure.

Lay Abstract: Background  Transient loss of consciousness is a medical term for  blackouts . This means sudden loss of awareness or self-control without obvious cause (like head injury). Blackouts are a very common problem in Emergency Departments (EDs). Some causes are not dangerous, others need urgent treatment.  There are three main causes.    Syncope (fainting): caused by a brief drop in blood supply to the brain.  Epileptic seizures (fits): due to too much electrical activity in the brain.  Dissociative seizures: automatic (uncontrolled) responses to difficult emotions, thoughts, sensations, or situations.   It can be hard to work out which explains a person s blackouts. About 3/10 people with blackouts currently get the wrong tests or diagnosis. This can be dangerous. People who faint may need to see a cardiologist (doctor specialising in the heart). Those who have seizures should see a neurologist (specialist in the brain).  Aims  We want to help people get the right diagnosis and treatment sooner.  We previously made a list of 134 questions for people with blackouts and witnesses to their attacks. These questions helped to tell the difference between the three main causes. We chose the most important questions and used them to create a computer programme to predict the cause of a person s blackouts. The computer programme was almost perfect at deciding who had fainted, and who had a seizure.  We now need to find out if the programme can do this when people first seek medical help.  Methods  We will ask people who go to the ED with a blackout to answer our questions. We will also ask people who have been referred to specialists for faints or seizures.  We will use 100 people's answers to train the programme to predict the right diagnosis. We will test its predictions on 150 people. Experts will agree the correct diagnosis for these people. We will compare the experts  diagnosis with that predicted by the programme.  We also want to know what people who have blackouts think of the programme. We will ask 30 people about their experience and use their answers to improve it.  PPI  We have designed this research with people who experience blackouts, to ensure it is useful for them.  Epilepsy Action, STARS, and FND Action all support people who experience blackouts. They have helped with design and will remain involved through a Research User Group.  Dissemination  When finished, we will have tested whether our programme predicts the cause of blackouts when people first seek medical help. Before using the programme we would carry out another study in several centres to test if it helps people get the right tests and treatments sooner. We will share our results in academic papers, through patient organisations, and on social media.

Research Activity Codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health Categories: NEUROLOGICAL