A Clinical Decision Aid for Diagnosing Transient Loss of Consciousness
NCT05367999 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 186
Last updated 2024-01-03
Summary
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.
Conditions
- Consciousness Disorder
Interventions
- DIAGNOSTIC_TEST
-
initial Paroxysmal Event Profile
The initial Paroxysmal Event Profile (iPEP) was derived from the paroxysmal event profile (PEP) and paroxysmal event observer (PEO) to provide a diagnostic tool aiming to differentiate between the most common underlying reasons for TLOC presentations: syncope, epilepsy, and dissociative seizures. The iPEP is a 35-item questionnaire developed from the PEP and PEO.5,25 The 5-point frequency scales used in response to each symptom in the PEP and PEO have been replaced with a binary 'present'/'not present' classification in recognition of the fact that the target patient group may have experienced only one or a few episodes of TLOC.
Sponsors & Collaborators
-
Sheffield Teaching Hospitals NHS Foundation Trust
lead OTHER
Principal Investigators
-
Markus Reuber · Honorary Consultant Neurologist
-
Alistair Wardrope · Specialty Registrar in Neurology
Eligibility
- Min Age
- 16 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2022-02-09
- Primary Completion
- 2023-06-30
- Completion
- 2023-06-30
Countries
- United Kingdom
Study Locations
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