Using phenomenology and semiology to support the differential diagnosis of transient loss of consciousness
Year: 2025
Type: dissertation
Study design: Observational Study
Abstract: BACKGROUND: Transient loss of consciousness (TLOC) is a common acute presentation; over 90% are due to either syncope, epilepsy, or functional/dissociative seizures (FDS). Differential diagnosis is challenging. Better clinical criteria to support differential diagnosis – including clinical decision aids (CDAs) – could improve outcomes. OBJECTIVES: This thesis aims to: (1) review barriers to accurate TLOC diagnosis; (2) provide external validation of candidate diagnostic criteria; and (3) develop a CDA for TLOC diagnosis. METHODS: Methods include: (1) narrative review; (2) ethical analysis; (3) thematic analysis of semi-structured interviews with 20 first-presentation TLOC patients; (4) retrospective cohort video study of 189 videos from 50 patients with epilepsy or FDS; (5) retrospective cohort diagnostic accuracy study of 300 patients with syncope, epilepsy, or FDS; and (5) prospective cohort diagnostic accuracy study of 178 first TLOC patients. RESULTS: Experiences of initial TLOC assessment: First TLOC can be a disorienting ‘biographical disruption’. Communication supports interim self-management. Individual diagnostic features: FDS are more likely than epilepsy to show peri-ictal social responsiveness in video review. This is externally validated as predicting FDS in first-presentation TLOC, as are fluctuating course or waxing/waning movements, asynchronous limb movements, younger age at onset, and total non-ictal and peri-ictal symptoms. Other diagnostic features derived from chronic patient cohorts are not validated in first presentations. CDA development: A machine learning classifier trained on 36 patient/witness questionnaire responses in the chronic syncope/epilepsy/FDS cohort classified 86.0% of patients correctly. Validation accuracy was worse (75.8%) in the first-presentation TLOC cohort. A classifier trained on first-presentation data identified 9 optimal patient-reported predictors. It correctly identified 80.8% of diagnoses, non-significantly superior to initial clinician assessment (70.5%, p=0.192). Patients reported the CDA accessible and acceptable to use. CONCLUSIONS: CDAs could improve outcomes for patients who experience TLOC. Future research needs to be conducted within the first presentation setting to ensure validity.
Author: Wardrope, Alistair Wardrope
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7015892880