Skip to main navigation Skip to search Skip to main content

RESILIENCE (Retrospective Linkage Study of Autoimmune Encephalitis): protocol for an Australian retrospective cohort study of outcomes in autoimmune encephalitis using data linkage techniques

  • Amy Jean Halliday
  • , Katrina Lambert
  • , Christine Bundell
  • , Andrew McLean-Tooke
  • , David Gillis
  • , Kerri M. Prain
  • , Greg Bryson
  • , Lisa Gillinder
  • , David Brown
  • , Sudarshini Ramanathan
  • , Russell Dale
  • , Fabienne Brilot
  • , Nerissa Jordan
  • , Nicholas Lawn
  • , Alan Lai
  • , James Boyd
  • , Ximena Camacho
  • , Wendyl D'Souza
  • , Australian Adult Comprehensive Epilepsy Centres Consortium

Research output: Contribution to journalArticleOtherpeer-review

Abstract

Introduction The autoimmune encephalitides (AE) are a heterogeneous group of neurological disorders with significant morbidity and healthcare costs. Despite advancements in understanding their pathophysiology, uncertainties persist regarding long-term prognosis and optimal management. This study aims to address these gaps, focusing on immunotherapeutic strategies, neoplastic associations and functional outcomes. Methods and analysis The Retrospective Linkage Study of Autoimmune Encephalitis project will use data linkage techniques to establish a retrospective 10-year population cohort of Australian patients with AE. Two cohorts will be analysed, the Reference Cohort (clinically confirmed AE cases obtained from hospital medical records, n=145) and the Operationally Defined Cohort (AE cases identified through administrative coding data, n≈5000). Univariate statistical methods will identify candidate coding elements for use in the operational case definition and multivariate models and evaluation methods used to identify and internally validate the optimal coding algorithms. The two study cohorts will be analysed separately due to the high likelihood of overlap. Primary outcomes include relapse rate, prevalence and control of epilepsy, cognitive disability, poor educational attainment, delayed tumour diagnosis and mortality. Statistical analyses, including random mixed-effects regression models, will assess treatment effects, covariates and outcomes. Ethics and dissemination This project has been approved by the leading investigators' institutional Human Research Ethics Committee (HREC), the St Vincent's Hospital Melbourne HREC, as well as the Australian Institute of Health and Welfare HREC and relevant jurisdictional HRECs where required. The dissemination of findings through peer-reviewed publications and patient advocacy channels will maximise the impact of this research.

Original languageEnglish
Article numbere084664
Number of pages10
JournalBMJ Open
Volume14
Issue number12
DOIs
Publication statusPublished - Dec 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • EPIDEMIOLOGY
  • IMMUNOLOGY
  • Neurology

Cite this