Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 11:11 PM
Ignite Modification Date:
2025-12-24 @ 11:11 PM
NCT ID:
NCT03631069
Brief Summary:
This retrospective case control explores the retinal features of dementia associated with neurodegenerative diseases, particularly Alzheimer's disease. By linking a pseudonymised dataset of three-dimensional retinal scans, called optical coherence tomography, with nationally held data on dementia, corresponding characteristics will be evaluated through descriptive statistics and machine learning techniques.
Detailed Description:
By 2025, it is estimated that approximately 1 million people in the United Kingdom (UK) will suffer from dementia, a syndrome associated with progressive decline in brain function. While there is currently no cure for most types of dementia, early diagnosis can help patients receive the appropriate treatment and support to help maintain mental function.
The focus of this project is to identify changes in retinal structure associated with dementia. In collaboration with bioinformatics experts at University College London (UCL), the investigators propose to analyse our repository of \>1 million retinal scans, termed optical coherence tomography (OCT), performed regularly on patients since 2008. OCT scans will be linked at a patient level to data from the Hospital Episode Statistics (HES) database to identify those who have been diagnosed with dementia or went on the develop dementia. Thus, a pseudonymised classified dataset of retinal scans will be generated for qualitative and quantitative analysis. The primary objective is to characterise changes in the layers of the retina associated with dementia. Machine learning techniques may also be employed to identify novel patterns of retinal change associated with dementia.
Study:
NCT03631069
Study Brief:
Protocol Section:
NCT03631069