Keratoconus Clinical Trial
— REDCAKEOfficial title:
Retrospective Digital Computer Analysis of Keratoconus Evolution - REDCAKE
Verified date | November 2020 |
Source | University Hospital, Antwerp |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The purpose of this study is to create a database of keratoconic eyes with two or more corneal topographies/tomographies, at least 5 months apart
Status | Completed |
Enrollment | 972 |
Est. completion date | December 31, 2018 |
Est. primary completion date | December 31, 2018 |
Accepts healthy volunteers | |
Gender | All |
Age group | 12 Years to 40 Years |
Eligibility | Inclusion Criteria: - Age between 12-40 years. - Clinically diagnosed mild or moderate keratoconus in one or both eyes - Two or more Scheimpflug measurements (type Pentacam HR, Pentacam AXL, Ziemer Galilei, CSO Sirius) of good technical quality, separated at least five months apart. Exclusion Criteria: - Corneal scarring present in both eyes. - Known corneal or retinal pathologies, apart from keratoconus - Known ocular procedures/ treatments (including crosslinking) - Known systemic diseases (e.g. diabetes, MS, HIV/AIDS, hypertension,…), except allergies - Change in contact lenses between measurements (e.g. start wearing lenses, change from corneal to scleral lenses, etc.) - Fluorescein drops instilled into the eye before Scheimpflug measurement. |
Country | Name | City | State |
---|---|---|---|
Belgium | Antwerp University Hospital | Edegem |
Lead Sponsor | Collaborator |
---|---|
University Hospital, Antwerp | European Vision Institute Clinical Research Network |
Belgium,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | To obtain a database, containing at least two valid corneal Scheimpflug measurements recorded at least 5 months apart, of 1500 keratoconus patients. | These data will be used to create a personalized three-dimensional model of the cornea at each time point, which permits classifying corneas according to shape and stage, as well as assessing the influence of patient age, gender, family history and ophthalmic habits (e.g. eye rubbing) on keratoconus progression. Based on corneal changes over time, an estimate of the underlying biomechanical changes will be made. | 5 months | |
Primary | To develop software to automatically detect keratoconus and estimate the keratoconus progression speed | The data from Outcome 1 will be combined to develop software for automated keratoconus detection and progression risk assessment to help ophthalmologists decide when to perform cross-linking on their patients. | 18 months | |
Secondary | To improve the predictive model for keratoconus progression speed so it can work using only one single measurement | Once a predictive model for keratoconus progression speed based on multiple measurements, this can be improved to make predictions based on a single measurement. | 18 months |
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