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A Big Data-based Cohort Study for Cataract Patients

Sponsor
Sun Yat-sen University (Other)
Overall Status
Recruiting
CT.gov ID
NCT05491798
Collaborator
(none)
1,000
Enrollment
1
Location
30
Anticipated Duration (Months)
33.3
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

Cataract is an important cause of blindness and visual impairment worldwide. At present, the only effective treatment method is surgery. The visual function of most patients can be significantly improved after surgery, but there are still 5-20% of patients whose visual function cannot be improved after surgery. Previous studies have found that the surgical complications and postoperative visual function of cataract patients are closely related to the condition of the fundus, but the current fundus camera cannot perform clear fundus imaging of cataract patients, and the existing potential visual inspections, such as retinal visual inspection, are also inaccurate. Predict postoperative visual acuity. Therefore, there is an urgent need for a reliable postoperative effect prediction system for cataract patients to provide reference for both ophthalmologists and patients.

This study intends to collect patient medical record information and traditional/ultra-wide fundus photos and other multi-modal data. Firstly, this study will use artificial intelligence technology to enhance fundus photos of cataract patients to obtain clearer fundus photos. Then this study will use both medical record information and traditional/ultra-wide fundus photographs to predict postoperative vision and visual function of cataract patients.

Condition or Disease Intervention/Treatment Phase

    Study Design

    Study Type:
    Observational [Patient Registry]
    Anticipated Enrollment :
    1000 participants
    Observational Model:
    Cohort
    Time Perspective:
    Prospective
    Official Title:
    A Big Data-based Cohort Study for Cataract Patients
    Actual Study Start Date :
    Jul 1, 2020
    Anticipated Primary Completion Date :
    Dec 31, 2022
    Anticipated Study Completion Date :
    Dec 31, 2022

    Outcome Measures

    Primary Outcome Measures

    1. Change of best corrected visual acuity [Baseline and 1 week after surgery]

      Change of best corrected visual acuity from baseline to 1 week after surgery

    2. Accuracy for detection of retinal disorders [1 week after surgery]

      Accuracy for detection of retinal disorders using enhanced fundus images

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years and Older
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    No
    Inclusion Criteria:
    • Candidates for cataract surgery (phacoemulsification and intraocular lens implantation) within a week.
    Exclusion Criteria:
    • Unwilling or unable to receive fundus photography

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Zhognshan Ophthalmic Center, Sun Yat-sen University Guangzhou Guangdong China 510060

    Sponsors and Collaborators

    • Sun Yat-sen University

    Investigators

    • Principal Investigator: Haotian Lin, M.D., Ph.D., Zhongshan Ophthalmic Center, Sun Yat-sen University

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Haotian Lin, Clinical Professor, Sun Yat-sen University
    ClinicalTrials.gov Identifier:
    NCT05491798
    Other Study ID Numbers:
    • CCPMOH2021-China-1
    First Posted:
    Aug 8, 2022
    Last Update Posted:
    Aug 8, 2022
    Last Verified:
    Aug 1, 2022
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Haotian Lin, Clinical Professor, Sun Yat-sen University
    Cataract
    Postoperative prediction
    Image enhancement
    Retina disorder
    Additional relevant MeSH terms:
    Cataract
    Retinal Diseases

    Study Results

    No Results Posted as of Aug 8, 2022