Prediction of Postoperative Visual Acuity in Cataract Patients Using a Macular Optical Coherence Tomography-based Deep Learning Method
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Data Collecting
- Sponsor
- Second Affiliated Hospital, School of Medicine, Zhejiang University
- Enrollment
- 1100
- Locations
- 1
- Primary Endpoint
- Uncorrected distance visual acuity
- Status
- Not yet recruiting
- Last Updated
- 4 years ago
Overview
Brief Summary
The purpose of this study is to collect the macular OCT images and preoperative and postoperative visual acuity of cataract patients who had been operated in the eye center of the Second Affiliated Hospital of Zhejiang University Medical College, and to train a model that can relatively accurately predict the postoperative visual acuity of patients by deep learing.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Senile cataract patients, with or without macular disease, the impact of cataract on vision has affected the daily life of patients.
Exclusion Criteria
- •Glasses can obviously improve eyesight
- •In addition to macular disease, combined with other eye diseases that seriously affect vision, resulting in no significant improvement in postoperative vision
- •Complicated cataract surgery due to trauma and other reasons
- •Combined with other eye diseases not suitable for intraocular lens implantation
- •Patients with systemic diseases who cannot tolerate surgery
Outcomes
Primary Outcomes
Uncorrected distance visual acuity
Time Frame: 1 month postoperatively
The UCVA was measured by the same optometrist at each visit
Best Corrected Visual Acuity
Time Frame: 1 month postoperatively
The BCVA was measured by the same optometrist at each visit
Macular optical coherence tomography
Time Frame: 1 month postoperatively
Macular oct was measured by the same doctor at each visit