Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE

Launched by SECOND AFFILIATED HOSPITAL OF NANCHANG UNIVERSITY · Jan 3, 2024

Keywords

ClinConnect Summary

This clinical trial is studying the use of advanced computer technology, known as a deep convolutional neural network (CNN), to predict potential complications during and after a specific eye surgery called Small Incision Lenticule Extraction (SMILE). The goal is to see how well this technology can help doctors identify issues that might arise during the procedure or affect recovery. The trial is currently looking for participants aged 18 and older who have certain vision problems, specifically myopia (nearsightedness), and meet other health guidelines.

To be eligible, participants should have a specific level of vision correction needs and must not have had any other eye surgeries or certain eye conditions. Those who join the study can expect to undergo assessments related to their eye health and may contribute to improving future surgical outcomes for others. It's important to know that the trial is focused on gathering data at multiple centers, which means participants might be involved in a larger research effort to enhance the safety and effectiveness of SMILE surgery.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • A condition in which the spherical equivalent refractive error of an eye is ≤-0.50 D when ocular accommodation is relaxed;
• • Age ≥18 years;
• • Spherical equivalent (SE) ≥-10.0D;
• • Corrected distance visual acuity (CDVA) ≥16/20;
• • Stable myopia for at least 2 years;
• • No contact lenses wearing for at least 2 weeks.
• Exclusion Criteria:
• • The presence or history of eye conditions other than myopia and astigmatism, such as keratoconus or external eye injury;
• • A history of eye surgery;
• • The presence or history of systemic diseases.