A Randomized Trial Comparing AI-Assisted Intraoperative Complication Detection Versus Standard Visual Monitoring During Manual Small Incision Cataract Surgery

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Published: 2026-01-30
DOI: https://doi.org/10.61919/f1d7r829
Keywords:
Artificial Intelligence; Cataract Extraction; Computer Vision Systems; Corneal Endothelium; Intraoperative Complications; Manual Small Incision Cataract Surgery

Main Article Content

Samia Mustafa
Optometrist & Clinical Researcher, Dow Institute of Medical Technology, Dow University of Health Sciences, Karachi, Pakistan
Amina Aman
Low Vision Consultant, Almaktoom School, Islamabad, Pakistan
Muhammad Sulaman Khan Niazi
Medical Officer, Syed Muhammad Hussain Government General and TB Hospital Samli, Murree, Pakistan
Fatima Nasar
Resident Surgeon Ophthalmology, Allied Hospital, Faisalabad, Pakistan
Muhammad Zia Iqbal
Professor Anatomy & Ophthalmologist, Suliman Alrajhi University, AlBukayriah, Saudi Arabia
Shariq Faisal
Postgraduate Student, DeMontfort University, Leicester, United Kingdom

Abstract

Background: Manual small incision cataract surgery is widely used in high-volume ophthalmic practice, but intraoperative complications and tissue manipulation can influence postoperative recovery. Real-time computer-vision systems may supplement conventional surgeon monitoring. Objective: To compare AI-assisted intraoperative monitoring with standard visual monitoring during manual small incision cataract surgery. Methods: This single-center parallel-group randomized controlled trial enrolled 96 adults undergoing elective surgery in Southern Punjab between March and July 2025. Participants were allocated 1:1 to AI-assisted monitoring or standard visual monitoring. Ninety-two participants had 4-week follow-up data. Outcomes included surgical duration, intraoperative complications, best-corrected visual acuity (BCVA), endothelial cell density loss, and central corneal thickness change. Results: Surgical duration was shorter with AI-assisted monitoring (14.2±2.1 vs 17.8±2.9 min; mean difference −3.60 min, 95% CI −4.63 to −2.57; p<0.001). Complications occurred in 3/46 (6.5%) versus 8/46 (17.4%) participants (RR 0.38, 95% CI 0.11-1.33; p=0.108). At 4 weeks, BCVA was better (0.18±0.08 vs 0.28±0.11 LogMAR), endothelial cell loss was lower (184.5±42.1 vs 278.3±56.4 cells/mm²), and CCT increase was smaller (12.4±3.8 vs 24.8±6.2 μm) in the AI-assisted group (all p<0.001). Conclusion: AI-assisted monitoring was associated with shorter surgery and more favorable early visual and corneal outcomes, while a statistically significant reduction in complication incidence was not demonstrated

Article Details

Issue

Vol. 4 No. 2 (2026)

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Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Samia Mustafa et al. 2026. A Randomized Trial Comparing AI-Assisted Intraoperative Complication Detection Versus Standard Visual Monitoring During Manual Small Incision Cataract Surgery. Journal of Health, Wellness and Community Research. 4, 2 (Jan. 2026), 1–10. DOI:https://doi.org/10.61919/f1d7r829.

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