OCT-PRO Model vs. Clinicians: Cataract Surgery Outcome Prediction

Official title

A Randomized Controlled Trial Comparing the Accuracy of the Postoperative Vision Prediction Model for Cataract Surgery (OCT-PRO) With Clinicians' Predictions of Surgical Outcomes

Overview

Cataract is the leading cause of blindness worldwide, yet 5-20% of patients fail to achieve satisfactory visual recovery after surgery. Current methods for predicting postoperative visual acuity lack accuracy, particularly in patients with co-morbid fundus diseases. The OCT-PRO model, developed by our team, uses artificial intelligence (AI) to integrate optical coherence tomography (OCT) images and clinical data to forecast surgical outcomes. This multi-center, randomized, single-blind trial aims to compare the predictive accuracy of OCT-PRO-assisted predictions versus standard clinician predictions. A total of 534 participants will be randomized 1:1 to either the experimental group (OCT-PRO-assisted prediction) or the control group (routine care). The primary outcome is the mean absolute error (MAE) between predicted and actual postoperative best-corrected visual acuity (BCVA). Secondary outcomes include patient satisfaction, informed decision-making scores, and clinician acceptance of the AI tool. This study will provide high-level evidence on the clinical utility of AI in optimizing cataract surgical decision-making and patient communication.

Detailed description

Cataract is the leading cause of blindness worldwide, yet 5-20% of patients fail to achieve satisfactory visual recovery after surgery. Accurate preoperative prediction remains challenging, particularly for eyes with co-morbid retinal pathologies, as current methods relying on clinician experience and traditional tests (e.g., laser interferometry) often lack reproducibility. Although AI models like OCT-PRO show promise, prospective RCT evidence comparing their accuracy against clinicians is lacking.

This multi-center, randomized, assessor-blinded trial will enroll 534 adults scheduled for cataract surgery. Participants are allocated 1:1 to either the Experimental Group or the Control Group via centralized randomization. In the Experimental Group, clinicians use the OCT-PRO model-integrating OCT images and clinical data-to obtain a predicted postoperative BCVA. Physicians may confirm or adjust this prediction, and the final value is communicated to patients during preoperative counseling. The Control Group receives standard care, where predictions are based solely on conventional clinical assessments without AI assistance. Outcome assessors will be blinded to group allocation.

The primary endpoint is the Mean Absolute Error (MAE) between predicted and actual postoperative BCVA. Secondary endpoints include patient-reported outcomes (expectations, informed choice, satisfaction), clinician acceptance of the model, and correlation analyses. Analysis will follow the Intention-to-Treat principle. This study aims to provide high-level evidence on integrating AI into clinical workflows to enhance prognostic accuracy and optimize shared decision-making in cataract surgery.

Interventions

• Device OCT-PRO prediction model
  The OCT-PRO model integrates optical coherence tomography (OCT) images and clinical data to predict postoperative best-corrected visual acuity (BCVA). In the experimental group, clinicians input preoperative data into the model, confirm or adjust the prediction, and communicate the final value to patients during preoperative counseling.
• Behavioral Routine Preoperative Counseling
  Standard preoperative communication based on clinical experience and conventional examinations without AI assistance.

Primary outcome measures

• The Mean Absolute Error (MAE) between the predicted postoperative BCVA and the actual measured BCVA at 1 month post-surgery. [Time frame: Baseline, 1 month post-surgery]

Secondary outcome measures (6)

• Patient-reported consistency between surgical outcomes and expectations [Time frame: Baseline, 1 month post-surgery]
• Patient-reported psychological impact of preoperative prognostic disclosure [Time frame: Baseline, 1 month post-surgery]
• Patient-reported willingness to recommend prognostic information to others [Time frame: Baseline, 1 month post-surgery]
• Patient-reported satisfaction with healthcare services [Time frame: Baseline, 1 month post-surgery]
• Clinician-reported outcomes assessing the satisfaction of using OCT-PRO in cataract treatment decision-making [Time frame: Baseline, 1 month post-surgery]
• Correlation coefficients (Pearson/Spearman) between predicted and actual BCVA in both groups [Time frame: From before surgery to 1 month (±1 week) post-surgery]

Eligibility criteria

Inclusion criteria

• Age ≥18 years scheduled to undergo phacoemulsification with intraocular lens (Phaco+IOL) implantation.
• Outpatient diagnosis of senile, complicated, or metabolic cataract.
• For bilateral cataracts, the eye with more advanced disease will be included.

Exclusion criteria

• History of amblyopia or neuro-ophthalmic disease in the operative eye.
• Poor-quality OCT images precluding clear visualization of fundus structures.
• Previous intraocular surgery in the operative eye.
• Hearing or intellectual impairment preventing adequate cooperation.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Single blind

Primary purpose

Other

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT07713069 · 2026KYPJ063

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗