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NCT Number: NCT07713069

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

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.

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Key information

Conditions

Cataract Eye Diseases Lens Diseases

Age range

18 year–90 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

OCT-PRO prediction model

Device

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.

Routine Preoperative Counseling

Behavioral

Standard preoperative communication based on clinical experience and conventional examinations without AI assistance.

Primary outcomes

  1. 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 outcomes

  1. Patient-reported consistency between surgical outcomes and expectations

    Time frame: Baseline, 1 month post-surgery

    Patient-perceived alignment between actual surgical outcomes and preoperative expectations, measured via a validated questionnaire using a 5-point Likert scale (strongly disagree to strongly agree).

  2. Patient-reported psychological impact of preoperative prognostic disclosure

    Time frame: Baseline, 1 month post-surgery

    Psychological response to receiving preoperative prognostic information (e.g., anxiety, reassurance), measured via a validated questionnaire using a 5-point Likert scale (strongly disagree to strongly agree).

  3. Patient-reported willingness to recommend prognostic information to others

    Time frame: Baseline, 1 month post-surgery

    Willingness to recommend cataract surgery prognostic information to others (e.g., family or friends), measured via a validated questionnaire using a 5-point Likert scale (strongly disagree to strongly agree).

  4. Patient-reported satisfaction with healthcare services

    Time frame: Baseline, 1 month post-surgery

    Patient satisfaction with overall healthcare services received during cataract surgery (e.g., communication, care quality, information clarity), measured via a validated questionnaire using a 5-point Likert scale (strongly disagree to strongly agree).

  5. Clinician-reported outcomes assessing the satisfaction of using OCT-PRO in cataract treatment decision-making

    Time frame: Baseline, 1 month post-surgery

    Clinician-reported satisfaction with incorporating OCT-PRO into preoperative decision-making (e.g., ease of use, confidence in prediction, communication aid), measured via a validated questionnaire using a 5-point Likert scale (strongly disagree to strongly agree).

  6. Correlation coefficients (Pearson/Spearman) between predicted and actual BCVA in both groups

    Time frame: From before surgery to 1 month (±1 week) post-surgery

Sponsors and collaborators

Lead sponsor

Zhongshan Ophthalmic Center, Sun Yat-sen University

Other

Registry information

Official study 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

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Jul 20, 2026
Registry last updated
Jul 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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