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

Официальное название

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

Обзор

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.

Подробное описание

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.

Вмешательства

• Устройство 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.
• Поведенческое Routine Preoperative Counseling
  Standard preoperative communication based on clinical experience and conventional examinations without AI assistance.

Первичные конечные точки

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

Вторичные конечные точки (6)

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

Критерии участия

Критерии включения

• 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.

Критерии исключения

• 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.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Другое

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Идентификаторы

NCT: NCT07713069 · 2026KYPJ063

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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