跳至主要内容
临床试验/NCT07713069
NCT07713069尚未招募不适用

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

Zhongshan Ophthalmic Center, Sun Yat-sen University0 个研究点目标入组 534 人开始时间: 2026年7月20日最近更新:
适应症

试验速览

阶段
不适用
状态
尚未招募
入组人数
534
主要终点
The Mean Absolute Error (MAE) between the predicted postoperative BCVA and the actual measured BCVA at 1 month post-surgery.

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Other
盲法
Single (Outcomes Assessor)

入排标准

年龄范围
18 Years 至 90 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 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.

排除标准

  • 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.

结局指标

主要结局

The Mean Absolute Error (MAE) between the predicted postoperative BCVA and the actual measured BCVA at 1 month post-surgery.

时间窗: Baseline, 1 month post-surgery

次要结局

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

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Haotian Lin

Professor

Zhongshan Ophthalmic Center, Sun Yat-sen University

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