Cataract
Conditions
Keywords
Cataract, Post-operative prognosis, Artificial intelligence, Multimodal data fusion, Clinical decision support
Brief summary
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
DEVICEOCT-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.
BEHAVIORALRoutine Preoperative Counseling
Standard preoperative communication based on clinical experience and conventional examinations without AI assistance.
Sponsors
Zhongshan Ophthalmic Center, Sun Yat-sen University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
SINGLE (Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The Mean Absolute Error (MAE) between the predicted postoperative BCVA and the actual measured BCVA at 1 month post-surgery. | Baseline, 1 month post-surgery |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Patient-reported consistency between surgical outcomes and expectations | 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). |
| Patient-reported psychological impact of preoperative prognostic disclosure | 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). |
| Patient-reported willingness to recommend prognostic information to others | 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). |
| Patient-reported satisfaction with healthcare services | 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). |
| Clinician-reported outcomes assessing the satisfaction of using OCT-PRO in cataract treatment decision-making | 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). |
| Correlation coefficients (Pearson/Spearman) between predicted and actual BCVA in both groups | From before surgery to 1 month (±1 week) post-surgery | — |
Outcome results
None listed