Machine Learning Prediction of 1-Year Refractive Error After SMILE (SMILE)

Development and Internal Validation of a Multi-output Machine Learning Model for Predicting 1-Year Postoperative Refractive Prediction Error After Small Incision Lenticule Extraction and Comparative Virtual Planning Analysis Against ZEISS 4.0

This retrospective single-center observational study is designed to develop and internally validate a multi-output machine learning model for predicting 1-year postoperative refractive prediction error after small incision lenticule extraction (SMILE). The primary modeling target is 1-year spherical equivalent prediction error. Secondary targets include J0 prediction error, J45 prediction error, and postoperative uncorrected distance visual acuity in logarithm of the minimum angle of resolution. A secondary objective is to use the prediction framework to derive individualized nomogram recommendations and to compare these recommendations with ZEISS 4.0 planning in a virtual treatment-planning analysis.

Study Overview

• Status: Completed
• Conditions: Myopia; Myopic Astigmatism; Refractive Error - Myopia Axial

• Study Type: Observational
• Enrollment (Actual): 1100

Contacts and Locations

Study Locations

• China
  • Shanghai Municipality
    • Shanghai, Shanghai Municipality, China, 200072
      • Shanghai Tenth People's Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

People with moderate myopia who have undergone SMILE surgeries

Description

Inclusion Criteria:

• Eyes that underwent SMILE for correction of myopia or myopic astigmatism
• Availability of preoperative examination data and surgical planning data
• Availability of postoperative follow-up data at approximately 1 year
• Age ≥ 18 years

Exclusion Criteria:

• Previous ocular surgery in the study eye
• Ocular comorbidity likely to affect refractive or visual outcome
• Intraoperative or postoperative complications that precluded standard outcome assessment
• Missing key variables required for analysis

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Training Cohort; Eyes included in the prespecified training dataset for development of the multi-output machine learning model.
Test Cohort; Eyes included in the prespecified independent test dataset for internal validation of the multi-output machine learning model.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Mean Absolute Error of Predicted 1-Year Postoperative Spherical Equivalent Prediction Error	Model performance for prediction of 1-year postoperative spherical equivalent prediction error, assessed in diopters.	1 year after SMILE

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Mean Absolute Error of Predicted 1-Year Postoperative J0 Prediction Error	Model performance for prediction of the cardinal astigmatic vector component (J0), assessed in diopters.	1 year after SMILE
Mean Absolute Error of Predicted 1-Year Postoperative J45 Prediction Error	Mean Absolute Error of Predicted 1-Year Postoperative J45 Prediction Error	1 year after SMILE

Collaborators and Investigators

• Sponsor: Tongji University

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2018
• Primary Completion (Actual): December 31, 2025
• Study Completion (Actual): January 31, 2026

Study Registration Dates

• First Submitted: March 12, 2026
• First Submitted That Met QC Criteria: March 12, 2026
• First Posted (Actual): March 17, 2026

Study Record Updates

• Last Update Posted (Actual): March 17, 2026
• Last Update Submitted That Met QC Criteria: March 12, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: Small Incision Lenticule Extraction; Refractive Error; Refractive Surgery; Nomogram
• Additional Relevant MeSH Terms: Eye Diseases; Myopia; Astigmatism; Refractive Errors
• Other Study ID Numbers: 2026ML; SHDC12025144 (Other Grant/Funding Number: Shanghai Hospital Development Center Foundation)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No