PREVALENCE AND TYPES OF ABERRATIONS IN EYES WITH SUPERVISION

Patient preparation and examination:

1. Full ophthalmic examination: Perform standard comprehensive eye exam including

·       Refractive status- UCVA, BCVA

·       Slit lamp examination, IOP and Dilated fundus examination

 

2. Aberrometry (Primary Test)(HOYA Itrace surgical workstation USA)

Key parameters captured:

·       Total HOA (RMS)

·       Corneal HOA (RMS)

·       Internal HOA (RMS)

·       Zernike coefficients up to 6th order

·       Specific aberrations of interest:

o   Coma (vertical, horizontal)

o   Trefoil

o   Spherical aberration

o   Secondary astigmatism

· Topography

·       Placido-disc corneal topography from iTrace

·       Keratometry values

·       Cone-like irregularities (if any)

· Quality Control

·       Minimum of 3 scans per eye, best-quality scan used

·       Pupil size documented for each scan

  Participants will be divided based on their refractive status into:

Group 1: untreated UCVA 6/4 or better

Group 2: BCVA 6/4 or better

Group 3: post corneal refractive surgery with 6/4 or better

 OUTCOME MEASURES

Primary Outcome

• Mean and distribution of total, corneal, and internal HOA RMS values in super-normal–vision eyes.

Secondary Outcomes

• Relationship between individual HOAs and UCVA (correlation analysis).
• Differences in HOA patterns across refractive groups.
• Proportion of subjects with “favorable” HOA profiles (e.g., negative spherical aberration).

    DATA COLLECTION AND EXTRACTION:

 Data should be extracted from iTrace software reports and recorded in study database (eg excel, red cap)

•       Patient demographics: Age, gender, study ID;

•       Refractive data (low order aberrations LOA); Aberration metrics: record the root mean square values for relevant aberrations, typically for a fixed pupil diameter.

     STATISTICAL ANALYSIS METHODOLOGY:

All analyses will be conducted using Python (v3.12) and Jamovi (v2.5). Group differences will be assessed using a one-way fixed-effect ANOVA, with normality evaluated using the Kolmogorov–Smirnov test and homogeneity of variances tested using Levene’s test. Continuous data will be presented as mean ± SD, and categorical data as frequencies and percentages. When the ANOVA is significant, Bonferroni-adjusted post hoc tests will be performed. When normality assumptions are not met, appropriate non-parametric tests will be applied. A two-tailed p-value < 0.05 will be considered statistically significant.