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Assessment of Preoperative Risk Factors for Post-LASIK Ectasia Development.

Mohamed Tarek El-Naggar¹, Rania Serag Elkitkat^2,3,4,5, Hossam El-Din Ziada⁶

¹Refractive Surgery Unit, Ophthalmology Department, Research Institute of Ophthalmology, Giza, Egypt.

Clinical Ophthalmology (Auckland, N.Z.)

|December 11, 2023

Summary

Pre-LASIK ectasia risk factors, particularly corneal topography, are crucial for identifying patients susceptible to post-LASIK ectasia. Current assessment methods are insufficient, highlighting the need for advanced diagnostics like AI-driven indices.

Keywords:

LASIK screening Pentacam cornea ectasia preoperative ectasia risk assessment

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Area of Science:

Ophthalmology
Corneal Surgery
Refractive Surgery

Background:

Post-LASIK ectasia is a sight-threatening complication following refractive surgery.
Accurate preoperative risk assessment is vital to prevent its development.

Purpose of the Study:

To evaluate preoperative risk factors, focusing on corneal topography and tomography, for predicting post-LASIK ectasia.
To assess the efficacy of existing ectasia risk assessment criteria.

Main Methods:

Retrospective review of 24 eyes diagnosed with post-LASIK ectasia.
Analysis of preoperative data including refraction, flap creation method, and advanced corneal tomography parameters (e.g., Belin Ambrosio display, PRFI).
Calculation of established ectasia risk indices (PTA, ERSS, NICE).

Main Results:

A significant proportion of ectasia cases had risk factors like young age (<25 years), microkeratome flap creation, and thin corneas (<510μm).
Elevated Belin Ambrosio display (BAD) deviation and high Pentacam Random Forest Index (PRFI) were common.
Existing risk assessment criteria (ERSS, NICE) identified risk in a majority of cases, but some patients had no identifiable factors.

Conclusions:

Current ectasia risk assessment criteria demonstrate limitations in detecting all susceptible cases.
Further research incorporating biomechanical assessment and epithelial thickness mapping is needed.
Novel AI-derived corneal tomography indices show promise for improving ectasia susceptibility characterization.