ArticleClinical ophthalmology (Auckland, N.Z.)2023
Assessment of Preoperative Risk Factors for Post-LASIK Ectasia Development.
Article in Clinical ophthalmology (Auckland, N.Z.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Tomographic and biomechanical corneal characteristics of patients with angioid streaks.International journal of ophthalmology · 2026Article
- Safety evaluation after LASIK surgery based on the linear creep property: a finite element analysis.International journal of ophthalmology · 2025Article
- Assessment of Preoperative Risk Factors for Post-LASIK Ectasia Development [Letter].Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- Assessment of Preoperative Risk Factors for Post-LASIK Ectasia Development [Response to Letter].Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- The development of a machine learning model to train junior ophthalmologists in diagnosing the pre-clinical keratoconus.Frontiers in medicine · 2024Article
- Shaping the future of myopia with artificial intelligence: Mapping trends and promising directions.Advances in ophthalmology practice and researchArticle
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate preoperative risk factors (mainly those related to corneal topography/tomography) for post-LASIK ectasia development. Methods: A retrospective case review for post-LASIK ectasia for myopia or myopic astigmatism. The evaluated data included preoperative subjective refraction, method of flap creation, and topometric/tomographic parameters from Oculus Pentacam, including subjective curvature pattern, topometric, elevation, and pachymetric indices from the Belin Ambrosio display "BAD", and the Pentacam Random Forest Index (PRFI). Moreover, preoperative ectasia detection indices were calculated (including Percentage of Tissue Altered "PTA" index, Randleman Ectasia Risk Score System "ERSS", and Navarro Index for Corneal Ectasia "NICE"). Results: Twenty-four eyes of 15 patients were enrolled. Concerning the risk factors, age was lower than 25 in 19 eyes (79%); flaps were created using a microkeratome in 17 eyes (70.8%); thinnest pachymetry was lower than 510μm in eight eyes (33%); total deviation from BAD was higher than 1.6 in 50%; Ambrósio's relational thickness (ART) max was lower than 340 in 45.83%; PTA index was higher than 40% in 16%; ERSS was more than 3 points in 62.5%; NICE was higher than 8 points in three eyes (12.5%); PRFI index was more than 0.125 in 87.5%; two eyes (8%) had no identifiable risk factors. Conclusion: Current ectasia risk assessment criteria were insufficient for detecting a relatively large number of cases. There is an unequivocal need for more information, which may be derived from biomechanical assessment and epithelial thickness mapping. Novel corneal tomography indices derived from artificial intelligence may increase accuracy in characterizing ectasia susceptibility.
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