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Record W4411648972 · doi:10.1016/j.jfo.2025.104572

Incidence of epithelial ingrowth following femtosecond laser LASIK flap lifts

2025· article· fr· W4411648972 on OpenAlexaffabout
Mohamed Gemae, Daniel A. Johnson

Bibliographic record

VenueJournal Français d Ophtalmologie · 2025
Typearticle
Languagefr
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsLASIKFemtosecondLaserMedicineIncidence (geometry)SurgeryOpticsPhysics

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the incidence of epithelial ingrowth (EI) following femtosecond LASIK (f-LASIK) flap relift. METHODS: This retrospective case series enrolled patients who underwent post-refractive enhancement surgery at a single independent outpatient health facility in Canada. Patients 18 years or older who underwent refractive enhancement surgery between July 2021 and December 2022 were eligible. We excluded patients with a history of cataract or refractive lens exchange surgery. Follow-ups were conducted at 1 week, 1 month, 3 months, 6 months, and 1 year postoperatively. The primary outcome was the incidence of EI following f-LASIK flap relifts. Secondary outcomes included other complications and visual outcomes 12 months postoperatively. RESULTS: Among the 103 included eyes, EI was reported in 41% of patients at some point in the follow-up period, with most EI present at one month and not requiring treatment. EI was three times less likely to develop if the enhancement was performed within one year of the original surgery (OR 0.31, P=0.023), and was 5-6 times more likely to develop if it was performed after three years (OR=0.17, P<0.001). Successful treatment of EI by flap lift with sutures (n=2) and Nd:YAG laser (n=2) was performed in 4 eyes. CONCLUSIONS: Only a small number (n=4) of EI post-flap lifts required treatment, and the procedure generally provided excellent long-term visual outcomes. Thus, f-LASIK flap lift is a safe option for refractive enhancement, even several years following the original surgery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.298
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

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