Purpose: To report a case of post–keratorefractive lenticule extraction (KLEx) ectasia in the United States followed by a comprehensive literature review of all published KLEx ectasia cases with an analysis of risk factors and prevalence rates. Methods: A systematic literature search of PubMed, Embase, Google Scholar, and institutional databases for studies published between January 2008 and April 2026 was conducted. Studies reporting cases of post-KLEx ectasia and large cohort studies with a minimum of 3-year follow-up without ectasia were included. Demographic, tomographic, and surgical parameters were extracted. Comparative statistical analysis between cohorts with and without ectasia was performed. Results: At our institution, a 34-year-old woman developed ectasia 4 years after KLEx, with borderline risk factors and possible subclinical keratoconus. Including this case, 69 eyes from 41 patients across 25 studies were identified with post-KLEx ectasia. Common preoperative abnormalities included elevated Belin/Ambrosio Display Deviation score, reduced Ambrosio Relational Thickness maximum, and tomographic abnormalities. Compared with international nonectatic cohorts, ectatic eyes were significantly younger, had thinner corneas, and higher astigmatism. Overall prevalence of post-KLEx ectasia at our institution was 0.3% over an 8-year period. Conclusions: Post-KLEx ectasia is a rare but recognized complication with several predisposing factors. Younger age, higher astigmatism, and tomographic abnormalities were more prevalent among the ectasia cohort, mirroring established risk factors for post-LASIK and post-PRK ectasia. The development of ectasia even in tomographically normal eyes poses the question of whether refractive surgery induces ectasia de novo or unmasks subclinical keratoconus.

Objectives: To evaluate a general-purpose large language model (LLM)’s ability to perform surgeon-level decision-making in choosing an intraocular lens (IOL) power when provided the same preoperative data. Methods: This study included 293 eyes (174 patients) that underwent monofocal or toric cataract surgery performed by a single surgeon. GPT-5.2 analyzed the same biometric printouts, topographic displays, and preoperative data used in surgical planning. Postoperative refraction for GPT-5.2-selected IOLs was simulated from the measured postoperative refraction using a fixed conversion factor. The mean refractive deviation from target, mean absolute error (MAE), and number of eyes within ±0.25 D and ±0.50 D of target refraction were calculated. A subgroup analysis evaluated toric IOL cylinder magnitude and axis. Results: GPT-5.2-selected IOL power differed significantly from that of the surgeon (19.24 ± 4.01 vs. 19.64 ± 4.07 D [mean ± SD], p < 0.001). Using simulated refractive outcomes for GPT-5.2, MAE was higher than for surgeon-selected IOLs (0.45 ± 0.03 vs. 0.35 ± 0.02 D [mean ± SE], p = 0.002), and a greater percentage of eyes fell within ±0.25 D of target refraction for the surgeon (51.9% vs. 44.7%, p < 0.01), with no difference within ±0.50 D (p = 0.06). In toric eyes, the cylinder magnitude did not differ, but simulated residual astigmatism was higher for GPT-5.2 (0.78 ± 0.55 vs. 0.58 ± 0.47 D, p < 0.001), with an axis flip in 47.1% versus 39.2% of eyes. Conclusions: GPT-5.2 synthesized clinical data and approximated surgeon IOL selection, but its simulated refractive outcomes were less accurate than the surgeon’s measured outcomes. These findings suggest that a domain-specific LLM may serve as a support tool in IOL selection and cataract surgery planning.

Purpose: Our study evaluated a cohort of patients who previously underwent EVO Implantable Collamer Lens (ICL) implantation to assess the retrospective performance of the ICLGuru™ artificial intelligence (AI) sizing tool in predicting postoperative vault. Additionally, biometric factors associated with vault prediction error were identified. Methods: This retrospective single-center study included 104 eyes from 56 patients who underwent EVO V4c or V5 ICL implantation between May 2023 and June 2025. Preoperative ultrasound biomicroscopy (UBM) images, from patients who had already undergone ICL surgery, were retrospectively analyzed using ICLGuru to generate predicted postoperative vaults. Actual postoperative vault was measured at 1-, 3-, or 6-month follow-up visits, with 3-month measurements preferentially included for analysis. Mixed-effects regression models were used to evaluate associations between biometric variables and vault prediction error. Results: Mean absolute error was 135 ± 110 μm, indicating a tendency for ICLGuru to overestimate postoperative vault (p < 0.001). Among 16 eyes with actual postoperative overvault, ICLGuru retrospectively identified 15 cases in which a smaller lens size was predicted to achieve target vault, suggesting these outcomes may have been flagged. Out of 7 eyes with actual undervault, only two cases may have been flagged with use of ICLGuru, indicating that the tool is not as useful in preventing undervault. Mixed-effects regression demonstrated that greater iridocorneal angle and higher aRISE were significantly associated with lower vault prediction error (p < 0.05). Conclusion: ICLGuru demonstrated useful postoperative vault predictions with performance comparable to existing machine learning and UBM-based nomograms, though it appeared to overestimate longer term vault in our cohort. The tool may be valuable in identifying eyes at risk for excessive vault. aRISE and iridocorneal angle were significant predictors of vault prediction error, supporting their importance in future ICL sizing models.

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Purpose: This study explores the relationship between the distribution of active American Society of Ophthalmic Plastic and Reconstructive Surgery (ASOPRS) oculofacial surgeons in the United States and the socioeconomic characteristics of their practice locations, as measured by the Area Deprivation Index (ADI). Methods: In this cross-sectional study, active ASOPRS oculofacial surgeons in the United States were identified using the Oculofacial Society surgeon directory. Data on physician demographics, career stage, and practice type and location were compiled from publicly available sources. The ADI was extracted for each practice address. Chi-squared testing was performed for qualitative analysis. Results: Overall, 580 physician addresses had obtainable state and national ADI values. The average ADI state decile was 3.5 and average national percentile was 29.9. The majority of surgeons (58.4%) practiced within the first state decile and national percentile quartile (i.e., the lowest socioeconomic disadvantage). Practice locations in 41 states had average state decile values categorized as “low”, while practice locations in 36 states had average national percentile values categorized as “low.” There was no statistically significant difference between male and female presence, career stage, and practice type in low versus high ADI areas. Conclusion: The majority of ASOPRS oculofacial surgeons practice in neighborhoods with less socioeconomic disadvantage, as indicated by lower ADI state deciles and national percentiles, potentially contributing to healthcare disparities. Further research is warranted to understand other factors that may contribute to the ADI distribution of physicians and the role of ADI in pinpointing health care inequities.