Background/Objectives: Keratoconus (KC) can rapidly erode vision in children with Leber congenital amaurosis (LCA), yet screening usually depends on costly corneal imaging that is often unavailable. We evaluated whether a lightweight, image-free neural network fed only routine clinical and genetic variables can detect KC in patients with AIPL1-related LCA. Methods: This retrospective, proof-of-concept pilot study analyzed chart data for 19 children with biallelic AIPL1 mutations (6 with KC) seen at five tertiary eye centers between January and December 2004. Ten baseline predictors were entered into a feed-forward neural network. Records were randomly split 60/20/20 into training, validation and test sets; 20 replicate networks were trained. The mean test accuracy, sensitivity and specificity across runs were the primary outcomes. Results: The ensemble achieved a mean test accuracy of 91.6% (SD 12.8%), sensitivity of 87.5% (SD 13.1%) and specificity of 93.5% (SD 17.0%). A total of 6 of the 20 runs made no test-set errors, and 16 achieved 100% specificity. The median training time per network was less than 1 s on a laptop CPU. Conclusions: This exploratory pilot shows that a point-of-care, image-free neural network using readily available clinical and genetic data accurately identified KC in AIPL1-LCA. External validation in larger, contemporary cohorts is warranted, but the approach could help triage scarce imaging resources and enable timely corneal–collagen cross-linking in settings where tomography is inaccessible.

Visual field (VF) testing is crucial for the management of glaucoma. However, the process is often hindered by technician shortages and reliability issues. In this study, we leveraged machine learning to predict pattern standard deviation (PSD) using clinical inputs. This machine learning retrospective study used publicly accessible data from 743 eyes (541 glaucoma and 202 non-glaucoma controls). An automated neural network (ANN) model was trained using seven clinical input features: mean retinal nerve fiber layer (RNFL), IOP, patient age, CCT, glaucoma diagnosis, study protocol, and laterality. The ANN demonstrated efficient training across 1000 epochs, with consistent error reduction in training and test sets. Mean RMSEs were 1.67 ± 0.05 for training, and 2.27 ± 0.27 for testing. The r was 0.89 ± 0.01 for training, and 0.81 ± 0.04 for testing, indicating strong predictive accuracy with minimal overfitting. The LOFO analysis revealed that the primary contributors to PSD prediction were RNFL, CCT, IOP, glaucoma status, study protocol, and age, listed in order of significance. Our neural network successfully predicted PSD from RNFL and clinical data with strong performance metrics, in addition to demonstrating construct validity. This work demonstrates that neural networks hold the potential to predict or even generate VF estimations based solely on RNFL and clinical inputs.

Précis: The Hydrus Microstent combined cataract surgery reduces IOP and medication use in mild-to-moderate glaucoma. For severe open angle glaucoma, it reduces medication use while maintaining a favorable safety profile. Purpose: This study evaluates the 12-month clinical outcomes of Hydrus Microstent combined with cataract surgery in eyes with open angle glaucoma stratified by disease severity. Materials and Methods: Retrospective, single-surgeon cohort study. Eyes with mild-to-moderate and severe glaucoma undergoing Hydrus implantation combined with cataract surgery were included. Primary outcomes were complete (no medication) and qualified (with medication) success (6–21 mm Hg) at 1 year. Secondary outcomes included IOP, number of glaucoma medications, complications, failure, and success rates for 6–18 and 6–15 mm Hg IOP thresholds. Results: A total of 147 eyes from 100 patients with a median baseline IOP of 16.0 [IQR: 14.0–20.0] on 2.0 [1.0–3.0] medications were included. Complete success was achieved in 78% and qualified success in 93% of eyes, with mild-to-moderate glaucoma achieving 77% and 92%, and severe glaucoma achieving 84% and 96%, respectively. In the mild-to-moderate group, mean IOP decreased from 17.1±3.8 mm Hg (SD) to 15.5±2.7 mm Hg ( P <0.0003), and medications were reduced from 2.2±1.1 to 0.6±1.1 ( P <0.0001). In the severe group, mean IOP was not significantly changed, and medications were reduced from 2.6±1.3 to 1.2±1.3 ( P =0.0008). At 12 months, 64% of eyes were medication-free, and 67% of severe cases required one or fewer medications. Focal peripheral anterior synechiae (35%) was the most common complication. Conclusion: The Hydrus Microstent lowered medication use across all glaucoma severities. Further studies with larger sample sizes are warranted to support these findings.