72 research outputs found

    Keratoconus: is it a Non-inflammatory Disease?

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    Editorial/No abstrac

    Late-Onset Anterior Dislocation of a Posterior Chamber Intraocular Lens in a Patient with Pseudoexfoliation Syndrome

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    Here, we report on a patient with pseudoexfoliation syndrome who developed acute angle-closure glaucoma with a marked myopic shift due to anterior dislocation of the posterior chamber intraocular lens almost 16 months after an uneventful phacoemulsification. Examination with a Scheimpflug camera was extremely useful in confirming the diagnosis. This is the fist case of late-onset angle-closure glaucoma with a significant myopic shift due to anterior dislocation of the posterior chamber intraocular lens, which resulted in a permanent alteration of the postoperative target refraction

    Validation of Neural Network Predictions for the Outcome of Refractive Surgery for Myopia

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    Background: Refractive surgery (RS) for myopia has made a very big progress regarding its safety and predictability of the outcome. Still, a small percentage of operations require retreatment. Therefore, both legally and ethically, patients should be informed that sometimes a corrective RS may be required. We addressed this issue using Neural Networks (NN) in RS for myopia. This was a recently developed validation study of a NN.  Methods: We anonymously searched the Ophthalmica Institute of Ophthalmology and Microsurgery database for patients who underwent RS with PRK, LASEK, Epi-LASIK or LASIK between 2010 and 2018. We used a total of 13 factors related to RS. Data was divided into four sets of successful RS outcomes used for training the NN, successful RS outcomes used for testing the NN performance, RS outcomes that required retreatment used for training the NN and RS outcomes that required retreatment used for testing the NN performance. We created eight independent Learning Vector Quantization (LVQ) networks, each one responding to a specific query with 0 (for the retreat class) or 1 (for the correct class). The results of the 8 LVQs were then averaged so we could obtain a best estimate of the NN performance. Finally, a voting procedure was used to reach to a conclusion. Results: There was a statistically significant agreement (Cohen’s Kappa = 0.7658) between the predicted and the actual results regarding the need for retreatment. Our predictions had good sensitivity (0.8836) and specificity (0.9186). Conclusion: We validated our previously published results and confirmed our expectations for the NN we developed. Our results allow us to be optimistic about the future of NNs in predicting the outcome and, eventually, in planning RS
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