A review of recent developments in retinitis pigmentosa genetics, its clinical features, and natural course

Background: Retinitis pigmentosa (RP), an inherited degenerative ocular disease, is considered the most common type of retinal dystrophy. Abnormalities of the photoreceptors, particularly the rods, and of the retinal pigment epithelium, characterizes this disease. The abnormalities progress from the midperiphery to the central retina. We here reviewed the developments in RP genetics in the last decade, along with its clinical features and natural course. Methods: The present review focused on articles in English language published between January 2008 and February 2020, and deposited in PubMed and Google Scholar databases. We searched for articles reporting on the clinical manifestations and genes related to both syndromic and non-syndromic RP. We screened and analyzed 139 articles, published in the last decade, referring to RP pathogenesis and identified, summarized, and highlighted the most significant genes implicated in either syndromic or non-syndromic RP pathogenesis, causing different clinical manifestations. Results: Recent literature revealed that approximately 80 genes are implicated in non-syndromic RP, and 30 genes in syndromic forms, such as Usher syndrome and Bardet‒Biedl syndrome (BBS). Moreover, it is estimated that 27 genes are implicated in autosomal dominant RP (adRP), 55 genes in autosomal recessive RP (arRP), and 6 genes in X-linked RP (xlRP), causing different RP phenotypes. Characteristically, RHO is the most prevalent adRP- and arRP-causing gene, and RPGR the most common xlRP-causing gene. Other important genes are PRPH2, RP1, CRX, RPE65, ABCA4, CRB1, and USH2Α. However, different phenotypes can also be caused by mutations in the same gene. Conclusions: The genetic heterogeneity of RP necessitates further study to map the exact mutations that cause more severe forms of RP, and to develop and use appropriate genetic or other effective therapies in future

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

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

A Case of Early Keratoconus Associated with Eye Rubbing in a Young Child

Abstract Introduction Keratoconus usually presents during puberty and is considered rare in young children. Methods Case report with clinical findings and computerized corneal tomography. Results We report the case of an 8-year-old girl with early bilateral keratoconus who presented with allergic conjunctivitis and persistent eye rubbing. Although our patient did not exhibit steep keratometry, early cones and inferotemporal thinnest corneal thicknesses were detected in both eyes using Scheimpflug imaging (Oculus GmbH Pentacam, Wetzlar, Germany). Belin/Ambrósio total D values were 1.85 on the right and 2.11 on the left. Improvement in best-corrected visual acuity was noted after treatment of allergic eye disease, and corneal tomographic findings remained stable 4 months after initial consult. Conclusion This is a case of early diagnosed keratoconus in a young patient. Diagnosis of this condition in young children is challenging, as these patients are less likely to report visual complaints, and clinical examination is usually unremarkable. Keratoconus screening should be considered in children with atopy and eye rubbing behavior regardless of age, even in those with no other associated pathology and with negative family history

YAG laser peripheral iridotomy for the prevention of pigment dispersion glaucoma a prospective, randomized, controlled trial

Purpose: To test the hypothesis that neodymium: yttrium-aluminum-garnet (Nd:YAG) laser peripheral iridotomy (LPI) significantly reduces the incidence of conversion from pigment dispersion syndrome (PDS) with ocular hypertension (OHT) to pigmentary glaucoma (PG).Design: Prospective, randomized, controlled 3-year trial.Participants: One hundred sixteen eyes of 116 patients with PDS and OHT.Intervention: Patients were assigned randomly either to Nd:YAG LPI or to a control group (no laser).Main Outcome Measures: The primary outcome measure was conversion to PG within 3 years, based on full-threshold visual field (VF) analysis using the Ocular Hypertension Treatment Study criteria. Secondary outcome measures were whether eyes required topical antiglaucoma medications during the study period and the time to conversion or medication.Results: Fifty-seven patients were randomized to undergo laser treatment and 59 were randomized to no laser (controls). Age, gender, spherical equivalent refraction, and intraocular pressure at baseline were similar between groups. Outcome data were available for 105 (90%) of recruited subjects, 52 in the laser treatment group and 53 in the no laser treatment group. Patients were followed up for a median of 35.9 months (range, 10-36 months) in the laser arm and 35.9 months (range, 1-36 months) in the control arm. Eight eyes (15%) in the laser group and 3 eyes (6%) in the control group converted to glaucoma in the study period. The proportion of eyes started on medical treatment was similar in the 2 groups: 8 eyes (15%) in the laser group and 9 eyes (17%) in the control group. Survival analyses showed no evidence of any difference in time to VF progression or commencement of topical therapy between the 2 groups. Cataract extraction was performed on 1 patient in the laser group and in 1 patient in the control group during the study period (laser eye at 18 months; control eye at 34 months).Conclusions: This study suggests that there was no benefit of Nd:YAG LPI in preventing progression from PDS with OHT to PG within 3 years of follow-up

Using neural networks to predict the outcome of refractive surgery for myopia

Introduction: Refractive Surgery (RS), has advanced immensely in the last decades, utilizing methods and techniques that fulfill stringent criteria for safety, efficacy, cost-effectiveness, and predictability of the refractive outcome. Still, a non-negligible percentage of RS require corrective retreatment. In addition, surgeons should be able to advise their patients, beforehand, as to the probability that corrective RS will be necessary. The present article addresses these issues with regard to myopia and explores the use of Neural Networks as a solution to the problem of the prediction of the RS outcome. Methods: We used a computerized query to select patients who underwent RS with any of the available surgical techniques (PRK, LASEK, Epi-LASIK, LASIK) between January 2010 and July 2017 and we investigated 13 factors which are related to RS. The data were normalized by forcing the weights used in the forward and backward propagations to be binary; each integer was represented by a 12-bit serial code, so that following this preprocessing stage, the vector of the data values of all 13 parameters was encoded in a binary vector of 1 × (13 × 12) = 1 × 156 size. Following the preprocessing stage, eight independent Learning Vector Quantization (LVQ) networks were created in random way using the function Ivqnet of Matlab, each one of them responding to one query with (0 retreat class) or (1 correct class). The results of the eight LVQs were then averaged to permit a best estimate of the network’s performance while a voting procedure by the neural nets was used to arrive at the outcome Results: Our algorithm was able to predict in a statistically significant way (as evidenced by Cohen’s Kappa test result of 0.7595) the need for retreatment after initial RS with good sensitivity (0.8756) and specificity (0.9286). Conclusion: The results permit us to be optimistic about the future of using neural networks for the prediction of the outcome and, eventually, the planning of RS