Rhegmatogenous retinal detachment in uveitis

Abstract Background Retinal detachment is more common among uveitis patients than in the general population. Here, we aimed to assess the prevalence of rhegmatogenous retinal detachment (RRD) in a uveitis population. Methods We retrospectively studied 851 uveitis patients, recording characteristics such as uveitis duration, anatomical location, and cause; RRD occurrence; proliferative vitreoretinopathy (PVR) at presentation; surgical approach; reattachment rate; and initial and final visual acuity (VA). Results RRD occurred in 26 patients (3.1%; 29 affected eyes) and was significantly associated with posterior uveitis (p < 0.001), infectious uveitis (p < 0.001), and male gender (p = 0.012). Among cases of infectious uveitis, cytomegalovirus and varicella zoster virus were most commonly associated with RRD development. RRD in non-infectious uveitis was not found to be associated with any specific uveitis entity. The rate of single-operation reattachment was 48%, and the rate of final reattachment was 83%. Mean final VA was 20/125, with 41% of eyes ultimately having a VA of less than 20/200. Conclusion Uveitis is a risk factor for RRD development, which carries a poor prognosis

DIAGNOSTIC PARS PLANA VITRECTOMY AND AQUEOUS ANALYSES IN PATIENTS WITH UVEITIS OF UNKNOWN CAUSE

Purpose: To compare the yield of diagnostic pars plana vitrectomy (PPV) with the yield of aqueous analyses in patients with uveitis of unknown cause. Methods: Seventy-five consecutive patients (84 eyes) with uveitis involving posterior eye segment who undergo a diagnostic PPV from 2005 through 2009 were retrospectively reviewed. Vitreous specimens were simultaneously analyzed by microbiological culture, flow cytometry, and cytology as well as by polymerase chain reaction and for intraocular antibody production by Goldmann-Witmer coefficient. In 53 eyes, both aqueous and vitreous samples were assessed. The primary outcome measure was the comparison between vitreous and aqueous analyses. Results: Vitreous analysis was positive in 18 of 84 eyes (21%). Positive results indicated infectious uveitis in 12 of 18 cases (67%) and lymphoma in 6 of 18 (33%) cases. Of the 53 eyes with both aqueous and vitreous samples available, aqueous analysis revealed the diagnosis in 6 of 53 eyes and vitreous in 9 of 53 eyes. Unilateral uveitis (P = 0.022), panuveitis and uveitis posterior (P <= 0.001), preoperative immunosuppressive therapy (P = 0.004), and increasing age (P = 0.018) were associated with an increased diagnostic yield of PPV. Overall, 1 year after PPV, median visual acuity improved from 20/200 to 20/80 (Snellen, P <= 0.001). Of 18 patients who were on immunosuppressive treatment before PPV, 8 (44%) were able to stop immunosuppressive therapy during 1-year follow-up. The complications of PPV consisted predominantly of cataract development (33/65, 51%). Conclusion: Diagnostic PPV with the analysis of vitreous fluid by multiple laboratories for infectious and malignant disorders was useful in diagnosing uveitis of unknown cause. Previous aqueous analysis was especially valuable for the diagnosis of intraocular infections and may therefore decrease the number of patients who would otherwise undergo an invasive diagnostic PPV. Furthermore, PPV was associated with improved visual acuity and decreased use of immunosuppressive therapy

A machine learning approach to explore predictors of graft detachment following posterior lamellar keratoplasty: a nationwide registry study

Machine learning can be used to explore the complex multifactorial patterns underlying postsurgical graft detachment after endothelial corneal transplantation surgery and to evaluate the marginal effect of various practice pattern modulations. We included all posterior lamellar keratoplasty procedures recorded in the Dutch Cornea Transplant Registry from 2015 through 2018 and collected the center-specific practice patterns using a questionnaire. All available data regarding the donor, recipient, surgery, and practice pattern, were coded into 91 factors that might be associated with the occurrence of a graft detachment. In this research, we used three machine learning methods; a regularized logistic regression (lasso), classification tree analysis (CTA), and random forest classification (RFC), to select the most predictive subset of variables for graft detachment. A total of 3647 transplants were included in our analysis and the overall prevalence of graft detachment was 9.9%. In an independent test set the area under the curve for the lasso, CTA, and RFC was 0.70, 0.65, and 0.72, respectively. Identified risk factors included: a Descemet membrane endothelial keratoplasty procedure, prior graft failure, and the use of sulfur hexafluoride gas. Factors with a reduced risk included: performing combined procedures, using pre-cut donor tissue, and a pre-operative laser iridotomy. These results can help surgeons to review their practice patterns and generate hypotheses for empirical research regarding the origins of graft detachments