OUTCOME OF ACUTE NONTRAUMATIC VITREOUS HEMORRHAGE IN HEALTHY PATIENTS.

PURPOSE: To compare outcomes in dense vitreous hemorrhage versus mild vitreous hemorrhage due to nontraumatic posterior vitreous detachment. METHODS: We compared 315 eyes, divided into 2 patient groups, one with dense and the other with mild vitreous hemorrhage. The main outcome measures were final mean best-corrected visual acuity, number of retinal tears, number of retinal detachments, and the number of pars plana vitrectomy and/or scleral buckle surgeries. RESULTS: In 33.4% of the patients, posterior vitreous detachment without complications was found. Retinal breaks after posterior vitreous detachment were found in 59% of the eyes. Rhegmatogenous retinal detachment was principally treated with pars plana vitrectomy and scleral buckle. In nonvisible fundus hemorrhage group, 44.4% of the patients underwent vitrectomy. In visible fundus hemorrhage group, 9.52% of the patients underwent pars plana vitrectomy. The mean final visual acuity was 20/25, without significant difference between groups (P = 0.064). CONCLUSION: Acute, spontaneous, nontraumatic posterior vitreous separation with vitreous hemorrhage is associated with a high incidence of retinal complications. Close follow-up is necessary. We did not find significant differences in final visual acuity neither between the two groups nor among the treatments.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography.

PURPOSE: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). METHODS: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. RESULTS: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911-0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. CONCLUSIONS: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

Diagnostic ability of macular nerve fiber layer thickness using new segmentation software in glaucoma suspects.

PURPOSE: To assess the capacity of internal retinal layer thickness measurements made at the macula using new spectral-domain optical coherence tomography (OCT) software to distinguish between healthy subjects and those with suspected glaucoma. The diagnostic performance of such measurements also was compared with that of conventional peripapillary retinal nerve fiber layer (RNFL) thickness measurements. METHODS: The study included 38 subjects with suspected glaucoma and 38 age-matched healthy subjects. In one randomly selected eye of each participant, thickness measurements at the level of the macula were made of the nerve fiber layer (mRNFL), the ganglion cell layer (GCL), and the ganglion cell complex (GCC; GCL + internal plexiform layer) through automated OCT segmentation. Peripapillary RNFL thickness (pRNFL) also was determined using the conventional scan. RESULTS: As the only variable showing intergroup variation, mRNFL in the glaucoma suspects was significantly thinner in the quadrants inner inferior (P = 0.003), inner temporal (P = 0.010), and outer inferior (P = 0.017). The variable best able to discriminate between the two groups was inner inferior mRNFL thickness, as indicated by an area below the receiver operating characteristic (ROC) curve of 0.742. CONCLUSIONS: Macular RNFL thickness measurements showed an improved diagnostic capacity over the other variables examined to distinguish between healthy subjects and glaucoma suspects.