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Glaucoma is the leading cause of blindness throughout the world (after cataracts); therefore, general physicians should be familiar with the diagnosis and management of affected patients. Glaucomas are usually categorized by the anatomy of the anterior chamber angle (open vs narrow/closed), rapidity of onset (acute vs chronic), and major etiology (primary vs secondary). Most glaucomas are primary (ie, without a contributing comorbidity); however, several coexisting ophthalmic conditions may serve as the underlying etiologies of secondary glaucomas. Chronic glaucoma occurs most commonly; thus, regular eye examinations should be performed in at-risk patients to prevent the insidious loss of vision that can develop before diagnosis. Glaucoma damages the optic nerve and retinal nerve fiber layer, leading to peripheral and central visual field defects. Elevated intraocular pressure (IOP), a crucial determinant of disease progression, remains the only modifiable risk factor; thus, all current treatments (medications, lasers, and operations) aim to reduce the IOP. Pharmacotherapy is the usual first-line therapy, but noncompliance, undesirable adverse effects, and cost limit effectiveness. Laser and surgical treatments may lower IOP significantly over long periods and may be more cost effective than pharmacotherapy, but they are plagued by greater procedural risks and frequent treatment failures. Traditional incisional procedures have recently been replaced by several novel, minimally invasive glaucoma surgeries with improved safety profiles and only minimal decreases in efficacy. Minimally invasive glaucoma surgeries have dramatically transformed the surgical management of glaucoma; nevertheless, large, randomized trials are required to assess their long-term efficacy.
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Purpose: Vivid Vision Perimetry (VVP; Vivid Vision, Inc) is a novel method for performing in-office and home-based visual field assessment using a virtual reality platform and oculokinetic perimetry. Here we examine the reproducibility of VVP Swift and compare results with conventional standard automated perimetry (SAP) and spectral-domain (SD) OCT. Design: Cross-sectional study. Participants: Fourteen eyes of 7 patients with open-angle glaucoma (OAG) (average age, 64.6 years; 29% women) and 10 eyes of 5 patients with suspected glaucoma (average age, 61.8 years; 40% women) were enrolled. Methods: Patients with OAG and suspected glaucoma were enrolled prospectively and underwent 2 VVP Swift examinations. Results were compared with 1 conventional SAP examination (Humphrey Visual Field [HVF]; Zeiss) and 1 SD OCT examination. Main Outcome Measures: Mean sensitivity (in decibels) obtained for each eye in 2 VVP Swift test sessions and a conventional SAP examination, thickness of the retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) for the SD OCT examination, and mean test durations of the VVP Swift and SAP examinations. Results: The mean test duration of VVP Swift in both eyes (8.5 minutes) was significantly shorter (P < 0.001) than SAP (12.2 minutes). The average absolute difference of the mean sensitivity between the 2 VVP Swift sessions was found to be 0.73 dB (95% confidence interval [CI], 0.40-1.06). A statistically significant association was found between average mean sensitivity measurements from the VVP and mean deviation (MD) measurements obtained by the HVF with a Pearson correlation coefficient of 0.86 (95% CI, 0.70-0.94; P < 0.001). Mean visual sensitivity measurements from the VVP Swift test were significantly associated with average RNFL thickness (r = 0.66; P = 0.014) and GCC thickness (r = 0.63; P = 0.02), whereas the correlation coefficients between HVF MD and RNFL and GCC were 0.86 (P < 0.001) and 0.83 (P < 0.001), respectively. Conclusions: Our results demonstrated that the VVP Swift test can generate reproducible results and is comparable with conventional SAP. This suggests that the device can be used by clinicians to assess visual function in glaucoma.
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Purpose: To assess whether the predictive accuracy of machine learning algorithms using Kalman filtering for forecasting future values of global indices on perimetry can be enhanced by adding global retinal nerve fiber layer (RNFL) data and whether model performance is influenced by the racial composition of the training and testing sets. Design: Retrospective, longitudinal cohort study. Participants: Patients with open-angle glaucoma (OAG) or glaucoma suspects enrolled in the African Descent and Glaucoma Evaluation Study or Diagnostic Innovation in Glaucoma Study. Methods: We developed a Kalman filter (KF) with tonometry and perimetry data (KF-TP) and another KF with tonometry, perimetry, and global RNFL data (KF-TPO), comparing these models with one another and with 2 linear regression (LR) models for predicting mean deviation (MD) and pattern standard deviation values 36 months into the future for patients with OAG and glaucoma suspects. We also compared KF model performance when trained on individuals of European and African descent and tested on patients of the same versus the other race. Main Outcome Measures: Predictive accuracy (percentage of MD values forecasted within the 95% repeatability interval) differences among the models. Results: Among 362 eligible patients, the mean ± standard deviation age at baseline was 71.3 ± 10.4 years; 196 patients (54.1%) were women; 202 patients (55.8%) were of European descent, and 139 (38.4%) were of African descent. Among patients with OAG (n = 296), the predictive accuracy for 36 months in the future was higher for the KF models (73.5% for KF-TP, 71.2% for KF-TPO) than for the LR models (57.5%, 58.0%). Predictive accuracy did not differ significantly between KF-TP and KF-TPO (P = 0.20). If the races of the training and testing set patients were aligned (versus nonaligned), the mean absolute prediction error of future MD improved 0.39 dB for KF-TP and 0.48 dB for KF-TPO. Conclusions: Adding global RNFL data to existing KFs minimally improved their predictive accuracy. Although KFs attained better predictive accuracy when the races of the training and testing sets were aligned, these improvements were modest. These findings will help to guide implementation of KFs in clinical practice.
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Background: Statins, the first-line therapy for hyperlipidemia, have received considerable attention as candidates for glaucoma treatments given its neuroprotective effects. In this systematic review and meta-analysis, we intended to assess the association of statin use with the onset and progression of open-angle glaucoma (OAG). Methods: Databases including PubMed, Embase and Web of Science Core Collection were searched for longitudinal studies reporting the association between statin use and OAG onset or progression on Feb 3, 2021. A meta-analysis was performed for the association between statin use and OAG onset. Relative risks (RRs) with 95% confidential intervals (CIs) were retrieved from included studies and pooled using random-effects models. Potential risks of bias were evaluated by the Newcastle-Ottawa Quality Assessment Scale for all eligible studies. This study had been registered on PROSPERO (CRD 42021232172). Findings: 515,788 participants (mean age 68.7 years, 62.3% female) from ten studies were included in the systematic review of the association between statin use and OAG onset, and 26,347 OAG patients (mean age 67.3 years, 52.2% female) from seven studies were included for the association between statin use and OAG progression. Potential risks of bias were detected in 12 studies, which were mainly attributed to selection and confounding bias. In addition, 515,600 participants from eight studies were included in the meta-analysis which collectively showed that statin use was associated with a reduced risk of OAG onset (Pooled RR: 0.95; 95%CI: 0.93-0.98; I2=0.199;). No significant heterogeneity or publication bias was found for studies included in the meta-analysis. There were inconsistent evidences for the association between statin use and OAG progression. Interpretation: Statin use is associated with a slightly lower risk of OAG onset based on existing evidences from longitudinal observational studies, the association between statin use and OAG progression remains inconclusive. The included evidences were typically weak due to poor study design and under-powered studies. Current findings should be interpreted cautiously and still need to be validated in further research. Funding: The National Key R&D Program of China (2018YFC0116500), Science and Technology Planning Project of Guangdong Province (2013B20400003), the China Postdoctoral Science Foundation (2019TQ0365), the National Natural Science Foundation of China (82000901 and 82101171).
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Purpose: We constructed a multitask learning model (latent space linear regression and deep learning [LSLR-DL]) in which the 2 tasks of cross-sectional predictions (using OCT) of visual field (VF; central 10°) and longitudinal progression predictions of VF (30°) were performed jointly via sharing the deep learning (DL) component such that information from both tasks was used in an auxiliary manner (The Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining [SIGKDD] 2021). The purpose of the current study was to investigate the prediction accuracy preparing an independent validation dataset. Design: Cohort study. Participants: Cross-sectional training and testing data sets included the VF (Humphrey Field Analyzer [HFA] 10-2 test) and an OCT measurement (obtained within 6 months) from 591 eyes of 351 healthy people or patients with open-angle glaucoma (OAG) and from 155 eyes of 131 patients with OAG, respectively. Longitudinal training and testing data sets included 7984 VF results (HFA 24-2 test) from 998 eyes of 592 patients with OAG and 1184 VF results (HFA 24-2 test) from 148 eyes of 84 patients with OAG, respectively. Each eye had 8 VF test results (HFA 24-2 test). The OCT sequences within the observation period were used. Methods: Root mean square error (RMSE) was used to evaluate the accuracy of LSLR-DL for the cross-sectional prediction of VF (HFA 10-2 test). For the longitudinal prediction, the final (eighth) VF test (HFA 24-2 test) was predicted using a shorter VF series and relevant OCT images, and the RMSE was calculated. For comparison, RMSE values were calculated by applying the DL component (cross-sectional prediction) and the ordinary pointwise linear regression (longitudinal prediction). Main Outcome Measures: Root mean square error in the cross-sectional and longitudinal predictions. Results: Using LSLR-DL, the mean RMSE in the cross-sectional prediction was 6.4 dB and was between 4.4 dB (VF tests 1 and 2) and 3.7 dB (VF tests 1-7) in the longitudinal prediction, indicating that LSLR-DL significantly outperformed other methods. Conclusions: The results of this study indicate that LSLR-DL is useful for both the cross-sectional prediction of VF (HFA 10-2 test) and the longitudinal progression prediction of VF (HFA 24-2 test).
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Purpose: To evaluate macular pigment response to carotenoid supplementation in glaucomatous eyes. Design: Double-masked, randomized, placebo-controlled clinical trial, the European Nutrition in Glaucoma Management Study (ClinicalTrials.gov identifier, NCT04460365). Participants: Sixty-two participants (38 men, 24 women) with a diagnosis of open-angle glaucoma were enrolled. Forty-two were randomized to receive the active supplement, 20 participants were allocated to placebo. Methods: Macular pigment optical density (MPOD) was measured by autofluorescence using the Heidelberg Spectralis scanning laser ophthalmoscope. Macular pigment optical density volume within the central 6° of retinal eccentricity as well as MPOD at 0.23°, 0.51°, 0.74°, and 1.02° were recorded at baseline and at 6-month intervals over 18 months. Visual function was assessed using visual acuity, mesopic and photopic contrast sensitivity under glare conditions, photo stress recovery time, microperimetry, and Glaucoma Activities Limitation 9 questionnaire. Advanced glaucoma module scans of retinal nerve fiber layer thickness and ganglion cell complex thickness over the central 6° of retinal eccentricity also were completed at each study visit. Main Outcome Measures: Change in MPOD after supplementation with 10 mg lutein, 2 mg zeaxanthin, and 10 mg meso-zeaxanthin or placebo over 18 months. Results: A mixed-model repeated measures analysis of variance revealed a statistically significant increase in MPOD volume (significant time effect: F(3,111) = 89.31, mean square error (MSE) = 1656.9; P < 0.01). Post hoc t tests revealed a significant difference in MPOD volume at each study visit for the treatment group (P < 0.01 for all), but no change in the placebo group (P > 0.05 for all). A statistically significant increase in mesopic contrast sensitivity under glare conditions was noted at 18 months in the treatment group, but not placebo. No other structural or functional changes were observed. No serious adverse events were noted during the trial. Conclusions: Macular pigment can be augmented in glaucomatous eyes by supplementation with a formulation containing the carotenoids lutein, zeaxanthin, and meso-zeaxanthin. The greatest relative benefit was observed in those with the lowest baseline levels, but increases were noted across all participants and each retinal eccentricity. The potential benefits of MP augmentation for macular health in glaucoma merit further long-term evaluation.