• Adherence to Fixed-Combination Versus Unfixed Travoprost 0.004%/Timolol 0.5% for Glaucoma or Ocular Hypertension: A Randomized Trial

      Barnebey, H.S.; Robin, A.L. (Elsevier Inc., 2017)
      Purpose: To assess adherence to treatment with fixed-combination travoprost 0.004%/timolol 0.5% (TTFC) compared with separate containers of travoprost 0.004% and timolol 0.5% (TRAV+TIM; unfixed) using electronic dosing aids. Design: Randomized, controlled, observer-masked clinical trial. Methods: SETTING: Two US clinical sites. PATIENT POPULATION: Eligible patients were adults diagnosed with open-angle glaucoma or ocular hypertension. Patients (n = 81) were sequentially randomized 1:1 to receive TTFC or TRAV+TIM for 12 months. INTERVENTION: TTFC was administered once daily in the morning or evening with a single dosing aid. Patients randomized to TRAV+TIM administered TRAV once daily in the evening and TIM once daily in the morning using separate dosing aids. MAIN OUTCOME MEASURE: Adherence with administered medication, as recorded by the dosing aids. Results: Mean ± SD patient age was 60 ± 10 years; most patients were male and white. Compared with TRAV+TIM (n = 40), patients receiving TTFC (n = 41) were consistently adherent on a greater percentage of days through month 12 (60% vs 43%). At months 1, 3, 6, and 12, 80% adherence was achieved by 71% vs 38%, 53% vs 30%, 45% vs 16%, and 32% vs 11% of patients receiving TTFC vs TRAV+TIM, respectively. Significantly more patients were adherent on ?80% of days with TTFC compared with TRAV+TIM (P < .001 to P = .041). Both treatments reduced IOP from baseline, and no safety issues were identified in either group. Ocular hyperemia was the most common treatment-related adverse event (n = 3/group). Conclusions: Patients receiving TTFC maintained better treatment adherence compared with patients receiving TRAV+TIM through 12 months of on-therapy evaluation. This suggests that, for patients requiring multiple IOP-lowering medications, a fixed combination may provide improved long-term adherence compared with unfixed therapy. Copyright 2016 The Author(s)
    • An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis

      Wang, M.; Shen, L.Q.; Pasquale, L.R. (Association for Research in Vision and Ophthalmology, 2019)
      Purpose: To detect visual field (VF) progression by analyzing spatial pattern changes. Methods: We selected 12,217 eyes from 7360 patients with at least five reliable 24-2 VFs and 5 years of follow-up with an interval of at least 6 months. VFs were decomposed into 16 archetype patterns previously derived by artificial intelligence techniques. Linear regressions were applied to the 16 archetype weights of VF series over time. We defined progression as the decrease rate of the normal archetype or any increase rate of the 15 VF defect archetypes to be outside normal limits. The archetype method was compared with mean deviation (MD) slope, Advanced Glaucoma Intervention Study (AGIS) scoring, Collaborative Initial Glaucoma Treatment Study (CIGTS) scoring, and the permutation of pointwise linear regression (PoPLR), and was validated by a subset of VFs assessed by three glaucoma specialists. Results: In the method development cohort of 11,817 eyes, the archetype method agreed more with MD slope (kappa: 0.37) and PoPLR (0.33) than AGIS (0.12) and CIGTS (0.22). The most frequently progressed patterns included decreased normal pattern (63.7%), and increased nasal steps (16.4%), altitudinal loss (15.9%), superior-peripheral defect (12.1%), paracentral/central defects (10.5%), and near total loss (10.4%). In the clinical validation cohort of 397 eyes with 27.5% of confirmed progression, the agreement (kappa) and accuracy (mean of hit rate and correct rejection rate) of the archetype method (0.51 and 0.77) significantly (P < 0.001 for all) outperformed AGIS (0.06 and 0.52), CIGTS (0.24 and 0.59), MD slope (0.21 and 0.59), and PoPLR (0.26 and 0.60). Conclusions: The archetype method can inform clinicians of VF progression patterns.
    • Cell - Vessel Mismatch in Glaucoma: Correlation of Ganglion Cell Layer Soma and Capillary Densities

      Villanueva, Ricardo; Le, Christopher; Liu, Zhuolin; Zhang, Furu; Magder, Laurence; Hammer, Daniel X; Saeedi, Osamah (Elsevier Inc., 2021-10-04)
      Purpose: The purpose of this study was to characterize the relationship between retinal ganglion cell layer (GCL) soma density and capillary density in glaucomatous eyes. Methods: Six glaucoma subjects with known hemifield defects and 6 age-matched controls were imaged with adaptive optics – optical coherence tomography (AO-OCT) at 6 locations: 3 degrees, 6 degrees, and 12 degrees temporal to the fovea above and below the midline. GCL soma density and capillary density were measured at each location. Coefficients of determination (pseudo R2) and slopes between GCL soma and capillary density were determined from mixed-effects regressions and were compared between glaucoma and control subjects, between more and less affected hemifield in subjects with glaucoma, and between subjects with early and moderate glaucoma, both in a local, bivariate model and then a global, multivariable model controlling for eccentricity and soma size. Results: The global correlation between GCL soma and capillary density was stronger in control versus subjects with glaucoma (R2 = 0.59 vs. 0.22), less versus more affected hemifields (R2 = 0.55 vs. 0.01), and subjects with early versus moderate glaucoma subjects (R2 = 0.44 vs. 0.18). When controlling for eccentricity and soma size, we noted an inverse soma-capillary density local relationship in subjects with glaucoma (−388 ± 190 cells/mm2 per 1% change in capillary density, P = 0.046) and more affected hemifields (−602 ± 257 cells/mm2 per 1% change in capillary density, P = 0.03). Conclusions: An inverted soma-capillary density local relationship in areas affected by glaucoma potentially explains weaker global correlations observed between GCL soma and capillary density, suggesting cell–vessel mismatch is associated with the disease.
    • Delineation of novel compound heterozygous variants in LTBP2 associated with juvenile open angle glaucoma

      Saeedi, O.; Yousaf, S.; Tsai, J. (MDPI AG, 2018)
      Juvenile open angle glaucoma (JOAG), which is an uncommon form of primary open angle glaucoma, is a clinically and genetically heterogeneous disorder. We report on a family with a recessively inherited form of JOAG. The proband has a superior and an inferior never fiber layer thinning in both the eyes and the nasal visual field (VF) defects in the left eye, which are clinical findings consistent with glaucomatous optic neuropathy. Whole exome sequencing revealed two novel compound heterozygous variants [c.2966C>G, p.(Pro989Arg); c.5235T>G, p.(Asn1745Lys)] in latent transforming growth factor-beta-binding protein 2 (LTBP2) segregating with the phenotype. Both these variants are predicted to replace evolutionary conserved amino acids, have a pathogenic effect on the encode protein, and have very low frequencies in the control databases. Mutations in LTBP2 are known to cause the Weill-Marchesani syndrome and a Weill-Marchesani-like syndrome, which include glaucoma in their clinical presentation. However, to our knowledge, this is the first published case of a JOAG subject associated with recessively inherited variants of LTPB2 and, thus, expands the repertoire of the known genetic causes of JOAG and the phenotypic spectrum of LTBP2 alleles. Copyright 2018 by the authors. Licensee MDPI, Basel, Switzerland.
    • Development and Comparison of Machine Learning Algorithms to Determine Visual Field Progression

      Saeedi, Osamah; Boland, Michael V; D'Acunto, Loris; Swamy, Ramya; Hegde, Vikram; Gupta, Surabhi; Venjara, Amin; Tsai, Joby; Myers, Jonathan S; Wellik, Sarah R; et al. (Association for Research in Vision and Ophthalmology, Inc., 2021-06-22)
      PURPOSE: To develop and test machine learning classifiers (MLCs) for determining visual field progression. METHODS: In total, 90,713 visual fields from 13,156 eyes were included. Six different progression algorithms (linear regression of mean deviation, linear regression of the visual field index, Advanced Glaucoma Intervention Study algorithm, Collaborative Initial Glaucoma Treatment Study algorithm, pointwise linear regression [PLR], and permutation of PLR) were applied to classify each eye as progressing or stable. Six MLCs were applied (logistic regression, random forest, extreme gradient boosting, support vector classifier, convolutional neural network, fully connected neural network) using a training and testing set. For MLC input, visual fields for a given eye were divided into the first and second half and each location averaged over time within each half. Each algorithm was tested for accuracy, sensitivity, positive predictive value, and class bias with a subset of visual fields labeled by a panel of three experts from 161 eyes. RESULTS: MLCs had similar performance metrics as some of the conventional algorithms and ranged from 87% to 91% accurate with sensitivity ranging from 0.83 to 0.88 and specificity from 0.92 to 0.96. All conventional algorithms showed significant class bias, meaning each individual algorithm was more likely to grade uncertain cases as either progressing or stable (P ≤ 0.01). Conversely, all MLCs were balanced, meaning they were equally likely to grade uncertain cases as either progressing or stable (P ≥ 0.08). CONCLUSIONS: MLCs showed a moderate to high level of accuracy, sensitivity, and specificity and were more balanced than conventional algorithms. TRANSLATIONAL RELEVANCE: MLCs may help to determine visual field progression.
    • The effect of a short animated educational video on knowledge among glaucoma patients

      Al Owaifeer, A.M.; Alrefaie, S.M.; Al Taisan, A.A. (Dove Medical Press Ltd, 2018)
      Purpose: To evaluate the effectiveness of an educational video in increasing knowledge among glaucoma patients and to determine the factors that may influence a patient's level of knowledge. Patients and methods: This was a pre-post intervention study on adult glaucoma patients attending the outpatient service at King Khaled Eye Specialist Hospital. The intervention tested was a short educational video that was edited specifically for this study. All patients completed a pre-video and post-video knowledge questionnaire; moreover, sociodemographic and clinical characteristics were obtained. Results: The total number of patients included was 196. The mean age of patients was 55.7±15.5 years. Overall, 55.1% were males, 29.6% were illiterate, 85.2% resided in an urban area, 62.8% had a low income, and 41.8% were unemployed. The mean pre-intervention knowledge score was 6 out of 17, and the post-intervention score was 11.1 (P?0.001). Predictors of a poor knowledge score were old age (>60 years), female sex, illiteracy, rural residence, low income, unemployment, and a negative family history of glaucoma. Conclusion: The evaluated video intervention was effective in a short-term increase in knowledge among glaucoma patients. This tool may serve as an alternative to traditional educational methods. Copyright 2018 Al Owaifeer et al.
    • Novel application of long short-term memory network for 3d to 2d retinal vessel segmentation in adaptive optics— optical coherence tomography volumes

      Le, Christopher T.; Wang, Dongyi; Villanueva, Ricardo; Liu, Zhuolin; Hammer, Daniel X.; Tao, Yang; Saeedi, Osamah J. (MDPI AG, 2021-10-12)
      Adaptive optics—optical coherence tomography (AO-OCT) is a non-invasive technique for imaging retinal vascular and structural features at cellular-level resolution. Whereas retinal blood vessel density is an important biomarker for ocular diseases, particularly glaucoma, automated blood vessel segmentation tools in AO-OCT have not yet been explored. One reason for this is that AO-OCT allows for variable input axial dimensions, which are not well accommodated by 2D-2D or 3D-3D segmentation tools. We propose a novel bidirectional long short-term memory (LSTM)-based network for 3D-2D segmentation of blood vessels within AO-OCT volumes. This technique incorporates inter-slice connectivity and allows for variable input slice numbers. We com-pare this proposed model to a standard 2D UNet segmentation network considering only volume projections. Furthermore, we expanded the proposed LSTM-based network with an additional UNet to evaluate how it refines network performance. We trained, validated, and tested these architectures in 177 AO-OCT volumes collected from 18 control and glaucoma subjects. The LSTM-UNet has statistically significant improvement (p < 0.05) in AUC (0.88) and recall (0.80) compared to UNet alone (0.83 and 0.70, respectively). LSTM-based approaches had longer evaluation times than the UNet alone. This study shows that a bidirectional convolutional LSTM module improves standard automated vessel segmentation in AO-OCT volumes, although with higher time cost. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.