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Efficacy of Conversion to Aflibercept for Diabetic Macular Edema Previously Refractory to Bevacizumab or Ranibizumab: A Meta-analysis of High-Quality Nonrandomized Studies.
Xiao, K, Li, FZ, Liang, SZ, Wang, J, Qian, C, Wan, GM
The Annals of pharmacotherapy. 2020;(8):750-756
Abstract
Background: Aflibercept has been widely used in treating diabetic macular edema (DME). However, the effect of aflibercept in treating DME refractory to bevacizumab or ranibizumab has not been well established. Objective: To assess the therapeutic effect of switching from bevacizumab or ranibizumab to aflibercept in the treatment of refractory DME. Methods: Relevant studies were searched from 3 databases: the Cochrane Library, PubMed, and Web of Science. Data on changes in best-corrected visual acuity (BCVA), central macular thickness (CMT), and adverse events within the follow-up period were collected and pooled using weighted mean differences (WMDs) with corresponding 95% CIs in a random effects model. The between-study heterogeneity was tested using the χ2 test and the I2 statistic, and funnel plots were used to evaluate the publication bias. Results: A total of 11 nonrandomized trials met the inclusion criteria and were included in the meta-analysis. Our studies showed significant improvements in the BCVA (WMD = 100.55; 95% CI = 68.46 to 132.63; P < 0.01) and reduction in CMT (WMD = 0.09; 95% CI = 0.03 to 0.14; P < 0.01) after switching to aflibercept. Although a large amount of heterogeneity was detected in the CMT results among these studies, the sensitivity analyses showed the reliability and stability of our results. Conclusion and Relevance: There were significant improvements in both visual and anatomical outcomes after switching from bevacizumab or ranibizumab to aflibercept, without risk of adverse events. Thus, switching therapy may be a safe and effective treatment for patients with refractory DME.
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Segmenting Diabetic Retinopathy Lesions in Multispectral Images Using Low-Dimensional Spatial-Spectral Matrix Representation.
He, Y, Jiao, W, Shi, Y, Lian, J, Zhao, B, Zou, W, Zhu, Y, Zheng, Y
IEEE journal of biomedical and health informatics. 2020;(2):493-502
Abstract
Multispectral imaging (MSI) provides a sequence of en-face fundus spectral slices and allows for the examination of structures and signatures throughout the thickness of retina to characterize diabetic retinopathy (DR) lesions comprehensively. Manual interpretation of MSI images is commonly conducted by qualitatively analyzing both the spatial and spectral properties of multiple spectral slices. Meanwhile, there exist few computer-based algorithms that can effectively exploit the spatial and spectral information of MSI images for the diagnosis of DR. We propose a new approach that can quantify the spatial-spectral features of MSI retinal images for automatic DR lesion segmentation. It combines a generalized low-rank approximation of matrices with a supervised regularization term to generate low-dimensional spatial-spectral representations using the feature vectors in all spectral slices. Experimental results showed that the proposed approach is very effective for the segmentation of DR lesions in MSI images, which suggests it as an interesting tool for assisting ophthalmologists in diagnosing, analyzing, and managing DR lesions in MSI.
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Deep learning algorithms for detection of diabetic retinopathy in retinal fundus photographs: A systematic review and meta-analysis.
Islam, MM, Yang, HC, Poly, TN, Jian, WS, Jack Li, YC
Computer methods and programs in biomedicine. 2020;:105320
Abstract
BACKGROUND Diabetic retinopathy (DR) is one of the leading causes of blindness globally. Earlier detection and timely treatment of DR are desirable to reduce the incidence and progression of vision loss. Currently, deep learning (DL) approaches have offered better performance in detecting DR from retinal fundus images. We, therefore, performed a systematic review with a meta-analysis of relevant studies to quantify the performance of DL algorithms for detecting DR. METHODS A systematic literature search on EMBASE, PubMed, Google Scholar, Scopus was performed between January 1, 2000, and March 31, 2019. The search strategy was based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines, and DL-based study design was mandatory for articles inclusion. Two independent authors screened abstracts and titles against inclusion and exclusion criteria. Data were extracted by two authors independently using a standard form and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was used for the risk of bias and applicability assessment. RESULTS Twenty-three studies were included in the systematic review; 20 studies met inclusion criteria for the meta-analysis. The pooled area under the receiving operating curve (AUROC) of DR was 0.97 (95%CI: 0.95-0.98), sensitivity was 0.83 (95%CI: 0.83-0.83), and specificity was 0.92 (95%CI: 0.92-0.92). The positive- and negative-likelihood ratio were 14.11 (95%CI: 9.91-20.07), and 0.10 (95%CI: 0.07-0.16), respectively. Moreover, the diagnostic odds ratio for DL models was 136.83 (95%CI: 79.03-236.93). All the studies provided a DR-grading scale, a human grader (e.g. trained caregivers, ophthalmologists) as a reference standard. CONCLUSION The findings of our study showed that DL algorithms had high sensitivity and specificity for detecting referable DR from retinal fundus photographs. Applying a DL-based automated tool of assessing DR from color fundus images could provide an alternative solution to reduce misdiagnosis and improve workflow. A DL-based automated tool offers substantial benefits to reduce screening costs, accessibility to healthcare and ameliorate earlier treatments.
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Dilatation of Retinal Arterioles Induced by Topical Dorzolamide for One Week Is Impaired in Patients with Type 1 Diabetes and Mild Retinopathy.
Tilma, KK, Bek, T
Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde. 2020;(3):236-242
Abstract
BACKGROUND Diabetic retinopathy is characterised by morphological lesions in the retina secondary to disturbances in retinal blood flow. Previous studies have shown that the carbonic anhydrase inhibitor (CAI) dorzolamide can induce immediate dilatation of retinal arterioles and a sustained increase in retinal blood flow in primary open-angle glaucoma. However, the effect of sustained treatment with CAI on retinal arterioles in normal persons and in patients with diabetic retinopathy is unknown. METHODS The Dynamic Vessel Analyzer was used to assess the baseline diameter and the diameter response of retinal arterioles during an increase in arterial blood pressure induced by isometric exercise and during flicker stimulation before and 2 h, 24 h and 1 week after onset of topical treatment with dorzolamide. At each examination the diameter responses were studied before and during breathing in of a hypercapnic gas mixture. RESULTS Treatment with dorzolamide for 1 week significantly increased the diameter of retinal arterioles in normal persons, and breathing in of a hypercapnic gas mixture reduced this response. The pathological vasodilatation and reduced retinal autoregulation in patients with diabetic retinopathy were unaffected by dorzolamide and hypercapnia. CONCLUSIONS The study suggests a lack of relevance of CAI for the treatment of pathological vasodilatation in early diabetic retinopathy.
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Interaction Between the Distribution of Diabetic Retinopathy Lesions and the Association of Optical Coherence Tomography Angiography Scans With Diabetic Retinopathy Severity.
Ashraf, M, Sampani, K, Rageh, A, Silva, PS, Aiello, LP, Sun, JK
JAMA ophthalmology. 2020;(12):1291-1297
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IMPORTANCE Studies have not yet determined whether the distribution of lesions in the retinal periphery alters the association between the severity of diabetic retinopathy (DR) and macular vessel density. OBJECTIVE To evaluate the association of DR lesion distribution with optical coherence tomography angiography (OCTA) metrics and DR severity. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional observational study was conducted at a tertiary care center for diabetic eye disease among 225 patients with type 1 or 2 diabetes who had undergone imaging between February 15, 2016, and December 31, 2019. EXPOSURES Optical coherence tomography angiography 3 × 3-mm macular scans and ultra-widefield color imaging. MAIN OUTCOMES AND MEASURES Optical coherence tomography angiography vessel density in the superficial capillary plexus, intermediate capillary plexus, and deep capillary plexus and choriocapillaris flow density. The severity of DR and the predominantly peripheral lesions (PPL) were evaluated from ultra-widefield color imaging. RESULTS The study evaluated 352 eyes (225 patients; 125 men [55.6%]; mean [SD] age, 52.1 [15.1] years), of which 183 eyes (52.0%) had mild nonproliferative diabetic retinopathy (NPDR), 71 eyes (20.2%) had moderate NPDR, and 98 eyes (27.8%) had severe NPDR or proliferative diabetic retinopathy (PDR). In eyes with no PPL (209 [59.4%]), the mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 38.1% [4.7%]; moderate NPDR, 36.4% [4.6%]; severe NPDR or PDR, 34.1% [4.1%]; P < .001) and the deep capillary plexus (mild NPDR, 45.8% [3.0%]; moderate NPDR, 45.8% [2.2%]; severe NPDR or PDR, 44.5% [1.9%]; P = .002), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 69.7% [6.2%]; moderate NPDR, 67.6% [5.6%]; severe NPDR or PDR, 67.1% [5.6%]; P = .01), decreased with increasing DR severity. These associations remained statistically significant even after correcting for age, signal strength index, spherical equivalent, duration of diabetes, type of diabetes, and correlation between eyes of the same patient. In eyes with PPL (143 [40.6%]), mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 34.1% [4.1%]; moderate NPDR, 35.2% [4.1%]; severe NPDR or PDR, 36.0% [4.3%]; P = .42) and the deep capillary plexus (mild NPDR, 44.5% [1.7%]; moderate NPDR, 45.4% [1.4%]; severe NPDR or PDR, 44.9% [1.5%]; P = .81), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 67.1% [5.6%]; moderate NPDR, 69.3% [4.6%]; severe NPDR or PDR, 68.3% [5.6%]; P = .49), did not appear to change with increasing DR severity. CONCLUSIONS AND RELEVANCE These results suggest that central retinal vessel density is associated with DR severity in eyes without, but not with, PPL. These findings suggest a potential need to stratify future optical coherence tomography angiography studies of eyes with DR by the presence or absence of PPL. If DR onset and worsening are associated with the location of retinal nonperfusion, assessment of global retinal nonperfusion using widefield angiography may improve the ability to evaluate DR severity and risk of DR worsening over time.
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Fundamental principles of an effective diabetic retinopathy screening program.
Lanzetta, P, Sarao, V, Scanlon, PH, Barratt, J, Porta, M, Bandello, F, Loewenstein, A, ,
Acta diabetologica. 2020;(7):785-798
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BACKGROUND Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults worldwide. Early detection and treatment are necessary to forestall vision loss from DR. METHODS A working group of ophthalmic and diabetes experts was established to develop a consensus on the key principles of an effective DR screening program. Recommendations are based on analysis of a structured literature review. RESULTS The recommendations for implementing an effective DR screening program are: (1) Examination methods must be suitable for the screening region, and DR classification/grading systems must be systematic and uniformly applied. Two-field retinal imaging is sufficient for DR screening and is preferable to seven-field imaging, and referable DR should be well defined and reliably identifiable by qualified screening staff; (2) in many countries/regions, screening can and should take place outside the ophthalmology clinic; (3) screening staff should be accredited and show evidence of ongoing training; (4) screening programs should adhere to relevant national quality assurance standards; (5) studies that use uniform definitions of risk to determine optimum risk-based screening intervals are required; (6) technology infrastructure should be in place to ensure that high-quality images can be stored securely to protect patient information; (7) although screening for diabetic macular edema (DME) in conjunction with DR evaluations may have merit, there is currently insufficient evidence to support implementation of programs solely for DME screening. CONCLUSION Use of these recommendations may yield more effective DR screening programs that reduce the risk of vision loss worldwide.
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Evaluation of different Swept'Source optical coherence tomography angiography (SS-OCTA) slabs for the detection of features of diabetic retinopathy.
Tian, M, Wolf, S, Munk, MR, Schaal, KB
Acta ophthalmologica. 2020;(4):e416-e420
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PURPOSE To compare different Swept-Source optical coherence tomography angiography (SS-OCTA) slabs for the detection of features of diabetic retinopathy (DR), to find the most suitable slab for grading. METHODS Retrospective cross-sectional study. Consecutive patients with DR were evaluated using SS-OCTA. The central 12 × 12 mm scan was used to generate the retinal, superficial and deep slab. The grading results of the slabs were then compared to determine if one specific slab is superior to detect respective features. RESULTS A total of 348 eyes (190 patients; mean age 58.1 ± 14.5 years) were graded for features of DR. The retinal slab detected most frequently MAs and IRMAs, however with no significant difference compared to the superficial slab (p = 0.93 and p = 0.93, respectively). Small capillary dropout was most frequently found on the superficial slab, but there was no significant difference compared with the retinal (p = 0.78) and deep slab (p = 0.45). The only statistically significant difference was found for large capillary dropout, where the retinal and superficial slab showed a higher detection rate compared with the deep slab (p ≤ 0.0001 and p = 0.001, respectively). CONCLUSIONS The superficial and retinal slabs are equally suitable for grading with no statistically significant difference in the detection rate of the diabetic features examined.
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Randomized Safety and Feasibility Trial of Ultra-Rapid Cooling Anesthesia for Intravitreal Injections.
Besirli, CG, Smith, SJ, Zacks, DN, Gardner, TW, Pipe, KP, Musch, DC, Shah, AR
Ophthalmology. Retina. 2020;(10):979-986
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PURPOSE To test the safety and preliminary efficacy of rapid, nonpharmacologic anesthesia via cooling for intravitreal injections. DESIGN Single-center, randomized phase 1 dose-ranging safety study (ClinicalTrials.gov identifier, NCT02872012). PARTICIPANTS Adults 18 years of age or older with a diagnosis of exudative macular degeneration or diabetic macular edema requiring bilateral anti-vascular endothelial growth factor therapy were included. METHODS A handheld device was developed to provide anesthesia via cooling to a focal area on the surface of the eye before intravitreal treatment (IVT). In 22 patients undergoing bilateral IVT, 1 eye was randomized to receive standard of care (SOC) lidocaine-based anesthesia and the other eye received cooling-anesthesia at 1 of 5 different temperatures and cooling times. Subjective pain was assessed via the visual analog scale (VAS; range, 1-10) at 2 time points: (1) immediately after IVT and (2) 4 hours after IVT. Treated eyes were assessed for ocular safety 24 hours after IVT. MAIN OUTCOME MEASURES We determined the occurrence of adverse events in eyes treated with cooling anesthesia. Mean VAS pain scores immediately after IVT and 4 hours after IVT in eyes receiving cooling anesthesia were compared with eyes receiving SOC. RESULTS A total of 44 eyes were treated, 22 with cooling anesthesia and 22 with SOC. No dose-related toxicity was found with cooling anesthesia. Mild, transient adverse events were recorded in 32% of patients treated with cooling anesthesia versus 44% of patients receiving SOC. The mean±standard error of the mean (SEM) VAS pain scores immediately after intravitreal injection were 2.3 ± 0.4 for patients receiving SOC and 2.2 ± 0.6 in patients receiving -10° C cooling anesthesia (P = 0.8). Mean±SEM pain scores 4 hours after injection were 1.6 ± 0.4 for SOC and 1.2 ± 0.5 in the combined -10° C arms (P = 0.56). Total mean±SEM procedure time was 124 ± 5 seconds for patients treated with cooling anesthesia versus 395 ± 40 seconds for SOC (P < 0.0001). CONCLUSIONS Ultra-rapid cooling of the eye for anesthesia was well tolerated, with -10° C treatment resulting in comparable levels of anesthesia to SOC with a reduction in procedure time.
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Risk of Death Associated With Intravitreal Anti-Vascular Endothelial Growth Factor Therapy: A Systematic Review and Meta-analysis.
Reibaldi, M, Fallico, M, Avitabile, T, Bonfiglio, V, Russo, A, Castellino, N, Parisi, G, Longo, A, Pulvirenti, A, Boscia, F, et al
JAMA ophthalmology. 2020;(1):50-57
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IMPORTANCE Although intravitreal anti-vascular endothelial growth factor (VEGF) treatment represents the first-line therapy for many retinal diseases, the issue of their systemic safety is debatable. OBJECTIVES To assess whether intravitreal anti-VEGF therapy might be associated with increased risk of mortality and which variables are associated with the increase. DATA SOURCES PubMed, MEDLINE, and Embase databases, the Cochrane Library, and ClinicalTrials.gov were systematically searched from inception to May 6, 2019. STUDY SELECTION Randomized clinical trials comparing intravitreal anti-VEGF treatment with control groups and with follow-up of at least 6 months were selected. DATA EXTRACTION AND SYNTHESIS Data were independently collected by 2 investigators. Meta-analyses were conducted using the frequentist and Bayesian methods. For the frequentist approach, random- and fixed-effects models were used, with random-effects models considered the primary technique. Odds ratios (ORs) with 95% CIs were computed. For the bayesian approach, uninformative and informative priors were used. Odds ratios with 95% credible intervals (CrIs) were computed. Meta-regression analyses were based on random-effects models. MAIN OUTCOMES AND MEASURES The primary outcome measure was the all-cause death rate. Secondary outcomes included meta-regression analyses on the following variables: type of drug, number of injections, follow-up time, diagnosis, and cardiovascular risk. RESULTS Of 2336 studies identified, 34 unique studies with 8887 unique participants were included in the present meta-analysis. For the frequentist analysis, fixed- and random-effects models yielded similar estimates (ORs, 1.34 [95% CI, 0.95-2.07; P = .09] and 1.34 [95% CI, 0.89-2.01; P = .17], respectively). For the Bayesian approach, noninformative and informative priors yielded similar results (ORs, 1.34 [95% CrI, 0.79-2.34; 0.13 probability of OR≤1.00] and 1.40 [95% CrI, 0.82-2.32; 0.11 probability of OR≤1.00], respectively). Meta-regression analyses showed the following risk for 1 injection more: frequentist OR of 1.12 (95% CI, 1.04-1.22; P = .005) and Bayesian OR of 1.06 (95% CrI, 0.98-1.15; 0.06 probability of OR≤1.00). CONCLUSIONS AND RELEVANCE In this study, no difference was found in the mortality rate between intravitreal anti-VEGF treatment and control groups. Additional data seem warranted to determine whether the mortality rate is increased in patients receiving a greater number of injections.
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Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.
Gilbert, MJ, Sun, JK
Seminars in ophthalmology. 2020;(7-8):325-332
Abstract
Background: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost certainly exceed the supply of eye care professionals to individually evaluate each patient on an annual basis, signaling the need for 21st century tools to assist our profession in meeting this challenge. Methods: Review of available literature on artificial intelligence (AI) as applied to diabetic retinopathy (DR) detection and predictionResults: The field of AI has seen exponential growth in evaluating fundus photographs for DR. AI systems employ machine learning and artificial neural networks to teach themselves how to grade DR from libraries of tens of thousands of images and may be able to predict future DR progression based on baseline fundus photographs. Conclusions: AI algorithms are highly promising for the purposes of DR detection and will likely be able to reliably predict DR worsening in the future. A deeper understanding of these systems and how they interpret images is critical as they transition from the bench into the clinic.