Importance: Predicting undesirable outcomes following anti-VEGF initiation in macular oedema is critical for effective clinical decision-making and optimised care.
Objective: To estimate the time to undesirable events in diabetic macular oedema (DMO), central and branch vein occlusions (CRVO and BRVO) after appropriate loading doses with either ranibizumab or aflibercept and identified baseline predictors of negative outcome.
Design, Setting, Participants: A retrospective cohort study of 3277 patients (N = 2107 in DMO, N = 413 in CRVO and N = 757 in BRVO) collected over a 10-year period, in a large UK tertiary centre.
Oestradiol and progesterone levels are higher in menstruating women than men of the same age, and their receptors are present in their neurosensory retina and retinal pigment epithelium. However, the impact of this hormonal environment on retinal physiology in women remains unclear. Using self-reported menstrual cycle phases as a surrogate for fluctuating hormonal levels, we investigated associations with retinovascular indices on colour fundus photograph and retinal thickness in optical coherence tomography across regularly menstruating women in the UK Biobank.
View Article and Find Full Text PDFObjective: To estimate inter-session coefficient of repeatability (CR) of visual function and OCTA metrics over 3 months in diabetic macular ischaemia (DMI) in stable laser-treated proliferative diabetic retinopathy (PDR) patients.
Methods: This prospective study recruited patients with stable PDR for at least 6 months following pan-retinal photocoagulation with visual acuity of at least 54 ETDRS letters. DMI was confirmed on OCTA as FAZ area of at least 0.
Importance: Some eyes with proliferative diabetic retinopathy (PDR) treated to stability with panretinal photocoagulation (PRP) continue to lose vision without diabetic macular edema. One presumed cause is macular capillary nonperfusion (CNP)-associated ischemia or infarction. Natural history data of macular CNP might guide treatment trials for it.
View Article and Find Full Text PDFPurpose: To evaluate if dual angiopoietin-2 (Ang-2)/VEGF-A inhibition with faricimab resulted in greater macular leakage resolution versus aflibercept in patients with diabetic macular edema (DME).
Design: Post hoc analysis of macular leakage assessments prespecified in the YOSEMITE/RHINE (NCT03622580/NCT03622593) phase III trials.
Participants: Adults with visual acuity loss due to center-involving DME.
Clinical trials investigating drugs for various stages of age-related macular degeneration (AMD) are actively underway and there is a strong interest in outcomes that demonstrate a structure-function-correlation. The ellipsoid zone (EZ), a crucial anatomical feature affected in this disease, has emerged as a strong contender. There is significant interest in evaluating EZ metrics on Optical Coherence Tomography (OCT), such as integrity and reflectivity, as disruption of this photoreceptor-rich layer may indicate disease progression.
View Article and Find Full Text PDFPurpose: The inclusion of ranibizumab biosimilars into National Health Service England commissioning recommendations published in 2022 created a need for expert guidance to optimize treatment outcomes in patients with neovascular age-related macular degeneration (nAMD) who otherwise may not have received first-line ranibizumab. This article provides a consensus treatment pathway supporting timely identification and management of a suboptimal response to these therapies, thereby aiming to facilitate clinically meaningful outcomes and efficient management of service capacity under specific circumstances where ranibizumab biosimilars may be initiated as a first-line treatment.
Methods: Two structured round-table meetings of UK medical retina specialists were held in person and virtually on September 22 and November 3, 2022, respectively.
Asia Pac J Ophthalmol (Phila)
October 2024
Aims: To identify baseline characteristics that best correlate to treatment interval for naive neovascular age-related macular degeneration patients treated with faricimab in the first year (Y1) of the TENAYA and LUCERNE phase 3 trials, and to further understand how these characteristics may impact treatment intervals.
Methods: This post-hoc analysis of Y1 data from the TENAYA and LUCERNE trials evaluated ocular baseline characteristics associated with Y1 treatment intervals. Patients were categorised into three subgroups based on their Y1 treatment interval: Q16W, Q12W or Q8W.
Purpose: Changes in the foveal avascular zone (FAZ) metrics over time are key outcome measures for clinical trials in diabetic macular ischemia (DMI). However, artifacts and automatically delineated FAZ measurements may influence the results. We aimed to compare the artifact frequency and FAZ metrics on 3 × 3 versus 6 × 6 mm optical coherence tomography angiography (OCTA) macular scans in patients with DMI.
View Article and Find Full Text PDFPurpose: To determine the association of gut microbiome diversity and sight-threatening diabetic retinopathy (STDR) amongst patients with pre-existing diabetes.
Methods: A cross-sectional study was performed, wherein 54 participants selected in total were placed into cases cohort if diagnosed with STDR and those without STDR but had a diagnosis of diabetes mellitus of at least 10-year duration were taken as controls. Statistical analysis comparing the gut microbial alpha diversity between cases and control groups as well as patients differentiated based on previously hypothesized Bacteroidetes/Firmicutes(B/F) ratio with an optimal cut-off 1.
Background/objectives: The Government of Kerala initiated a pilot screening programme for diabetic retinopathy in 16 Family Health Centres in Thiruvananthapuram district in 2019 in collaboration with the ORNATE India project. The evaluation of this pilot included a study of its costs and cost-effectiveness to inform decisions about extending the programme throughout Kerala.
Subjects/methods: The participants comprise all 5307 people who were screened for diabetic retinopathy under the pilot programme for whom data could be collected.
Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-efficient downstream image analysis. However, the direct application of conventional contrastive methods to medical datasets introduces two domain-specific issues.
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