Publications by authors named "Zarranz-Ventura J"

Practice patterns for neovascular age-related macular degeneration (nAMD) have evolved from the landmark registration trials of vascular endothelial growth factor (VEGF) inhibitors. Non-monthly regimens like treat-and-extend (T&E) have become popular due to their effectiveness in clinical practice. T&E regimens attempt to limit the burden of visits and treatments by allowing progressively longer treatment intervals, but in so doing, are potentially associated with the expense of treating quiescent disease.

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Objectives: To compare visual outcomes for low vision eyes (LVE) (<35 letters LogMAR or <20/200 Snellen) versus non-low vision eyes (NLVE) (>35 letters LogMAR or >20/200 Snellen) at the time of the first injection in a clinical practice setting.

Methods: Subgroup analysis of a multicenter national database of treatment- naïve eyes neovascular age related macular degeneration (nAMD) treated with anti-VEGF intravitreal injections divided into LVE and NLVE. Demographics, visual acuity (VA) at baseline and subsequent timepoints (12, 24, and 36 months), number of injections and visits data were collected using a validated web-based tool (Fight Retinal Blindness!).

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Several studies published so far used highly selective image datasets from unclear sources to train computer vision models and that may lead to overestimated results, while those studies conducted in real-life remain scarce. To avoid image selection bias, we stacked convolutional and recurrent neural networks (CNN-RNN) to analyze complete optical coherence tomography (OCT) cubes in a row and predict diabetic macular edema (DME), in a real-world diabetic retinopathy screening program. A retrospective cohort study was carried out.

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: To analyze the performance of custom semi-automated software for quantitative analysis of retinal capillaries in eyes with macula-off rhegmatogenous retinal detachment (RRD) and the role of these microvascular measures as potential biomarkers of postoperative visual outcomes. : A prospective, observational, and single-center study was conducted on consecutive patients who underwent 25G pars-plana vitrectomy for primary uncomplicated macula-off RRD. Optical coherence tomography angiography (OCTA) was performed in the fellow and RRD eyes before surgery and in months 1, 3, and 6 after surgery.

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Purpose: To evaluate the 3-year outcomes of VEGF inhibitors in the treatment of cystoid macular edema due to branch retinal vein occlusion (BRVO) in an international multicenter cohort of eyes.

Design: Multicenter, international, BRVO database study.

Subjects: Seven hundred forty-seven patients (760 eyes) undergoing intravitreal therapy for BRVO for 3 years in a multicenter international setting.

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Purpose: To determine and compare the serum levels of complement Factor H (FH), monomeric C-Reactive Protein (mCRP) and pentameric C-Reactive protein (pCRP) in patients with age-related macular degeneration (AMD) and to correlate them with clinical, structural and functional parameters.

Methods: Cross-sectional observational study. One hundred thirty-nine individuals (88 patients and 51 healthy controls) from two referral centers were included and classified into three groups: early or intermediate AMD (n=33), advanced AMD (n=55), and age and sex matched healthy controls (n=51).

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Purpose: The purpose of this study was to objectively evaluate the longitudinal changes observed in the retinal capillaries in eyes with macula-on rhegmatogenous retinal detachment (RRD), assessed with optical coherence tomography angiography (OCTA), and to assess the role of these microvascular measures as potential biomarkers of postoperative visual outcomes.

Methods: This was a prospective, longitudinal study conducted on consecutive patients who underwent 25 G pars plana vitrectomy for primary RRD. The vessel area density (VAD), vessel skeleton density (VSD), and vessel diameter index (VDI) were assessed in the superficial (SCP) and deep (DCP) capillary plexuses.

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To compare baseline characteristics, initial response and 12-month efficacy and safety outcomes in eyes with branch and central retinal vein occlusion (BRVO and CRVO) treated with dexamethasone implants (DEX) or anti-vascular endothelial growth factor (anti-VEGF) we performed a multi-centre, retrospective and observational study using Fight Retinal Blindness! Registry. Of 725 eligible eyes, 10% received DEX initially with very frequent adjunctive anti-VEGF (BRVO-DEX 49%, CRVO-DEX 60%). The primary outcome of mean adjusted change in VA at 12 months with DEX and anti-VEGF initiated groups were not statistically significantly different (BRVO: DEX + 6.

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Optical coherence tomography angiography (OCTA) enables three-dimensional reconstruction of the functional blood vessels in the retina. Therefore, it enables the quantification of 3D retinal vessel parameters such as surface area and vessel volume. In spite of the widespread use of OCTA, no representative volume-rendered vessel volume (VV) data are published to date.

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Purpose: To evaluate the proportion, predictors, and outcomes of patients with neovascular age-related macular degeneration (nAMD) treated with a high burden of VEGF inhibitor intravitreal (IVT) injections after 2 years in routine clinical practice.

Design: Retrospective analysis of data from a prospectively designed observational outcomes registry, the Fight Retinal Blindness! Project, of patients treated in European centers.

Participants: Treatment-naïve eyes (1 eye per patient) starting VEGF inhibitors for nAMD from January 2017 to March 2020 with 24 months of follow-up.

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Purpose: To evaluate the influence of macular neovascularization (MNV) lesion type on 12-month clinical outcomes in treatment-naive eyes with neovascular age-related macular degeneration (nAMD) treated with anti-VEGF drugs nationwide.

Design: Multicenter national nAMD database observational study.

Subjects: One thousand six hundred six treatment-naive nAMD eyes (1330 patients) undergoing anti-VEGF therapy for 12 months nationwide.

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Supervised deep learning (DL) algorithms are highly dependent on training data for which human graders are assigned, for example, for optical coherence tomography (OCT) image annotation. Despite the tremendous success of DL, due to human judgment, these ground truth labels can be inaccurate and/or ambiguous and cause a human selection bias. We therefore investigated the impact of the size of the ground truth and variable numbers of graders on the predictive performance of the same DL architecture and repeated each experiment three times.

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Aim: To compare the effectiveness and costs of the implementation of the Intravitreal Therapy Unit Model, endorsed by the SERV, SECA, SEO and SEDISA, compared to the usual procedure.

Method: Analytical decision model that compares an UTI-type healthcare organization with 4 usual practice scenarios in Spain, in terms of quality-of-life results due to loss of visual acuity and the use of resources. The probability, cost, and quality-adjusted life years (QALYs) were estimated for each scenario proposed.

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Introduction: Timely anti-vascular endothelial growth factor (VEGF) treatment is crucial for visual function in neovascular age-related macular degeneration (nAMD). The aim of this study was to assess the reasons for anti-VEGF treatment delay during the COVID-19 lockdown and its clinical impact in patients with nAMD.

Methods: A retrospective, observational, multicentre study in patients with nAMD treated with anti-VEGF therapy was performed in 16 centres nationwide.

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Currently, most medical image data, such as optical coherence tomography (OCT) images, are displayed in two dimensions on a computer screen. Advances in computer information technology have contributed to the growing storage of these data in electronic form. However, the data are usually processed only locally on site.

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Article Synopsis
  • The article discusses how artificial intelligence (AI) is being used to screen and diagnose retinal diseases, highlighting its potential impact on telemedicine and healthcare systems, particularly in ophthalmology.
  • It reviews recent studies on AI algorithms for retinal disease and outlines four essential factors for their effective use: managing large data sets, ensuring practical application in eye care, adhering to regulations, and balancing costs and profitability.
  • The Vision Academy acknowledges the pros and cons of AI technologies and provides recommendations for future advancements in this area.
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Article Synopsis
  • - The review aims to outline the latest advancements in AI devices for managing retinal conditions and offers recommendations from the Vision Academy.
  • - Despite the promising benefits of AI models for personalized treatments and risk scoring, most have not yet received regulatory approval, raising concerns about their application and safety in diverse patient populations.
  • - As AI medical devices continue to develop, current clinical practices may need to adapt, emphasizing the importance of reaching a consensus on their safety and effectiveness for widespread use.
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Article Synopsis
  • The aging population is leading to an increase in age-related eye diseases, making it essential for health systems to adapt and manage the anticipated higher demand for eye care, particularly for conditions like neovascular age-related macular degeneration (nAMD) and diabetic eye disease.
  • Recent advancements in eye care provide an opportunity to improve patient experiences and outcomes, but there are existing capacity limitations that need to be addressed through sustainable strategies.
  • A collaborative effort involving clinical experts and patient advocates from multiple countries has identified these capacity challenges and calls for action to implement effective solutions for managing retinal diseases in the future.
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Purpose: To study the treatment patterns, visual outcomes and safety profile of intravitreal dexamethasone implant (IDI) used for the treatment of macular edema secondary to retinal vein occlusion.

Methods: Up to 2 years of routinely collected anonymized data within electronic medical record systems were remotely extracted from 16 centers. The outcome measures include visual outcome, number of injections, and safety measures, including the rate of intraocular pressure (IOP) rise, frequency of IOP-lowering medication usage, and cataract surgery rates.

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Diabetic retinopathy (DR) is a sight threatening complication of diabetes mellitus (DM). The incidence of DR in the pediatric population has increased in the last two decades and it is expected to further rise in the future, following the increase in DM prevalence and obesity in youth. As early stages of the retinal disease are asymptomatic, screening programs are of extreme importance to guarantee a prompt diagnosis and avoid progression to more advanced, sight threatening stages.

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The aim of this multicenter, national clinical audit is to evaluate the predictive factors and management of postoperative macular edema (ME) after retropupillary iris-claw intraocular lens (RICI) implantation and pars plana vitrectomy (PPV). Preoperative, surgical and postoperative data were collected. Number and type of intravitreal injections (IT) administered (anti-VEGF or dexamethasone implant), visual acuity (VA), intraocular pressure (IOP) and central retinal thickness (CRT) assessed by OCT were collected at 1, 3, 6 and 12 months.

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Aim: To explore associations between artificial intelligence (AI)-based fluid compartment quantifications and 12 months visual outcomes in OCT images from a real-world, multicentre, national cohort of naïve neovascular age-related macular degeneration (nAMD) treated eyes.

Methods: Demographics, visual acuity (VA), drug and number of injections data were collected using a validated web-based tool. Fluid compartment quantifications including intraretinal fluid (IRF), subretinal fluid (SRF) and pigment epithelial detachment (PED) in the fovea (1 mm), parafovea (3 mm) and perifovea (6 mm) were measured in nanoliters (nL) using a validated AI-tool.

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Purpose: To evaluate the diagnostic accuracy of machine learning (ML) techniques applied to radiomic features extracted from OCT and OCT angiography (OCTA) images for diabetes mellitus (DM), diabetic retinopathy (DR), and referable DR (R-DR) diagnosis.

Design: Cross-sectional analysis of a retinal image dataset from a previous prospective OCTA study (ClinicalTrials.govNCT03422965).

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