Evidence map›Paper›PMID 41552661›Full record

ArticleOphthalmology science2026

Impact of Vision Impairment and Microperimetry Parameters on Quality of Life in Patients with Center-Involving Diabetic Macular Edema.

Gabriele Piccoli, Eva K Fenwick, Vanda Bucceri, Ecosse L Lamoureux, Elena Tagliabue, Paolo Nucci, Stela Vujosevic

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Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Gabriele PiccoliEye Clinic, IRCCS MultiMedica, Milan, Italy.
Eva K FenwickSingapore Eye Research Institute, Singapore National Eye Centre, Singapore.
Vanda BucceriEye Clinic, IRCCS MultiMedica, Milan, Italy.
Ecosse L LamoureuxSingapore Eye Research Institute, Singapore National Eye Centre, Singapore.
Elena TagliabueIRCCS MultiMedica, Milan, Italy.
Paolo NucciDepartment of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy.
Stela VujosevicEye Clinic, IRCCS MultiMedica, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To determine the association between retinal sensitivity (RS), fixation stability (FS) and best-corrected visual acuity (BCVA), and vision-related quality of life (VRQoL) in patients with center-involving diabetic macular edema (CI-DME) using a novel computerized adaptive diabetic macular edema (DME)-specific patient-reported outcome measure (PROM) (RetCAT) and to corroborate the findings using the National Eye Institute Visual Function Questionnaire-25 (NEIVFQ-25). Design: Cross-sectional, prospective, clinical study. Participants: One hundred patients (mean age 67.55 ± 11.65 years; 58% males) with treatment-naïve CI-DME in one or both eyes. Methods: All patients underwent a comprehensive ophthalmic evaluation, including BCVA measurement, and microperimetry for RS (measured using threshold values) and FS assessment (measured using bivariate contour ellipse area parameters). Vision-related quality of life was measured using 10 domains of the RetCAT, namely Activity limitation, Mobility, Emotional well-being, Concerns, Symptoms, Social, Convenience, Lighting, Driving, and Economic, and the NEIVFQ-25 questionnaire. Associations between visual parameters and VRQoL outcomes were explored using multiple linear regression models. Dominance analysis estimated the relative contribution for each of the single visual parameters on VRQoL. Main Outcome Measures: The associations between functional parameters and VRQoL in patients with CI-DME using a RetCAT and NEIVFQ-25 PROMs. Results: Patients with worse vision and RS had lower scores on all RetCAT domains compared with those with better visual parameters, and those with worse FS had lower scores on 5 of the 10 RetCAT domains. Retinal sensitivity had the strongest dominance in explaining variance in half of the RetCAT domains (Activity limitation, Concerns, Emotional, Mobility, and Social). Best-corrected visual acuity was the dominant predictor only in Conclusions: Retinal sensitivity has a stronger association with VRQoL than BCVA in patients with CI-DME. These findings support the importance of microperimetry in demonstrating the role of RS in the functional abilities of patients with DME and modern adaptive PROM measures like RetCAT which directly capture the impact of DME on patients' daily lives in both clinical practice and research. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Diabetic macular edemaDiabetic retinopathyMicroperimetryQuality of life

Identifiers

PMID41552661
PMCPMC12805012

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.