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Validation of Esaso Classification of Diabetic Maculopathy

  • Giacomo Panozzo
  • , Elia Franzolin
  • , Diana Giannarelli
  • , Giulia Dalla Mura
  • , Rosa Longo
  • , Anita Rosa Longo
  • , Maria Vittoria Cicinelli
  • , Edoardo Angelini
  • , Pietro Airaghi
  • , Teresio Avitabile
  • , Francesco Bandello
  • , Andrea Beccastrini
  • , Giorgia Benedetti
  • , Federico Bertuzzi
  • , Paolo Francesco Bertuzzi
  • , Vincenza Maria Elena Bonfiglio
  • , Francesco Boscia
  • , Adriano Carnevali
  • , Marianna Carosielli
  • , Matteo Giuseppe Cereda
  • Cecilia Contardi, Michele Coppola, Ciro Costagliola, Riccardo Cristofolini, Pasquale Cucciniello, Rossella D’Aloisio, Maddalena De Bernardo, Alessandro De Filippis, Roberto Dell’Omo, Roberto Dell'Omo, Ilenia Di Paola, Matteo Dell’Acqua, Massimiliano Dell'Acqua, Alessio Franco, Maria Oliva Grassi, Giulia Gregori, Elena Gusson, Rosangela Lattanzio, Paolo Lanzetta, Antonio Longo, Giorgio Marchini, Paola Marolo, Rodolfo Mastropasqua, Giuliana Mele Bertoldo, Giuseppina Monteleone, Giorgio Monteleone, Elina Ortisi, Guglielmo Parisi, Giuseppe Parisi, Salvatore Parrulli, Porzia Pucci, Marco Rocco Pastore, Michele Reibaldi, Stanislao Rizzo, Francesco Romano, Federica Romano, Nicola Rosa, Valentina Sarao, Giuseppe Scarpa, Vincenzo Scorcia, Andrea Scupola, Giovanni Staurenghi, Valentina Sunseri Trapani, Daniele Tognetto, Giuseppe Trabucchi, Sabrina Vaccaro, Maria Vadalà, Daniele Veritti, Alex Lucia Vinciguerra, Emma Clara Zanzottera

Research output: Contribution to journalArticle

Abstract

Purpose: To test reliability and reproducibility of ESASO morphologic OCT-based classification of diabetic maculopathy (DM). Methods: This is a multi-center cross-sectional study including a coordination center (CC) and 18 participating centers (PCs). After instruction on the correct use of ESASO Classification, the validation process was carried out in two consecutive stages. In the first retrospective phase, we evaluated the concordance between PCs and CC in the staging of OCT images collected during PCs’ daily activity (608 images). In a second prospective phase, we analyzed the inter-observer agreement of staging assigned by each PCs to OCT images selected by the CC (22 images). Results: The overall concordance achieved in the retrospective phase was 89.8% (Kappa = 0.83 (95% CI: 0.78–0.87); p<0.0001). In 99.5% of cases, concordance did not differ by more than one stage. In the prospective phase, PCs reached an inter-operator agreement of 93.0% (Krippendorff's Alpha = 0.953, 95% CI: 0.929–0.977, p<0.0001). Any discrepancy among the 22 images was within one stage. Conclusion: The results achieved in this study confirm that ESASO OCT-based Classification can be considered as an easy and reproducible method to stage DM during clinical practice. A diffused use of a common and validated method to describe the progression of retinal damage in DM may offer several clinical and scientific advantages.
Original languageEnglish
Pages (from-to)11206721231186649-11206721231186653
Number of pages5
JournalEuropean Journal of Ophthalmology
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • diabetic macular edema (DME)
  • optical coherence tomography
  • ESASO classification
  • diabetic maculopathy (DM)

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