June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Inconsistencies in the diagnosis of aggressive posterior retinopathy of prematurity
Author Affiliations & Notes
  • Mrinali Patel Gupta
    Ophthalmology, Weill Cornell Medical College, New York, New York, United States
  • Samir Patel
    Ophthalmology, Weill Cornell Medical College, New York, New York, United States
  • Ranjodh Singh
    Ophthalmology, Weill Cornell Medical College, New York, New York, United States
  • Karyn Elizabeth Jonas
    Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois, United States
  • Susan Ostmo
    Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon, United States
  • Paul Petrakos
    Ophthalmology, Weill Cornell Medical College, New York, New York, United States
  • J. Peter Campbell
    Ophthalmology, Casey Eye Institute at Oregon Health and Science University, Portland, Oregon, United States
  • Michael F Chiang
    Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon, United States
    Ophthalmology, Casey Eye Institute at Oregon Health and Science University, Portland, Oregon, United States
  • Robison Vernon Paul Chan
    Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago, Chicago, Illinois, United States
    Center for Global Health, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States
  • Footnotes
    Commercial Relationships   Mrinali Patel Gupta, None; Samir Patel, None; Ranjodh Singh, None; Karyn Jonas, None; Susan Ostmo, None; Paul Petrakos, None; J. Peter Campbell, None; Michael Chiang, Clarity Medical Systems (S), Novartis (C); Robison Chan, Visunex Medical Systems (C)
  • Footnotes
    Support  Funding/Support: supported by grants P30EY10572, R01EY19474, and R21EY22387 from the National Institutes of Health (Bethesda, MD), grant 1622679 from the National Science Foundation (Arlington, VA), and by unrestricted departmental funding from Research to Prevent Blindness (New York, NY)
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 5531. doi:
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      Mrinali Patel Gupta, Samir Patel, Ranjodh Singh, Karyn Elizabeth Jonas, Susan Ostmo, Paul Petrakos, J. Peter Campbell, Michael F Chiang, Robison Vernon Paul Chan; Inconsistencies in the diagnosis of aggressive posterior retinopathy of prematurity. Invest. Ophthalmol. Vis. Sci. 2017;58(8):5531.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To determine the accuracy and reliability of diagnosing aggressive posterior retinopathy of prematurity (APROP).

Methods : 1220 eye examinations from 230 infants undergoing retinopathy of prematurity (ROP) screening examinations were prospectively obtained at 8 major ROP centers. An ophthalmologist at each center provided a clinical diagnosis using indirect ophthalmoscopy. Wide-angle retinal images were then obtained, which were independently read by two ROP experts using a web-based system for an image-based diagnosis. Sensitivity and specificity of image-based APROP diagnosis by the ROP experts were calculated using the clinical diagnosis as the reference standard. Image-based and clinical diagnosis agreement for APROP was calculated using absolute agreement and the unweighted κ statistic.

Results : 104/1220 (9%) examinations had a clinical diagnosis of APROP. Sensitivity and specificity for the presence of APROP were 35% and 96% for expert 1, and 17% and 99% for expert 2. There were 79 of 1220 (6%) examinations in which the image-based responses of both experts disagreed with the clinical diagnosis of APROP. In 11 of 1220 (1%) examinations, both experts provided an image-based diagnosis of APROP, but the clinical diagnosis was no APROP. In 68 of 1220 (6%) examinations, both experts provided an image-based diagnosis of no APROP, but the clinical diagnosis was APROP. Using the kappa statistic, expert image-based versus clinical diagnostic agreement for the diagnosis of APROP was 0.34 (fair) for expert 1, and 0.24 (fair) for expert 2. Agreement for the diagnosis of APROP between the image-based diagnoses of expert 1 and expert 2 was 0.49 (moderate).

Conclusions : There are inconsistencies between the clinical diagnosis of APROP (as determined by indirect ophthalmoscopy) and the image-based diagnosis of APROP. This may have important implications for ROP management and the current international ROP classification system.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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