Literature DB >> 30690127

Plus Disease in Telemedicine Approaches to Evaluating Acute-Phase ROP (e-ROP) Study: Characteristics, Predictors, and Accuracy of Image Grading.

Qianqian Ellie Cheng1, Ebenezer Daniel2, Wei Pan2, Agnieshka Baumritter3, Graham E Quinn4, Gui-Shuang Ying5.   

Abstract

PURPOSE: To describe characteristics and predictors of plus disease, and the accuracy of image grading for plus disease in the e-ROP Study.
DESIGN: Secondary analyses of data from 13 North American centers. PARTICIPANTS: Premature infants with birth weight (BW) <1251 g.
METHODS: Infants underwent regularly scheduled diagnostic examinations by ophthalmologists and digital imaging by trained imagers using a wide-field digital camera. Two masked nonphysician trained readers independently evaluated images for posterior pole abnormality (normal, preplus, plus), with discrepancies adjudicated by a reading supervisor. Logistic regression models were used to determine predictors for plus disease. The sensitivity and specificity of image grading for plus disease were calculated using the clinical examination finding as reference standard. MAIN OUTCOME MEASURES: Odds ratios (OR), sensitivity, and specificity.
RESULTS: Among 1239 infants (mean BW 864 g, mean gestational age [GA] 27 weeks), 129 infants (10%) (226 eyes, 75% bilateral) had plus disease from clinical examination. When plus disease was first diagnosed in clinical examination at median postmenstrual age (PMA) of 36 weeks (range: 32-43 weeks), 94% to 96% of plus occurred in the superior or inferior temporal quadrant. Significant predictors for plus disease from multivariate analysis were as follows: GA (OR = 3.2 for ≤24 vs. ≥28 weeks, P = 0.004), race (OR = 2.4 for white vs. black, P = 0.01), respiratory support (OR = 7.1, P = 0.006), weight gain (OR = 1.5 for weight gain ≤12 vs. >18 g/day, P = 0.03), and image findings at the first image session, including presence of preplus/plus disease (OR = 2.7, P = 0.003), ROP stage (OR = 4.2 for stage 3 ROP vs. no ROP, P = 0.006), and blot hemorrhage (OR = 3.1, P = 0.003). These features predicted plus disease with an area under the receiver operating characteristic curve of 0.89 (95% confidence interval [CI]: 0.85-0.92). The image grading using preplus as the cut point had sensitivity of 94% (95% CI: 90%-97%) and specificity of 81% (95% CI: 79%-82%) for detecting plus disease in an eye.
CONCLUSIONS: Among e-ROP infants, plus disease developed in 10% of infants at a median PMA of 37 weeks, with the majority being bilateral and mostly in the superior or inferior temporal quadrant. GA, race, respiratory support, postnatal weight gain, image findings of the posterior pole, and ROP predict development of plus disease. Nonphysician image grading can detect almost all plus disease with good specificity.
Copyright © 2019 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2019        PMID: 30690127     DOI: 10.1016/j.ophtha.2019.01.021

Source DB:  PubMed          Journal:  Ophthalmology        ISSN: 0161-6420            Impact factor:   12.079


  6 in total

1.  Cost-effectiveness of Artificial Intelligence-Based Retinopathy of Prematurity Screening.

Authors:  Steven L Morrison; Dmitry Dukhovny; R V Paul Chan; Michael F Chiang; J Peter Campbell
Journal:  JAMA Ophthalmol       Date:  2022-04-01       Impact factor: 8.253

2.  Comparison of RetCam and Smartphone-Based Photography for Retinopathy of Prematurity Screening.

Authors:  Jui-Yen Lin; Eugene Yu-Chuan Kang; Alay S Banker; Kuan-Jen Chen; Yih-Shiou Hwang; Chi-Chun Lai; Jhen-Ling Huang; Wei-Chi Wu
Journal:  Diagnostics (Basel)       Date:  2022-04-10

3.  Progression from preplus to plus disease in the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity (e-ROP) Study: incidence, timing, and predictors.

Authors:  Qianqian Ellie Cheng; Graham E Quinn; Ebenezer Daniel; Agnieshka Baumritter; Eli Smith; Gui-Shuang Ying
Journal:  J AAPOS       Date:  2020-11-16       Impact factor: 1.220

Review 4.  Artificial intelligence for retinopathy of prematurity.

Authors:  Rebekah H Gensure; Michael F Chiang; John P Campbell
Journal:  Curr Opin Ophthalmol       Date:  2020-09       Impact factor: 3.761

5.  Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy, Third Edition.

Authors:  Mark B Horton; Christopher J Brady; Jerry Cavallerano; Michael Abramoff; Gail Barker; Michael F Chiang; Charlene H Crockett; Seema Garg; Peter Karth; Yao Liu; Clark D Newman; Siddarth Rathi; Veeral Sheth; Paolo Silva; Kristen Stebbins; Ingrid Zimmer-Galler
Journal:  Telemed J E Health       Date:  2020-03-25       Impact factor: 3.536

Review 6.  Telemedicine for Retinopathy of Prematurity.

Authors:  Christopher J Brady; Samantha D'Amico; J Peter Campbell
Journal:  Telemed J E Health       Date:  2020-03-25       Impact factor: 3.536

  6 in total

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