Literature DB >> 31940501

Positive predictive value and screening performance of GoCheck Kids in a primary care university clinic.

Megan X Law1, Mariana Flores Pimentel1, Catherine E Oldenburg1, Alejandra G de Alba Campomanes2.   

Abstract

PURPOSE: To determine the positive predictive value (PPV) of GoCheck Kids, a smartphone-based photoscreener, to detect refractive amblyopia risk factors (ARFs) in children 3-48 months of age.
METHODS: The medical records of all children ≤48 months of age who failed GoCheck Kids photoscreening at a University of California, San Francisco, pediatric clinic between February 2017 and August 2018 and subsequently examined at the pediatric ophthalmology clinic were reviewed retrospectively. The PPV of GoCheck Kids was determined, where a true positive represents an abnormal cycloplegic refractive error according to the 2013 American Association of Pediatric Ophthalmology and Strabismus Vision Screening Committee criteria. For patients ≤12 months of age, refractive error thresholds were based on the 2017 American Academy of Ophthalmology Preferred Practice Patterns Pediatric Eye Evaluation guidelines.
RESULTS: A total of 2,963 children were screened with GoCheck Kids. Of these, 172 (5.8%) failed the screening, of whom 115 (67%) were evaluated in the pediatric ophthalmology clinic. The mean age was 24.9 ± 11.1months (range, 3-48). Fifty-seven patients met ARF criteria yielding a PPV of 50% (95% CI, 41%-60%). The PPV was higher in patients of Latino/hispanic ethnicity (75%; 95% CI, 57%-100%; P < 0.01) and changed significantly with increasing age (P = 0.03). Patients who were screened between age 3-12 months had the lowest PPV at 26% (95% CI, 14%-47%).
CONCLUSIONS: Modifying refractive error thresholds based on patient age and prevalence of ARFs in a population may improve the PPV of GoCheck Kids in a community-based screening program.
Copyright © 2020 American Association for Pediatric Ophthalmology and Strabismus. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 31940501     DOI: 10.1016/j.jaapos.2019.11.006

Source DB:  PubMed          Journal:  J AAPOS        ISSN: 1091-8531            Impact factor:   1.220


  2 in total

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Authors:  Iara Debert; Douglas Rodrigues da Costa; Mariza Polati; Janaina Guerra Falabretti; Remo Susanna Junior
Journal:  Rev Paul Pediatr       Date:  2022-05-06

2.  Artificial Intelligence to Reduce Ocular Health Disparities: Moving From Concept to Implementation.

Authors:  John P Campbell; Ciku Mathenge; Hunter Cherwek; Konstantinos Balaskas; Louis R Pasquale; Pearse A Keane; Michael F Chiang
Journal:  Transl Vis Sci Technol       Date:  2021-03-01       Impact factor: 3.283

  2 in total

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