Investigative Ophthalmology & Visual Science Cover Image for Volume 57, Issue 12
September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Risk calculator to predict severe retinopathy of prematurity
Author Affiliations & Notes
  • Madeline Yung
    Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
  • Emily Tam
    Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
  • Sasha Hubschman
    Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
  • Irena Tsui
    Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, United States
  • Footnotes
    Commercial Relationships   Madeline Yung, None; Emily Tam, None; Sasha Hubschman, None; Irena Tsui, None
  • Footnotes
    Support  none
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 6262. doi:
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      Madeline Yung, Emily Tam, Sasha Hubschman, Irena Tsui; Risk calculator to predict severe retinopathy of prematurity. Invest. Ophthalmol. Vis. Sci. 2016;57(12):6262.

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

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Abstract

Purpose : Although retinopathy of prematurity (ROP) is an important cause of vision loss, there are currently no data-derived risk prediction systems that are widely used in clinical practice. We conducted a prospective cohort study to examine the relationship of established ROP risk factors with the severity of ROP, with the goal of synthesizing a risk calculator to predict the risk for severe ROP.

Methods : This study included 282 infants (124 males and 158 females) who were hospitalized within the UCLA healthcare system between January 1, 2008 and December 31, 2014, screened for ROP based on published guidelines, and received care through at least 1 month of age. Patient charts were analyzed for established ROP risk factors and progression to severe ROP, defined as ROP requiring treatment with laser photocoagulation or anti-VEGF therapy. In addition to bivariate and multivariate analysis, least absolute shrinkage and selection operator (LASSO) method was used to identify major risk factors, and restricted cubic splines (RCS) were used to formulate a risk calculator.

Results : Of the 20 variables examined, 13 conferred significant risk for severe ROP on bivariate analysis. The most influential risk factors on multivariate analysis included gestational age (OR=0.61 per week, 95% CI 0.47-0.81, p= < 0.001), birthweight (OR=1.00 per gram, 95% CI 1.00-1.00, p=0.08), average blood oxygen saturation at one month (OR=0.93 per percentage point, 95% CI 0.87-0.98, p=0.01), and transfer in to the UCLA healthcare system (OR= 0.23, 95% CI 0.08-0.69, p=0.009) (table 1). A risk calculator based on these four major factors yielded an accuracy of 81.3%, sensitivity of 84.6%, and specificity of 77.9%.

Conclusions : Using the major risk factors of gestational age, birthweight, transfer status, and average oxygen saturation at one month of age, we formulated an easy-to-use risk calculator that predicts risk of severe ROP at tertiary care centers. This tool is useful for counseling families and informing a multi-disciplinary healthcare team of an infant’s vision care prognosis. Further refinement of the calculator may extend its applications to community settings or even guiding ROP management.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

Table 1: Risk factors for retinopathy of prematurity on bivariate and multivariate analysis. OR - odds ratio. CI - confidence interval. ¥ Variables with multiple clinical outcomes were treated as separate variables their own p-value.

Table 1: Risk factors for retinopathy of prematurity on bivariate and multivariate analysis. OR - odds ratio. CI - confidence interval. ¥ Variables with multiple clinical outcomes were treated as separate variables their own p-value.

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