September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Risk Score for Predicting Development of Treatment-Requiring Retinopathy of Prematurity in the Telemedicine Approaches to Evaluating of Acute-Phase ROP (e-ROP) Study
Author Affiliations & Notes
  • Gui-Shuang Ying
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
  • Deborah VanderVeen
    Boston Children's Hospital, Boston, Massachusetts, United States
  • Graham E Quinn
    Division of Ophthalmology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Ebenezer Daniel
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
  • Agnieshka Baumritter
    Division of Ophthalmology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Gui-Shuang Ying, None; Deborah VanderVeen, None; Graham Quinn, None; Ebenezer Daniel, None; Agnieshka Baumritter, None
  • Footnotes
    Support  U10EY017014, R21EY025686
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 6261. doi:
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      Gui-Shuang Ying, Deborah VanderVeen, Graham E Quinn, Ebenezer Daniel, Agnieshka Baumritter; Risk Score for Predicting Development of Treatment-Requiring Retinopathy of Prematurity in the Telemedicine Approaches to Evaluating of Acute-Phase ROP (e-ROP) Study. Invest. Ophthalmol. Vis. Sci. 2016;57(12):6261.

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

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Abstract

Purpose : To develop a risk score for predicting treatment-requiring ROP (TR-ROP).

Methods : Secondary analyses of data among infants with birth weight of <1251g who had an imaging session ≦34 PMA weeks and at least one subsequent ROP examination for determining TR-ROP by study-certified ophthalmologists. Non-physician trained readers evaluated characteristics of ROP, posterior pole abnormality, and hemorrhage in wide-field retinal images. Multivariate logistic regression modeling was performed to determine independent predictors of TR-ROP, and calculate the risk score points based on regression coefficients of statistically significant predictors

Results : Among 771 infants, 85 (11.0%) developed TR-ROP. In a multivariate model, significant predictors [odds ratio (95% confidence interval)] for TR-ROP were: gestational age [5.7 (1.7 – 18.9) for ≤25 vs. ≥28 weeks], number of quadrants with preplus or plus [4.0 (1.4 – 11.4) for 3 preplus quadrants, and 3.8 (1.5 – 9.7) for 4 preplus quadrants or plus in any quadrant vs. no preplus or plus], zone and stage of ROP [4.7 (2.1 – 11.8) for stage 1-2 zone I, 5.9 (2.1 – 16.6) for stage 3 zone I vs. no ROP], blot hemorrhage [3.1 (1.4 – 6.7) for presence vs. absence], respiratory support [7.0 (1.3 – 37.1) for need of high frequency oscillatory ventilation vs. no respiratory support], and slow weight gain [2.4 (1.2 – 4.6) for weight gain ≤12 vs. >15g/day]. Image findings at the first image session better predicted TR-ROP than gestational age (area under ROC curve [AUC] =0.82 vs. 0.75, p<0.0001). The 22-point risk score from these 6 significant predictors had a median of 4 points (range: 0 to 18). The risk of TR-ROP steadily increased with higher risk score (0% for risk score 0 point, to 94% for 13 points or above, Figure). The risk score well predicted TR-ROP with AUC of 0.88 (95% CI: 0.85-0.92) and had a sensitivity of 98.8% and specificity of 40.1% using risk score ≥3 points as high risk.

Conclusions : Zone and stage of ROP, posterior pole abormalities, blot hemorrhage in retinal images by 34 PMA independently predicted TR-ROP. Image findings along with gestational age, respiratory support and postnatal weight gain at the time of first image session may help identify infants in need of increased surveillance to detect TR-ROP.

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

 

Figure: The rate if treatment-requiring ROP by the risk score points

Figure: The rate if treatment-requiring ROP by the risk score points

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