Early prediction of severe retinopathy of prematurity requiring laser treatment using physiological data

Jarinda A. Poppe*, Sean P. Fitzgibbon, H. Rob Taal, Sjoukje E. Loudon, Angela M. Tjiam, Charles C. Roehr, Irwin K.M. Reiss, Sinno H.P. Simons, Caroline Hartley

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
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Abstract

Background: Early risk stratification for developing retinopathy of prematurity (ROP) is essential for tailoring screening strategies and preventing abnormal retinal development. This study aims to examine the ability of physiological data during the first postnatal month to distinguish preterm infants with and without ROP requiring laser treatment. Methods: In this cohort study, preterm infants with a gestational age <32 weeks and/or birth weight <1500 g, who were screened for ROP were included. Differences in the physiological data between the laser and non-laser group were identified, and tree-based classification models were trained and independently tested to predict ROP requiring laser treatment. Results: In total, 208 preterm infants were included in the analysis of whom 30 infants (14%) required laser treatment. Significant differences were identified in the level of hypoxia and hyperoxia, oxygen requirement, and skewness of heart rate. The best model had a balanced accuracy of 0.81 (0.72–0.87), a sensitivity of 0.73 (0.64–0.81), and a specificity of 0.88 (0.80–0.93) and included the SpO2/FiO2 ratio and baseline demographics (including gestational age and birth weight). Conclusions: Routinely monitored physiological data from preterm infants in the first postnatal month are already predictive of later development of ROP requiring laser treatment, although validation is required in larger cohorts. Impact: Routinely monitored physiological data from the first postnatal month are predictive of later development of ROP requiring laser treatment, although model performance was not significantly better than baseline characteristics (gestational age, birth weight, sex, multiple birth, prenatal glucocorticosteroids, route of delivery, and Apgar scores) alone.A balanced accuracy of 0.81 (0.72–0.87), a sensitivity of 0.73 (0.64–0.81), and a specificity of 0.88 (0.80–0.93) was achieved with a model including the SpO2/FiO2 ratio and baseline characteristics.Physiological data have potential to play a significant role for future ROP prediction and provide opportunities for early interventions to protect infants from abnormal retinal development.

Original languageEnglish
Pages (from-to)699-706
Number of pages8
JournalPediatric Research
Volume94
Issue number2
DOIs
Publication statusPublished - Aug 2023

Bibliographical note

Funding Information:
This work was supported by the Wellcome Trust and Royal Society (213486/Z/18/Z [to C.H.]) and the European Society for Paediatric Research (Young Investigator START-UP Grant 2020 [to J.A.P.]). Study funders had no role in study design, data collection, data analysis, interpretation of study results, or writing of the manuscript.

Publisher Copyright:
© 2023, The Author(s).

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