Early prediction of severe retinopathy of prematurity requiring laser treatment using physiological data.
| Autor: | Poppe JA; Department of Neonatal and Pediatric Intensive Care, Division of Neonatology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam, the Netherlands. j.poppe@erasmusmc.nl., Fitzgibbon SP; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK., Taal HR; Department of Neonatal and Pediatric Intensive Care, Division of Neonatology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam, the Netherlands., Loudon SE; Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands., Tjiam AM; Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands., Roehr CC; National Perinatal Epidemiology Unit, Nuffield Department of Population Health, Medical Sciences, Division, University of Oxford, Oxford, UK.; Newborn Services, Southmead Hospital, North Bristol Trust, Bristol, UK.; Faculty of Health Sciences, University of Bristol, Bristol, UK., Reiss IKM; Department of Neonatal and Pediatric Intensive Care, Division of Neonatology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam, the Netherlands., Simons SHP; Department of Neonatal and Pediatric Intensive Care, Division of Neonatology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam, the Netherlands., Hartley C; Department of Paediatrics, University of Oxford, Oxford, UK. |
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| Jazyk: | angličtina |
| Zdroj: | Pediatric research [Pediatr Res] 2023 Aug; Vol. 94 (2), pp. 699-706. Date of Electronic Publication: 2023 Feb 14. |
| DOI: | 10.1038/s41390-023-02504-6 |
| Abstrakt: | 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 SpO 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 SpO (© 2023. The Author(s).) |
| Databáze: | MEDLINE |
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