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Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity

  • Background/AimsPrematurely born infants undergo costly, stressful eye examinations to uncover the small fraction with retinopathy of prematurity (ROP) that needs treatment to prevent blindness. The aim was to develop a prediction tool (DIGIROP-Screen) with 100% sensitivity and high specificity to safely reduce screening of those infants not needing treatment. DIGIROP-Screen was compared with four other ROP models based on longitudinal weights.MethodsData, including infants born at 24–30 weeks of gestational age (GA), for DIGIROP-Screen development (DevGroup, N=6991) originate from the Swedish National Registry for ROP. Three international cohorts comprised the external validation groups (ValGroups, N=1241). Multivariable logistic regressions, over postnatal ages (PNAs) 6–14 weeks, were validated. Predictors were birth characteristics, status and age at first diagnosed ROP and essential interactions.ResultsROP treatment was required in 287 (4.1%)/6991 infants in DevGroup and 49 (3.9%)/1241 in ValGroups. To allow 100% sensitivity in DevGroup, specificity at birth was 53.1% and cumulatively 60.5% at PNA 8 weeks. Applying the same cut-offs in ValGroups, specificities were similar (46.3% and 53.5%). One infant with severe malformations in ValGroups was incorrectly classified as not needing screening. For all other infants, at PNA 6–14 weeks, sensitivity was 100%. In other published models, sensitivity ranged from 88.5% to 100% and specificity ranged from 9.6% to 45.2%.ConclusionsDIGIROP-Screen, a clinical decision support tool using readily available birth and ROP screening data for infants born GA 24–30 weeks, in the European and North American populations tested can safely identify infants not needing ROP screening. DIGIROP-Screen had equal or higher sensitivity and specificity compared with other models. DIGIROP-Screen should be tested in any new cohort for validation and if not validated it can be modified using the same statistical approaches applied to a specific clinical setting.

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Author: Aldina Pivodic, Helena Johansson, Lois E H Smith, Anna-Lena Hård, Chatarina Löfqvist, Bradley A Yoder, M Elizabeth Hartnett, Carolyn Wu, Marie-Christine Bründer, Wolf A Lagrèze, Andreas Stahl, Abbas Al-Hawasi, Eva Larsson, Pia Lundgren, Lotta Gränse, Birgitta Sunnqvist, Kristina Tornqvist, Agneta Wallin, Gerd Holmström, Kerstin Albertsson-Wikland, Staffan Nilsson, Ann Hellström
URN:urn:nbn:de:gbv:9-opus-75774
DOI:https://doi.org/doi:10.1136/bjophthalmol-2020-318719
ISSN:0007-1161
ISSN:1468-2079
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/33980506
Parent Title (English):British Journal of Ophthalmology
Publisher:BMJ Publishing Group Ltd.
Place of publication:London
Document Type:Article
Language:English
Date of first Publication:2021/05/12
Release Date:2022/11/14
Tag:ROP screening; clinical decision support tool; diagnostic tests/Investigation; neovascularisation; optimized screening; prediction model; preterm; retinopathy of prematurity
GND Keyword:-
Volume:106
Issue:11
First Page:1573
Last Page:1580
Faculties:Universitätsmedizin / Klinik und Poliklinik für Augenheilkunde
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell