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

Autor:	Pivodic A; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden aldina.pivodic@gu.se., Johansson H; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia.; Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden., Smith LEH; Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA., Hård AL; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden., Löfqvist C; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.; Learning and Leadership for Health Care Professionals, Institute of Health Care Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden., Yoder BA; Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, USA., Hartnett ME; Department of Ophthalmology, John A Moran Eye Center, University of Utah, Salt Lake City, Utah, USA., Wu C; Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA., Bründer MC; Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany., Lagrèze WA; Department of Ophthalmology, Eye Center, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany., Stahl A; Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany., Al-Hawasi A; Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden., Larsson E; Department of Neuroscience/Ophthalmology, Uppsala University, Uppsala, Sweden., Lundgren P; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.; Department of Ophthalmology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden., Gränse L; Department of Clinical Sciences, Ophthalmology, Skåne University Hospital, Lund University, Lund, Sweden., Sunnqvist B; Länssjukhuset Ryhov, Jönköping, Sweden., Tornqvist K; Department of Clinical Sciences, Ophthalmology, Skåne University Hospital, Lund University, Lund, Sweden., Wallin A; St. Erik Eye Hospital, Stockholm, Sweden., Holmström G; Department of Neuroscience/Ophthalmology, Uppsala University, Uppsala, Sweden., Albertsson-Wikland K; Department of Physiology/Endocrinology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden., Nilsson S; Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.; Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden., Hellström A; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Jazyk:	angličtina
Zdroj:	The British journal of ophthalmology [Br J Ophthalmol] 2022 Nov; Vol. 106 (11), pp. 1573-1580. Date of Electronic Publication: 2021 May 12.
DOI:	10.1136/bjophthalmol-2020-318719
Abstrakt:	Background/aims: Prematurely 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. Methods: Data, 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. Results: ROP 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%. Conclusions: DIGIROP-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. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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