Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity
Artikel i vetenskaplig tidskrift, 2022
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.
Författare
A. Pivodic
Göteborgs universitet
H. Johansson
Göteborgs universitet
Australian Catholic University
Lois E.H. Smith
Harvard Medical School
Anna Lena Hård
Göteborgs universitet
Chatarina Löfqvist
Göteborgs universitet
Bradley A. Yoder
University of Utah
M. Elizabeth Hartnett
University of Utah
Carolyn Wu
Harvard Medical School
Marie Christine Bründer
Universitätsmedizin Greifswald
Wolf A. Lagrèze
Albert-Ludwigs-Universität Freiburg
Andreas Stahl
Universitätsmedizin Greifswald
Abbas Al-Hawasi
Linköpings universitet
Eva Larsson
Uppsala universitet
Pia Lundgren
Göteborgs universitet
Örebro universitet
Lotta Gränse
Skånes universitetssjukhus (SUS)
Birgitta Sunnqvist
Länssjukhuset Ryhov
Kristina Tornqvist
Skånes universitetssjukhus (SUS)
Agneta Wallin
S:t Eriks Ögonsjukhus
Gerd Holmström
Uppsala universitet
Kerstin Albertsson-Wikland
Göteborgs universitet
Staffan Nilsson
Göteborgs universitet
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Ann Hellström
Göteborgs universitet
British Journal of Ophthalmology
0007-1161 (ISSN) 14682079 (eISSN)
Vol. 106 1573-1580 318719Ämneskategorier
Pediatrik
Oftalmologi
Reproduktionsmedicin och gynekologi
DOI
10.1136/bjophthalmol-2020-318719
PubMed
33980506