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.


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 318719




Reproduktionsmedicin och gynekologi





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