Evidence map›Paper›PMID 41555069›Full record

ArticleEye (London, England)2026

Optimised multivariable prediction model to predict treatment requirement in preterm infants with retinopathy of prematurity.

Taku Toyama, Han Peng Zhou, Sao Sugimoto, Kentaro Hayashi, Masako Nagahara, Takuya Kuriyama, Gen Mihara, Kosuke Nakajima, Takashi Ueta

Abstract read
In one paragraph

Article in Eye (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Taku ToyamaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan. toyama.ophthalmol@gmail.com.ORCID 0009-0001-0388-0635
Han Peng ZhouDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Sao SugimotoDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Kentaro HayashiDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Masako NagaharaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.ORCID 0009-0006-4613-0056
Takuya KuriyamaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Gen MiharaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Kosuke NakajimaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
Takashi UetaDepartment of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, Japan.

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) 22K16963
6 · The paper itself

Abstract

backgroundRetinopathy of prematurity (ROP) is a leading cause of blindness in preterm infants. However, frequent fundus examinations place burdens on neonates, families, and healthcare staff. We aimed to develop a model to identify low-risk infants and reduce the number of patients requiring screening.

methodsWe conducted a single-centre retrospective cohort study at the University of Tokyo Hospital (October 2019-December 2024), including infants with birth weight ≤1800 g or gestational age <34 weeks (n = 298). Fourteen variables-birth weight, gestational age (GD), sex, growth velocity (GV), SpO₂/FiO₂ ratio, CRP, platelet count (Plt), PLR, NLR, LMR, SII, haemoglobin, albumin, and infection status-were evaluated at 28, 30, 32, and 34 postmenstrual weeks. We performed logistic regression on all variable combinations and selected the optimal model using the Akaike Information Criterion. ROC analysis was conducted by fixing sensitivity at 1.0 and selecting the threshold that maximised specificity. This threshold was then simulated in a hypothetical cohort of 100 infants to estimate the reduction in exam need.

resultsThe optimal model included GD, sex, GV, NLR_max, Plt_min, and PLR_max. Discriminative performance (AUC) improved with age: 0.70 (28 weeks), 0.78 (30), 0.82 (32), and 0.85 (34). Evaluations at 32 and 34 weeks maintained sensitivity while reducing the number of infants requiring examination by ~50%.

conclusionsThis model can identify low-risk infants from 32 weeks postmenstrual age, potentially halving the number of patients needing fundus exams. All predictors are routinely available in NICUs. External validation in independent multicenter, multi-ethnic, and international prospective cohorts is warranted before clinical implementation.

Indexed as

Retinopathy of PrematurityBirth WeightFemaleGestational AgeHumansInfant, NewbornInfant, PrematureLogistic ModelsMalePrediction AlgorithmsRetrospective StudiesRisk FactorsROC Curve

Identifiers

PMID41555069
PMCPMC13013675

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.