Evidence map›Paper›PMID 40416432›Full record

ArticleFrontiers in pediatrics2025

Development and validation of a multivariate nomogram for predicting retinopathy of prematurity in infants with gestational age ≤34 weeks.

Leilei Shen, Ruixue Zheng, Xiaodong Sun, Sheng Chen

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In one paragraph

Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Leilei ShenDepartment of Pediatrics, Third Military Medical University Southwest Hospital, Chongqing, China.
Ruixue ZhengDepartment of Pediatrics, Third Military Medical University Southwest Hospital, Chongqing, China.
Xiaodong SunDepartment of Pediatrics, Third Military Medical University Southwest Hospital, Chongqing, China.
Sheng ChenDepartment of Pediatrics, Third Military Medical University Southwest Hospital, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To delineate risk factors and develop a predictive nomogram for retinopathy of prematurity (ROP) in infants with gestational age (GA) ≤34 weeks. Methods: We conducted a comprehensive retrospective analysis of infants with GA ≤34 weeks, divided into ROP and non-ROP groups based on fundus screening results. Clinical and laboratory data were collected to identify risk factors associated with ROP. Multivariable logistic regression was performed to identify independent predictors, and a nomogram was developed to predict the occurrence of ROP in infants with GA ≤34 weeks. Results: Our analysis identified five independent risk factors for ROP in infants with GA ≤34 weeks: hypertensive disorders of pregnancy (HDP), number of blood transfusions, oxygen therapy time (OTT), oxygen therapy concentration (OTC) >50%, and blood glucose spikes in the first postnatal week. These predictors were incorporated into a nomogram to estimate individual ROP risk. The predictive model achieved a C-index of 0.923 (95% CI: 0.888-0.959), indicating high predictive accuracy. Internal validation of the nomogram demonstrated excellent calibration and practical utility for clinical decision-making. Conclusions: The established predictive model, incorporating five key clinical parameters, offers clinicians a practical instrument to stratify ROP risk in neonates born at ≤34 weeks' gestation. This clinical tool demonstrates significant utility in guiding intervention protocols, potentially enhancing patient outcomes through early identification and optimized management strategies. Registration number: ChiCTR2400086213.

Indexed as

neonatal healthpredictive nomogrampremature infantsretinopathy of prematurityrisk factors

Identifiers

PMID40416432
PMCPMC12098479

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