Evidence map›Paper›PMID 39633312›Full record

ArticleBMC pediatrics2024

Risk factors and nomogram for the prediction of intracranial hemorrhage in very preterm infants.

Yan Wang, Yong Yang, Lijun Wen, Minxu Li

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Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers 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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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yan WangDepartment of Neonatology, Dongguan Maternal and Child Health Care Hospital, Dongguan, 523000, China.
Yong YangDepartment of Neonatology, Dongguan Maternal and Child Health Care Hospital, Dongguan, 523000, China.
Lijun WenDepartment of Neonatology, Dongguan Maternal and Child Health Care Hospital, Dongguan, 523000, China.
Minxu LiDepartment of Neonatology, Dongguan Maternal and Child Health Care Hospital, Dongguan, 523000, China. dgminxu@163.com.

Funding

Dongguan Science and Technology Bureau 20221800905762
6 · The paper itself

Abstract

aimsThis study aims to identify important risk factors for intracranial hemorrhage (ICH) in very preterm infants at our institution and develop a predictive nomogram for early detection of ICH.

methodsWe retrospectively analyzed neonates with a gestational age (GA) under 32 weeks, admitted to the neonatal intensive care unit from March 2022 to July 2023. Infants were categorized into two groups based on ultrasound findings and assessed for thirteen variables including gender, GA, birth weight (BW), acidosis, among others. We used multivariate logistic regression analysis to build a prediction model and identify independent risk factors for ICH. We build a prediction model by assigning 241 cases to the training set and 103 to the validation set (ratio 7:3).

resultsAmong 344 very preterm infants, the incidence of ICH was 36.9% (89 cases) in training set. Significant differences were observed in gestational age, birth weight, antenatal corticosteroids, mechanical ventilation days, and acidosis between cases and controls. Logistic regression analysis identified gestational age (OR = 0.674), antenatal corticosteroids (OR = 0.257), acidosis (OR = 2.556), and mechanical ventilation mechanical ventilation days(OR = 0.257) as independent risk factors for ICH. The C-index of the training and validation sets was 0.814 (95% CI: 0.762-0.869) and 0.784 (95% CI: 0.693-0.875), respectively. According to decision curve analysis, our model outperformed the "None" and "All" baseline lines over a wide range of risk thresholds (0.12-0.92).

conclusionAcidosis and mechanical ventilation are independent risk factors for ICH in very preterm neonates, while higher gestational age and antenatal corticosteroid use are protective. The nomogram developed from these four factors demonstrates strong predictive accuracy and calibration, which can aid clinicians in identifying preterm infants at high risk for ICH and facilitate early diagnosis and management.

Indexed as

Intracranial HemorrhagesNomogramsAcidosisFemaleGestational AgeHumansIncidenceInfant, Extremely PrematureInfant, NewbornInfant, PrematureInfant, Premature, DiseasesLogistic ModelsMaleRespiration, ArtificialRetrospective StudiesRisk FactorsIntracranial hemorrhageNomogramPrediction modelRisk factorsVery preterm neonates

Identifiers

PMID39633312
PMCPMC11616105

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.