Assessing the risk factors and establishing multivariable prediction models for singleton macrosomia.

IF 3.1 3区医学 Q1 MEDICINE, GENERAL & INTERNAL

Frontiers in Medicine Pub Date : 2025-09-24 eCollection Date: 2025-01-01 DOI:10.3389/fmed.2025.1590283

Jinying Luo, Wenyan Huang, Suping Luo, Lin Deng, Lihua Lin, Qiuping Liao, Jianying Yan, Jinfu Zhou

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Abstract

Introduction: Fetal macrosomia is related to adverse neonatal and maternal health outcomes. Therefore, we aimed to evaluate the risk factors for macrosomia and establish multivariable prediction models to enable early identification, prevention, and mitigation of its adverse outcomes.

Methods: This retrospective case-control study included 800 singleton pregnant women who delivered in 2022 at Fujian Maternity and Child Health Hospital and Quanzhou Women and Children's Hospital. They were categorized into the macrosomia [birth weight (BW) ≥ 4,000 g, n = 400] and non-macrosomia (BW = 2,500-3,999 g, n = 400) groups according to the BW of the newborns. Prediction models in singleton fetuses during mid-to-late pregnancy and before delivery were constructed.

Results: Maternal height ≥ 165 cm [odds ratio (OR) = 2.303, 95% confidence interval (CI): 1.232-4.305], pre-pregnancy overweight (OR = 2.166, 95% CI: 1.119-4.195), pre-pregnancy obesity (OR = 3.189, 95% CI: 1.020-9.968), excessive gestational weight gain in the second trimester (OR = 2.083, 95% CI: 1.250-3.470), and at least two abnormal blood glucose values in the oral glucose tolerance test (OR = 5.267, 95% CI: 1.814-15.29) were identified as risk factors for macrosomia. Additionally, maternal abdominal circumference (AC) plus fundal length ≥ 140 cm (OR = 6.283, 95% CI: 3.976-9.927), fetal biparietal diameter ≥ 10 cm (OR = 3.373, 95% CI: 1.103-10.31), fetal head circumference ≥ 35 cm (OR = 3.473, 95% CI: 1.334-9.041), and fetal AC ≥ 36 cm at pre-delivery (OR = 23.46, 95% CI: 14.81-37.16) were risk factors for macrosomia.

Discussion: The construction of the macrosomia prediction model in singleton fetuses during mid-to-late pregnancy and before delivery showed a strong predictive value. This study identified key high-risk factors for macrosomia during the perinatal period. The macrosomia prediction model developed here is expected to enable early identification of macrosomia, allowing for timely interventions aimed at reducing the risk of adverse perinatal outcomes.

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评估单胎巨大儿的危险因素并建立多变量预测模型。

胎儿巨大儿与新生儿和产妇的不良健康结局有关。因此，我们旨在评估巨大儿的危险因素，并建立多变量预测模型，以便早期识别、预防和减轻其不良后果。方法：采用回顾性病例对照研究，纳入福建省妇幼保健院和泉州妇女儿童医院于2022年分娩的800例单胎孕妇。根据新生儿体重分为巨大儿组[出生体重(BW)≥4000 g, n = 400]和非巨大儿组（BW = 2500 ~ 3999 g, n = 400）。建立了妊娠中晚期和分娩前单胎胎儿的预测模型。结果：产妇身高≥165 cm[优势比(OR) = 2.303, 95%可信区间（CI）： 1.232 ~ 4.305]、孕前超重（OR = 2.166, 95% CI: 1.119 ~ 4.195）、孕前肥胖（OR = 3.189, 95% CI: 1.020 ~ 9.968）、妊娠中期体重增加过多（OR = 2.083, 95% CI: 1.250 ~ 3.470）、口服糖耐量试验中至少2项血糖异常（OR = 5.267, 95% CI: 1.814 ~ 15.29）被确定为巨大儿的危险因素。此外，母体腹围（AC）加子宫底长≥140 cm （OR = 6.283, 95% CI: 3.976 ~ 9.927）、胎儿双顶径≥10 cm （OR = 3.373, 95% CI: 1.103 ~ 10.31）、胎儿头围≥35 cm （OR = 3.473, 95% CI: 1.334 ~ 9.041）、产前胎儿腹围≥36 cm （OR = 23.46, 95% CI: 14.81 ~ 37.16）是巨大儿的危险因素。讨论：构建妊娠中晚期及分娩前单胎胎儿巨大儿预测模型具有较强的预测价值。本研究确定了围产期巨大儿的高危因素。这里开发的巨大儿预测模型有望使巨大儿的早期识别，允许及时干预，旨在降低不良围产期结局的风险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Medicine Medicine-General Medicine

CiteScore

5.10

自引率

5.10%

发文量

3710

审稿时长

12 weeks

期刊介绍： Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate - the use of patient-reported outcomes under real world conditions - the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines - the scientific bases for guidelines and decisions from regulatory authorities - access to medicinal products and medical devices worldwide - addressing the grand health challenges around the world