Sid John, K S Joseph, John Fahey, Shiliang Liu, Sarka Lisonkova, Michael S Kramer
{"title":"Do Birthweight-For-Gestational Age Centiles Predict Serious Neonatal Morbidity and Neonatal Mortality?","authors":"Sid John, K S Joseph, John Fahey, Shiliang Liu, Sarka Lisonkova, Michael S Kramer","doi":"10.1111/ppe.70065","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Studies show that foetal and birthweight-for-gestational age centiles are poor predictors of serious neonatal morbidity and neonatal mortality (SNMM) in univariable models.</p><p><strong>Objective: </strong>We assessed the predictive performance of multivariable SNMM models based on maternal/pregnancy characteristics, with and without birthweight centiles.</p><p><strong>Methods: </strong>The study was based on all live births in the United States, 2019-2021, with data obtained from the period live birth-infant death files of the National Center for Health Statistics. SNMM was defined as any one or more of the following: 5-minute Apgar score < 4, seizures, assisted ventilation for> 30 or neonatal death. SNMM was modelled by log-linear regression on maternal/pregnancy characteristics as predictors, with and without birthweight centiles. Models were developed for live births at 24-42 weeks' and 39 weeks' gestation to all women and those with hypertensive disorders or pre-existing diabetes. Model performance was assessed using area under the curve (AUC).</p><p><strong>Results: </strong>The study population included 10,487,243 live births and 221,728 SNMM cases (2.1 per 100 live births). The models with all live births at 24-42 weeks' gestation had AUCs of 0.83 (95% confidence interval [CI] 0.82, 0.83) based on maternal/pregnancy characteristics and 0.83 (95% CI 0.83, 0.84) based on maternal/pregnancy characteristics and birthweight centiles. However, AUCs of models based on all live births at 39 weeks' gestation were 0.66 (95% CI 0.64, 0.68) with maternal/pregnancy characteristics and 0.69 (95% CI 0.68, 0.71) with maternal/pregnancy characteristics and birthweight centiles. AUCs of the models with live births at 39 weeks' gestation to women with pre-existing diabetes were 0.69 (95% CI 0.66, 0.72) based on maternal/pregnancy characteristics, and 0.77 (95% CI 0.74, 0.79) with the addition of birthweight centiles.</p><p><strong>Conclusions: </strong>Birthweight centiles improve multivariable SNMM predictive performance in specific subpopulations, although evaluation of decision thresholds is required to determine the clinical importance of improvement in predictive ability.</p>","PeriodicalId":19698,"journal":{"name":"Paediatric and perinatal epidemiology","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Paediatric and perinatal epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/ppe.70065","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Studies show that foetal and birthweight-for-gestational age centiles are poor predictors of serious neonatal morbidity and neonatal mortality (SNMM) in univariable models.
Objective: We assessed the predictive performance of multivariable SNMM models based on maternal/pregnancy characteristics, with and without birthweight centiles.
Methods: The study was based on all live births in the United States, 2019-2021, with data obtained from the period live birth-infant death files of the National Center for Health Statistics. SNMM was defined as any one or more of the following: 5-minute Apgar score < 4, seizures, assisted ventilation for> 30 or neonatal death. SNMM was modelled by log-linear regression on maternal/pregnancy characteristics as predictors, with and without birthweight centiles. Models were developed for live births at 24-42 weeks' and 39 weeks' gestation to all women and those with hypertensive disorders or pre-existing diabetes. Model performance was assessed using area under the curve (AUC).
Results: The study population included 10,487,243 live births and 221,728 SNMM cases (2.1 per 100 live births). The models with all live births at 24-42 weeks' gestation had AUCs of 0.83 (95% confidence interval [CI] 0.82, 0.83) based on maternal/pregnancy characteristics and 0.83 (95% CI 0.83, 0.84) based on maternal/pregnancy characteristics and birthweight centiles. However, AUCs of models based on all live births at 39 weeks' gestation were 0.66 (95% CI 0.64, 0.68) with maternal/pregnancy characteristics and 0.69 (95% CI 0.68, 0.71) with maternal/pregnancy characteristics and birthweight centiles. AUCs of the models with live births at 39 weeks' gestation to women with pre-existing diabetes were 0.69 (95% CI 0.66, 0.72) based on maternal/pregnancy characteristics, and 0.77 (95% CI 0.74, 0.79) with the addition of birthweight centiles.
Conclusions: Birthweight centiles improve multivariable SNMM predictive performance in specific subpopulations, although evaluation of decision thresholds is required to determine the clinical importance of improvement in predictive ability.
背景:研究表明,在单变量模型中,胎儿和出生体重占胎龄百分数是严重新生儿发病率和新生儿死亡率(SNMM)的较差预测因子。目的:我们评估了基于母亲/妊娠特征的多变量SNMM模型的预测性能,包括和不包括出生体重百分位数。方法:该研究基于2019-2021年美国所有活产婴儿,数据来自国家卫生统计中心的活产-婴儿死亡档案。SNMM被定义为以下任何一项或多项:5分钟Apgar评分30或新生儿死亡。SNMM采用对数线性回归建模,以母亲/妊娠特征作为预测因子,有或没有出生体重百分位数。研究人员为所有女性以及高血压疾病或糖尿病患者在妊娠24-42周和39周时的活产婴儿建立了模型。采用曲线下面积(AUC)评价模型性能。结果:研究人群包括10,487,243例活产和221,728例SNMM病例(每100例活产2.1例)。基于产妇/妊娠特征的24-42周活产模型的auc为0.83(95%可信区间[CI] 0.82, 0.83),基于产妇/妊娠特征和出生体重百分位数的auc为0.83 (95% CI 0.83, 0.84)。然而,基于妊娠39周所有活产的模型的auc为0.66 (95% CI 0.64, 0.68),产妇/妊娠特征为0.69 (95% CI 0.68, 0.71),产妇/妊娠特征和出生体重百分位数为0.69 (95% CI 0.68, 0.71)。根据产妇/妊娠特征,妊娠39周活产的糖尿病妇女模型的auc为0.69 (95% CI 0.66, 0.72),加上出生体重百分位数,auc为0.77 (95% CI 0.74, 0.79)。结论:出生体重百分位数改善了特定亚群的多变量SNMM预测性能,尽管需要评估决策阈值来确定预测能力改善的临床重要性。
期刊介绍:
Paediatric and Perinatal Epidemiology crosses the boundaries between the epidemiologist and the paediatrician, obstetrician or specialist in child health, ensuring that important paediatric and perinatal studies reach those clinicians for whom the results are especially relevant. In addition to original research articles, the Journal also includes commentaries, book reviews and annotations.