Blanca Novillo-Del Álamo, Alicia Martínez-Varea, Carmen Sánchez-Arco, Elisa Simarro-Suárez, Iker González-Blanco, Mar Nieto-Tous, José Morales-Roselló
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Multiple maternal and fetal variables were collected, and several multivariable logistic regression analyses were applied to construct models to predict perinatal death, selecting the most accurate and reproducible according to the highest area under the curve (AUC) and the lowest Akaike Information Criteria (AIC).</p><p><strong>Results: </strong>A group of 148 pregnant women were included, and 18 perinatal deaths were registered. Univariable logistic regression selected as statistically significant variables the following: gestational age (GA) at admission, fetal sex, poor response to antihypertensive drugs, PlGF, umbilical artery (UA) pulsatility index (PI), cerebroplacental ratio (CPR), and absent/reversed ductus venosus (DV). The multivariable model, including all these parameters, presented an AUC of 0.95 and an AIC of 76.5. However, a model including only GA and fetal sex presented a similar accuracy with the highest simplicity (AUC 0.93, AIC 67.6). Finally, in fetuses with a similar GA, fetal death became dependent on PlGF and fetal sex, underlying the role of fetal sex in all circumstances.</p><p><strong>Conclusions: </strong>Female fetal sex and low PlGF are notorious predictors of perinatal death in preterm PE, only surpassed by early GA at birth.</p>","PeriodicalId":16722,"journal":{"name":"Journal of Personalized Medicine","volume":"14 10","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11508532/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prediction of Fetal Death in Preterm Preeclampsia Using Fetal Sex, Placental Growth Factor and Gestational Age.\",\"authors\":\"Blanca Novillo-Del Álamo, Alicia Martínez-Varea, Carmen Sánchez-Arco, Elisa Simarro-Suárez, Iker González-Blanco, Mar Nieto-Tous, José Morales-Roselló\",\"doi\":\"10.3390/jpm14101059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background/objectives: </strong>Preeclampsia (PE) is a systemic disease that affects 4.6% of pregnancies. Despite the existence of a first-trimester screening for the prediction of preterm PE, no consensus exists regarding neither the right moment to end the pregnancy nor the appropriate variables to estimate the prognosis. The objective of this study was to obtain a prediction model for perinatal death in patients with preterm PE, useful for clinical practice.</p><p><strong>Methods: </strong>Singleton pregnant women with PE and preterm delivery were included in an observational retrospective study. Multiple maternal and fetal variables were collected, and several multivariable logistic regression analyses were applied to construct models to predict perinatal death, selecting the most accurate and reproducible according to the highest area under the curve (AUC) and the lowest Akaike Information Criteria (AIC).</p><p><strong>Results: </strong>A group of 148 pregnant women were included, and 18 perinatal deaths were registered. Univariable logistic regression selected as statistically significant variables the following: gestational age (GA) at admission, fetal sex, poor response to antihypertensive drugs, PlGF, umbilical artery (UA) pulsatility index (PI), cerebroplacental ratio (CPR), and absent/reversed ductus venosus (DV). The multivariable model, including all these parameters, presented an AUC of 0.95 and an AIC of 76.5. However, a model including only GA and fetal sex presented a similar accuracy with the highest simplicity (AUC 0.93, AIC 67.6). 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引用次数: 0
摘要
背景/目的:子痫前期(PE)是一种全身性疾病,影响 4.6% 的妊娠。尽管有预测先兆子痫的首胎筛查,但对于结束妊娠的正确时机和估计预后的适当变量,目前还没有达成共识。本研究的目的是获得早产 PE 患者围产期死亡的预测模型,以用于临床实践:方法:一项观察性回顾研究纳入了患有早产 PE 的单胎孕妇。收集了多种母体和胎儿变量,并应用多种多变量逻辑回归分析建立围产期死亡预测模型,根据最高的曲线下面积(AUC)和最低的阿凯克信息标准(AIC)选择最准确和可重复的模型:共纳入148名孕妇,登记了18例围产期死亡。单变量逻辑回归选取了以下具有统计学意义的变量:入院时胎龄(GA)、胎儿性别、对降压药物反应差、PlGF、脐动脉(UA)搏动指数(PI)、脑-胎盘比值(CPR)和缺失/倒置的静脉导管(DV)。包括所有这些参数的多变量模型的 AUC 为 0.95,AIC 为 76.5。然而,仅包括 GA 和胎儿性别的模型具有相似的准确性和最高的简易性(AUC 0.93,AIC 67.6)。最后,在具有相似GA的胎儿中,胎儿死亡取决于PlGF和胎儿性别,这说明胎儿性别在所有情况下都起作用:结论:女性胎儿性别和低PlGF是早产PE围产儿死亡的恶性预测因素,仅次于早产GA。
Prediction of Fetal Death in Preterm Preeclampsia Using Fetal Sex, Placental Growth Factor and Gestational Age.
Background/objectives: Preeclampsia (PE) is a systemic disease that affects 4.6% of pregnancies. Despite the existence of a first-trimester screening for the prediction of preterm PE, no consensus exists regarding neither the right moment to end the pregnancy nor the appropriate variables to estimate the prognosis. The objective of this study was to obtain a prediction model for perinatal death in patients with preterm PE, useful for clinical practice.
Methods: Singleton pregnant women with PE and preterm delivery were included in an observational retrospective study. Multiple maternal and fetal variables were collected, and several multivariable logistic regression analyses were applied to construct models to predict perinatal death, selecting the most accurate and reproducible according to the highest area under the curve (AUC) and the lowest Akaike Information Criteria (AIC).
Results: A group of 148 pregnant women were included, and 18 perinatal deaths were registered. Univariable logistic regression selected as statistically significant variables the following: gestational age (GA) at admission, fetal sex, poor response to antihypertensive drugs, PlGF, umbilical artery (UA) pulsatility index (PI), cerebroplacental ratio (CPR), and absent/reversed ductus venosus (DV). The multivariable model, including all these parameters, presented an AUC of 0.95 and an AIC of 76.5. However, a model including only GA and fetal sex presented a similar accuracy with the highest simplicity (AUC 0.93, AIC 67.6). Finally, in fetuses with a similar GA, fetal death became dependent on PlGF and fetal sex, underlying the role of fetal sex in all circumstances.
Conclusions: Female fetal sex and low PlGF are notorious predictors of perinatal death in preterm PE, only surpassed by early GA at birth.
期刊介绍:
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.