Literature DB >> 21895614

First trimester prediction of small- and large-for-gestation neonates by an integrated model incorporating ultrasound parameters, biochemical indices and maternal characteristics.

Ioannis Papastefanou1, Athena P Souka1,2, Athanasios Pilalis1,2, Makarios Eleftheriades2, Vasiliki Michalitsi1, Demetrios Kassanos1.   

Abstract

OBJECTIVE: To identify maternal/pregnancy characteristics, first trimester ultrasound parameters and biochemical indices which are significant independent predictors of small-for-gestational age (SGA) and large-for-gestational age (LGA) neonates.
DESIGN: Retrospective cross-sectional study.
SETTING: Two fetal Medicine Units. POPULATION: 4 702 singleton pregnancies presenting for screening for chromosomal abnormalities by nuchal translucency and maternal serum biochemistry at 11-14 weeks.
METHODS: Reference ranges for birthweight applied to our population were constructed by the Royston and Wright method. Multiple logistic regression was applied to develop first trimester prediction models for SGA and LGA. MAIN OUTCOME MEASURES: Birth of SGA or LGA neonate.
RESULTS: Maternal height, parity, smoking, assisted conception, delta crown-rump length, delta nuchal translucency, free beta human chorionic gonadotrophin and pregnancy-associated plasma protein-A were significant independent predictors of SGA. Maternal weight and height, smoking, delta crown-rump length and delta nuchal translucency were significant independent predictors of LGA. Models for SGA (AUC=0.7296, CI: 0.69-0.76, p<0.0001) and LGA (AUC=0.6901, CI: 0.65-0.72, p<0.0001) were derived, applicable to routine obstetric population at low risk for these conditions. For 20% screen positive rate the modeling achieves sensitivities of about 55% for SGA and 48% for LGA neonates.
CONCLUSION: Prediction for birthweight deviations is feasible using data available at the routine 11-14 weeks' examination. Delta CRL and delta nuchal translucency were significant independent predictors for both SGA and LGA.
© 2011 The Authors Acta Obstetricia et Gynecologica Scandinavica © 2011 Nordic Federation of Societies of Obstetrics and Gynecology.

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Year:  2011        PMID: 21895614     DOI: 10.1111/j.1600-0412.2011.01271.x

Source DB:  PubMed          Journal:  Acta Obstet Gynecol Scand        ISSN: 0001-6349            Impact factor:   3.636


  10 in total

1.  Risk Assessment at 11-14-Week Antenatal Visit: A Tertiary Referral Center Experience from South India.

Authors:  Anusha Vellamkondu; Akhila Vasudeva; Rajeshwari G Bhat; Asha Kamath; Sapna V Amin; Lavanya Rai; Pratap Kumar
Journal:  J Obstet Gynaecol India       Date:  2017-04-08

2.  Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study.

Authors:  Stefan Kuhle; Bryan Maguire; Hongqun Zhang; David Hamilton; Alexander C Allen; K S Joseph; Victoria M Allen
Journal:  BMC Pregnancy Childbirth       Date:  2018-08-15       Impact factor: 3.007

3.  Increased nuchal translucency and pregnancy outcomes: experience of Başkent University Ankara Hospital.

Authors:  Nihal Şahin Uysal; Çağrı Gülümser; Zerrin Yılmaz Çelik; Filiz Bilgin Yanık
Journal:  Turk J Obstet Gynecol       Date:  2019-07-03

4.  Role of pregnancy-associated plasma protein A (PAPP-A) and human-derived chorionic gonadotrophic hormone (free β-hCG) serum levels as a marker in predicting of Small for gestational age (SGA): A cohort study.

Authors:  Maryam Honarjoo; Elahe Zarean; Mohammad Javad Tarrahi; Shahnaz Kohan
Journal:  J Res Med Sci       Date:  2021-11-29       Impact factor: 1.852

5.  A Predictive Model for Large-for-Gestational-Age Infants among Korean Women with Gestational Diabetes Mellitus Using Maternal Characteristics and Fetal Biometric Parameters.

Authors:  Hee-Sun Kim; Soo-Young Oh; Geum Joon Cho; Suk-Joo Choi; Soon Cheol Hong; Ja-Young Kwon; Han Sung Kwon
Journal:  J Clin Med       Date:  2022-08-23       Impact factor: 4.964

Review 6.  Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes.

Authors:  Sofia Nahavandi; Jas-Mine Seah; Alexis Shub; Christine Houlihan; Elif I Ekinci
Journal:  Front Endocrinol (Lausanne)       Date:  2018-07-31       Impact factor: 5.555

7.  External validation and clinical usefulness of first-trimester prediction models for small- and large-for-gestational-age infants: a prospective cohort study.

Authors:  Lje Meertens; Ljm Smits; Smj van Kuijk; R Aardenburg; Ima van Dooren; J Langenveld; I M Zwaan; Mea Spaanderman; Hcj Scheepers
Journal:  BJOG       Date:  2019-01-17       Impact factor: 6.531

Review 8.  Fetal Growth Acceleration-Current Approach to the Big Baby Issue.

Authors:  Jan Modzelewski; Anna Kajdy; Katarzyna Muzyka-Placzyńska; Dorota Sys; Michał Rabijewski
Journal:  Medicina (Kaunas)       Date:  2021-03-02       Impact factor: 2.430

9.  Predictability of Macrosomic Birth based on Maternal Factors and Fetal Aneuploidy Screening Biochemical Markers in Hyperglycemic Mothers.

Authors:  Junguk Hur; Jinho Yoo; Dayeon Shin; Kwang-Hyun Baek; Sunwha Park; Kyung Ju Lee
Journal:  Int J Med Sci       Date:  2021-05-13       Impact factor: 3.738

10.  Vitamin D Deficiency, Excessive Gestational Weight Gain, and Oxidative Stress Predict Small for Gestational Age Newborns Using an Artificial Neural Network Model.

Authors:  Otilia Perichart-Perera; Valeria Avila-Sosa; Juan Mario Solis-Paredes; Araceli Montoya-Estrada; Enrique Reyes-Muñoz; Ameyalli M Rodríguez-Cano; Carla P González-Leyva; Maribel Sánchez-Martínez; Guadalupe Estrada-Gutierrez; Claudine Irles
Journal:  Antioxidants (Basel)       Date:  2022-03-17
  10 in total

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