Literature DB >> 17557369

A direct method for ultrasound prediction of day of delivery: a new, population-based approach.

H K Gjessing1, P Grøttum, S H Eik-Nes.   

Abstract

OBJECTIVES: To introduce a direct population-based method for prediction of term based on ultrasound measurements of the biparietal diameter and femur length in the second trimester of pregnancy.
METHODS: Our data consisted of 41 343 ultrasound scans from a non-selected population, prospectively collected during the years 1987-2004. Using measurements of biparietal diameter and femur length, we constructed prediction curves for term by computing median remaining time of pregnancy from the ultrasound measurement to birth. A local linear quantile regression method was used to smooth the median and quantile curves.
RESULTS: The quality of term prediction was stable over the prediction range for both biparietal diameter (25-60 mm) and femur length (11-42 mm). The femur-based predictions were nearly as good as those of the biparietal diameter. For the biparietal diameter, the median of the prediction residual was -0.09 days; 87.2% of the births fell within +/- 14 days of the predicted day of delivery, 3.5% births were classified as preterm and 4.3% as post-term. The corresponding figures for femur length were - 0.04 days, 86.7%, 3.6% and 4.5%. The covariates maternal age, parity, mother's smoking habits, sex of the fetus and examination year generally affected the predicted term by less than 1 day.
CONCLUSIONS: This direct ultrasound-based prediction of term using population-based data avoids selection biases possibly present in smaller prospective samples. The model obviates the dependence on last menstrual period found in standard methods for term prediction, and allows an immediate assessment of prediction quality in a population setting. The femur-based predictions had a quality similar to those based on the biparietal diameter. The model can be updated continuously as new data are collected.

Mesh:

Year:  2007        PMID: 17557369     DOI: 10.1002/uog.4053

Source DB:  PubMed          Journal:  Ultrasound Obstet Gynecol        ISSN: 0960-7692            Impact factor:   7.299


  6 in total

1.  Placental pathology in pregnancies with maternally perceived decreased fetal movement--a population-based nested case-cohort study.

Authors:  Brita Askeland Winje; Borghild Roald; Nina Petrov Kristensen; J Frederik Frøen
Journal:  PLoS One       Date:  2012-06-19       Impact factor: 3.240

2.  Fetal movement counting improved identification of fetal growth restriction and perinatal outcomes--a multi-centre, randomized, controlled trial.

Authors:  Eli Saastad; Brita A Winje; Babill Stray Pedersen; J Frederik Frøen
Journal:  PLoS One       Date:  2011-12-21       Impact factor: 3.240

3.  Wavelet principal component analysis of fetal movement counting data preceding hospital examinations due to decreased fetal movement: a prospective cohort study.

Authors:  Brita Askeland Winje; Jo Røislien; Eli Saastad; Jorid Eide; Christopher Finne Riley; Babill Stray-Pedersen; J Frederik Frøen
Journal:  BMC Pregnancy Childbirth       Date:  2013-09-05       Impact factor: 3.007

4.  Prediction of gestational age based on genome-wide differentially methylated regions.

Authors:  J Bohlin; S E Håberg; P Magnus; S E Reese; H K Gjessing; M C Magnus; C L Parr; C M Page; S J London; W Nystad
Journal:  Genome Biol       Date:  2016-10-07       Impact factor: 13.583

5.  Prelabor rupture of membranes and the association with cerebral palsy in term born children: a national registry-based cohort study.

Authors:  Maren Mynarek; Solveig Bjellmo; Stian Lydersen; Kristin Melheim Strand; Jan Egil Afset; Guro L Andersen; Torstein Vik
Journal:  BMC Pregnancy Childbirth       Date:  2020-01-31       Impact factor: 3.007

6.  An EPIC predictor of gestational age and its application to newborns conceived by assisted reproductive technologies.

Authors:  Astanand Jugessur; Jon Bohlin; Kristine L Haftorn; Yunsung Lee; William R P Denault; Christian M Page; Haakon E Nustad; Robert Lyle; Håkon K Gjessing; Anni Malmberg; Maria C Magnus; Øyvind Næss; Darina Czamara; Katri Räikkönen; Jari Lahti; Per Magnus; Siri E Håberg
Journal:  Clin Epigenetics       Date:  2021-04-19       Impact factor: 6.551

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.