Literature DB >> 20415768

The predictive ability of conditional fetal growth percentiles.

Jennifer A Hutcheon1, Grace M Egeland, Lucie Morin, Sara J Meltzer, Geir Jacobsen, Robert W Platt.   

Abstract

Conditional fetal growth percentiles are percentiles that are calculated taking into account (conditional on) an infant's weight earlier in pregnancy. Although they have been proposed in the statistical literature as a more methodologically appropriate method of measuring fetal growth, their ability to predict adverse perinatal outcomes due to fetal growth restriction is unknown. Using a large, unselected clinical ultrasound database at the Royal Victoria Hospital in Montreal, Canada, we calculated conditional growth percentiles for infants' weight at birth, given their weight at the time of a routine 32- or 33-week ultrasound. The risk of adverse perinatal outcome (perinatal mortality, low Apgar, acidaemia, or seizures/organ failure due to asphyxia) among small-for-gestational-age infants (SGA) as established by conditional growth percentiles was calculated as well as the risk among infants classified as SGA by conventional weight-for-gestational-age percentiles. Regardless of the threshold used to define SGA (fifth, 10th, 15th, 20th), conditional percentiles did not appear to improve the identification of adverse perinatal outcomes compared with conventional weight-for-gestational-age charts. Further work is needed to confirm our results as well as to explore potential reasons for the lack of benefits from using a measure of growth instead of size to identify fetal growth restriction.

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Year:  2010        PMID: 20415768     DOI: 10.1111/j.1365-3016.2010.01101.x

Source DB:  PubMed          Journal:  Paediatr Perinat Epidemiol        ISSN: 0269-5022            Impact factor:   3.980


  4 in total

1.  Modeling fetal weight for gestational age: a comparison of a flexible multi-level spline-based model with other approaches.

Authors:  Luc Villandré; Jennifer A Hutcheon; Maria Esther Perez Trejo; Haim Abenhaim; Geir Jacobsen; Robert W Platt
Journal:  Int J Biostat       Date:  2011-08-23       Impact factor: 0.968

2.  Personalized third-trimester fetal growth evaluation: comparisons of individualized growth assessment, percentile line and conditional probability methods.

Authors:  Russell L Deter; Wesley Lee; Haleh Sangi-Haghpeykar; Adi L Tarca; Jia Li; Lami Yeo; Roberto Romero
Journal:  J Matern Fetal Neonatal Med       Date:  2015-09-25

3.  Identifying outliers and implausible values in growth trajectory data.

Authors:  Seungmi Yang; Jennifer A Hutcheon
Journal:  Ann Epidemiol       Date:  2015-10-19       Impact factor: 3.797

4.  Small Size at Birth or Abnormal Intrauterine Growth Trajectory: Which Matters More for Child Growth?

Authors:  Jennifer A Hutcheon; Geir W Jacobsen; Michael S Kramer; Marit Martinussen; Robert W Platt
Journal:  Am J Epidemiol       Date:  2016-06-02       Impact factor: 4.897

  4 in total

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