Fetal growth: a comparison of growth curves with mathematical modeling

Shields, Laurence E.; Huff, Robert W.; Jackson, G. Marc; Olive, D.; Patterson, Robert

doi:10.7863/jum.1993.12.5.271

Cited by 17 publications

(10 citation statements)

References 5 publications

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“…More importantly, when the errors occur in the opposite directions in two scans in early pregnancy, the deviation of term projection is amplified 53. So far, the literature has not provided convincing evidence that the Rossavik model is superior to computationally simpler models 25,28,54,55…”

Section: The Individualized Approaches To Define Fetal Size Abnormmentioning

confidence: 99%

Defining normal and abnormal fetal growth: promises and challenges

Zhang

Merialdi

Platt

et al. 2010

American Journal of Obstetrics and Gynecology

229

170

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Normal fetal growth is a critical component of a healthy pregnancy and influences the long-term health of the offspring. However, defining normal and abnormal fetal growth has been a long-standing challenge in clinical practice and research. The authors review various references and standards that are widely used to evaluate fetal growth, and discuss common pitfalls of current definitions of abnormal fetal growth. Pros and cons of different approaches to customize fetal growth standards are described. The authors further discuss recent advances towards an integrated definition for fetal growth restriction. Such a definition may incorporate fetal size with the status of placental health measured by maternal and fetal Doppler velocimetry and biomarkers, biophysical findings and genetics. Although the concept of an integrated definition appears promising, further development and testing are required. An improved definition of abnormal fetal growth should benefit both research and clinical practice.

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Section: The Individualized Approaches To Define Fetal Size Abnormmentioning

confidence: 99%

Defining normal and abnormal fetal growth: promises and challenges

Zhang

Merialdi

Platt

et al. 2010

American Journal of Obstetrics and Gynecology

229

170

View full text Add to dashboard Cite

show abstract

“…In this procedure, the percentile for a given size parameter measurement is derived from a population size curve, either at birth (8,9) or in the second or third trimesters (6,7). The specified percentile is then used to identify a percentile line of the prenatal population size curve for the same population (7,8) or a different one (6). This percentile line is assumed to be the expected trajectory for the size parameter in the fetus being studied.…”

Section: Introductionmentioning

confidence: 99%

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

Deter

Lee

Sangi‐Haghpeykar

et al. 2014

The Journal of Maternal-Fetal & Neonatal Medicine

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Objective To compare third trimester size trajectory prediction errors for three individualized fetal growth assessment methods. Methods This study utilized longitudinal measurements of 9 directly measured size parameters in 118 fetuses with normal neonatal growth outcomes. Expected Value [EV] function coefficients and variance components were obtained using two-level random coefficient modeling. Growth models [IGA] or EV coefficients and variance components [PLM, CPM] were used to calculate predicted values at approximately 400 3rd trimester time points. Percent Deviations [% Dev] calculated at these time points were expressed as percentages of their IGA, age-specific reference ranges (T%Dev). Third trimester T%Dev values were averaged [aT%Dev] for each parameter. Means ± SD’s for sets of aT%Dev values derived from each method [IGA, PLM, CPM] were calculated and compared. Results Mean aT%Dev values for nine parameters were: 1) IGA: – 4.3 to 5.2% [9/9 not different from zero]; 2) PLM: −32.7% to 25.6% [4/9 not different from zero]; and 3) CPM: −20.4% to 17.4% [5/9 not different from zero]. Seven of nine systematic deviations from zero were statistically significant when IGA values were compared to either PLM or CPM values. Variabilities were smaller for IGA when compared to those for PLM or CPM, with 1) 5/9 being statistically significant [IGA vs. PLM], 2) 2/9 being statistically significant [IGA vs. CPM] and 3) 5/9 being statistically significant [PLM vs. CPM]. Conclusions Significant differences in the agreement between predicted third trimester size parameters and their measured values were found for the three methods tested. With most parameters, IGA gave smaller mean aT%Dev values and smaller variabilities. The CPM method was better than PLM approach for most but not all parameters. These results suggest that 3rd trimester size trajectories are best characterized by IGA in fetuses with normal growth outcomes.

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“…The Rossavik model 37 calculates an expected growth curve from two scans at about 18 and 24-26 weeks. In addition to have failed to demonstrate an improvement in the prediction of fetal weight, 38 there are several concerns regarding it conceptual framework. First, ultrasound error at each of the sequential scans can lead to substantial variation when forward projecting the growth curve that has been calculated from these measurements.…”

Section: Biometric Evaluationmentioning

confidence: 99%