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Correlation models for monitoring fetal growth
- Source :
- Statistical Methods in Medical Research
- Publication Year :
- 2020
- Publisher :
- SAGE Publications, 2020.
-
Abstract
- Ultrasound growth measurements are monitored to evaluate if a fetus is growing normally compared with a defined standard chart at a specified gestational age. Using data from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st project, we have modelled the longitudinal dependence of fetal head circumference, biparietal diameter, occipito-frontal diameter, abdominal circumference, and femur length using a two-stage approach. The first stage involved finding a suitable transformation of the raw fetal measurements (as the marginal distributions of ultrasound measurements were non-normal) to standardized deviations (Z-scores). In the second stage, a correlation model for a Gaussian process is fitted, yielding a correlation for any pair of observations made between 14 and 40 weeks. The correlation structure of the fetal Z-score can be used to assess whether the growth, for example, between successive measurements is satisfactory. The paper is accompanied by a Shiny application, see https://lxiao5.shinyapps.io/shinycalculator/ .
- Subjects :
- Statistics and Probability
medicine.medical_specialty
Longitudinal study
Epidemiology
Gestational Age
01 natural sciences
Ultrasonography, Prenatal
Correlation
Fetal Development
010104 statistics & probability
03 medical and health sciences
0302 clinical medicine
Health Information Management
Chart
Pregnancy
Fetal growth
medicine
Humans
Femur
Longitudinal Studies
0101 mathematics
Fetus
030219 obstetrics & reproductive medicine
Obstetrics
business.industry
Ultrasound
longitudinal study
Gestational age
Articles
Fetal health
reference chart
correlation
Female
business
Subjects
Details
- Language :
- English
- ISSN :
- 14770334 and 09622802
- Volume :
- 29
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- Statistical Methods in Medical Research
- Accession number :
- edsair.doi.dedup.....60cb0b114584219ed98ffd73f8c667c9