Publication: Estimation of gestational age from fundal height: A solution for resource-poor settings
Issued Date
2012-03-07
Resource Type
ISSN
17425662
17425689
17425689
Other identifier(s)
2-s2.0-84863175565
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of the Royal Society Interface. Vol.9, No.68 (2012), 503-510
Suggested Citation
Lisa J. White, Sue J. Lee, Kasia Stepniewska, Julie A. Simpson, Saw Lu Mu Dwell, Ratree Arunjerdja, Pratap Singhasivanon, Nicholas J. White, Francois Nosten, Rose McGready Estimation of gestational age from fundal height: A solution for resource-poor settings. Journal of the Royal Society Interface. Vol.9, No.68 (2012), 503-510. doi:10.1098/rsif.2011.0376 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/13776
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Title
Estimation of gestational age from fundal height: A solution for resource-poor settings
Abstract
Many women in resource-poor settings lack access to reliable gestational age assessment because they do not know their last menstrual period; there is no ultrasound (US) and methods of newborn gestational age dating are not practised by birth attendants. A bespoke multiple-measures model was developed to predict the expected date of delivery determined by US. The results are compared with both a linear and a nonlinear model. Prospectively collected early US and serial symphysis-pubis fundal height (SFH) data were used in the models. The data were collected from Karen and Burmese women attending antenatal care on the Thai-Burmese border. The multiple-measures model performed best, resulting in a range of accuracy depending on the number of SFH measures recorded per mother (for example six SFH measurements resulted in a prediction accuracy of ±2 weeks). SFH remains the proxy for gestational age in much of the resource-poor world. While more accurate measures should be encouraged, we demonstrate that a formula that incorporates at least three SFH measures from an individual mother and the slopes between them provide a significant increase in the accuracy of prediction compared with the linear and nonlinear formulae also using multiple SFH measures. © 2011 The Royal Society.