Temporal patterns in <it>count-to-ten</it> fetal movement charts and their associations with pregnancy characteristics: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Fetal movement counting has long been suggested as a screening tool to identify impaired placental function. However, quantitative limits for decreased fetal movement perform poorly for screening purposes, indicating the need for met...

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Main Authors: Winje Brita Askeland (Author), Røislien Jo (Author), Frøen J Frederik (Author)
Format: Book
Published: BMC, 2012-11-01T00:00:00Z.
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001 doaj_60bdeb200e334b0e828eaa7d5cb9352c
042 |a dc 
100 1 0 |a Winje Brita Askeland  |e author 
700 1 0 |a Røislien Jo  |e author 
700 1 0 |a Frøen J Frederik  |e author 
245 0 0 |a Temporal patterns in <it>count-to-ten</it> fetal movement charts and their associations with pregnancy characteristics: a prospective cohort study 
260 |b BMC,   |c 2012-11-01T00:00:00Z. 
500 |a 10.1186/1471-2393-12-124 
500 |a 1471-2393 
520 |a <p>Abstract</p> <p>Background</p> <p>Fetal movement counting has long been suggested as a screening tool to identify impaired placental function. However, quantitative limits for decreased fetal movement perform poorly for screening purposes, indicating the need for methodological refinement. We aimed to identify the main individual temporal patterns in fetal movement counting charts, and explore their associations with pregnancy characteristics.</p> <p>Methods</p> <p>In a population-based prospective cohort in Norway, 2009-2011, women with singleton pregnancies counted fetal movements daily from pregnancy week 24 until delivery using a modified "count-to-ten" procedure. To account for intra-woman correlation of observations, we used functional data analysis and corresponding functional principal component analysis to identify the main individual temporal patterns in fetal movement count data. The temporal patterns are described by continuous functional principal component (FPC) curves, with an individual score on each FPC for each woman. These scores were later used as outcome variables in multivariable linear regression analyses, with pregnancy characteristics as explanatory variables.</p> <p>Results</p> <p>Fetal movement charts from 1086 pregnancies were included. Three FPC curves explained almost 99% of the variation in the temporal data, with the first FPC, representing the individual overall counting time, accounting for 91% alone. There were several statistically significant associations between the FPCs and various pregnancy characteristics. However, the effects were small and of limited clinical value.</p> <p>Conclusions</p> <p>This statistical approach for analyzing fetal movement counting data successfully captured clinically meaningful individual temporal patterns and how these patterns vary between women. Maternal body mass index, gestational age and placental site explained little of the variation in the temporal fetal movement counting patterns. Thus, a perceived decrease in fetal movement should not be attributed to a woman's basic pregnancy characteristics, but assessed as a potential marker of risk.</p> 
546 |a EN 
690 |a Fetal movement 
690 |a Kick counting 
690 |a Decreased fetal movement 
690 |a Functional data analysis 
690 |a Principal components 
690 |a Temporal pattern 
690 |a Gynecology and obstetrics 
690 |a RG1-991 
655 7 |a article  |2 local 
786 0 |n BMC Pregnancy and Childbirth, Vol 12, Iss 1, p 124 (2012) 
787 0 |n http://www.biomedcentral.com/1471-2393/12/124 
787 0 |n https://doaj.org/toc/1471-2393 
856 4 1 |u https://doaj.org/article/60bdeb200e334b0e828eaa7d5cb9352c  |z Connect to this object online.