Dataset Information

Shape information in repeated glucose curves during pregnancy provided significant physiological information for neonatal outcomes.

ABSTRACT:

Objective

To use multilevel functional principal component analysis to exploit the information inherent in the shape of longitudinally sampled glucose curves during pregnancy, and to analyse the impact of glucose curve characteristics on neonatal birth weight, percentage fat and cord blood C-peptide.

Study design and setting

A cohort study of healthy, pregnant women (n = 884). They underwent two oral glucose tolerance tests (gestational weeks 14-16 and 30-32), which gave two glucose curves per woman.

Results

Glucose values were higher, and peaked later in third trimester than in early pregnancy. The curve characteristic "general glucose level" accounted for 91% of the variation across visits, and 72% within visits. The curve characteristics "timing of postprandial peak", and "oscillating glucose levels" accounted for a larger part of the variation within visits (15% and 8%), than across visits (7% and <2%). A late postprandial peak during pregnancy, and high general glucose levels in third trimester had significant, positive effects on birth weight (p<0.05). Generally high glucose levels during pregnancy had a significant, positive impact on neonatal percentage fat (p = 0.04). High general glucose level in third trimester had a significant, positive impact on cord blood C-peptide (p = 0.004).

Conclusion

Shape information in entire OGTT curves provides significant physiological information of importance for several outcomes, and may contribute to the understanding of the metabolic changes during pregnancy.

SUBMITTER: Froslie KF

PROVIDER: S-EPMC3949679 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Shape information in repeated glucose curves during pregnancy provided significant physiological information for neonatal outcomes.

Frøslie Kathrine Frey KF Røislien Jo J Qvigstad Elisabeth E Godang Kristin K Bollerslev Jens J Henriksen Tore T Veierød Marit B MB

PloS one 20140311 3

<h4>Objective</h4>To use multilevel functional principal component analysis to exploit the information inherent in the shape of longitudinally sampled glucose curves during pregnancy, and to analyse the impact of glucose curve characteristics on neonatal birth weight, percentage fat and cord blood C-peptide.<h4>Study design and setting</h4>A cohort study of healthy, pregnant women (n = 884). They underwent two oral glucose tolerance tests (gestational weeks 14-16 and 30-32), which gave two gluco ...[more]

PMID: 24619030

Similar Datasets

Project description:UnlabelledBackgroundPlasma glucose levels are important measures in medical care and research, and are often obtained from oral glucose tolerance tests (OGTT) with repeated measurements over 2-3? hours. It is common practice to use simple summary measures of OGTT curves. However, different OGTT curves can yield similar summary measures, and information of physiological or clinical interest may be lost. Our mean aim was to extract information inherent in the shape of OGTT glucose curves, compare it with the information from simple summary measures, and explore the clinical usefulness of such information.MethodsOGTTs with five glucose measurements over two hours were recorded for 974 healthy pregnant women in their first trimester. For each woman, the five measurements were transformed into smooth OGTT glucose curves by functional data analysis (FDA), a collection of statistical methods developed specifically to analyse curve data. The essential modes of temporal variation between OGTT glucose curves were extracted by functional principal component analysis. The resultant functional principal component (FPC) scores were compared with commonly used simple summary measures: fasting and two-hour (2-h) values, area under the curve (AUC) and simple shape index (2-h minus 90-min values, or 90-min minus 60-min values). Clinical usefulness of FDA was explored by regression analyses of glucose tolerance later in pregnancy.ResultsOver 99% of the variation between individually fitted curves was expressed in the first three FPCs, interpreted physiologically as "general level" (FPC1), "time to peak" (FPC2) and "oscillations" (FPC3). FPC1 scores correlated strongly with AUC (r=0.999), but less with the other simple summary measures (-0.42?r?0.79). FPC2 scores gave shape information not captured by simple summary measures (-0.12?r?0.40). FPC2 scores, but not FPC1 nor the simple summary measures, discriminated between women who did and did not develop gestational diabetes later in pregnancy.ConclusionsFDA of OGTT glucose curves in early pregnancy extracted shape information that was not identified by commonly used simple summary measures. This information discriminated between women with and without gestational diabetes later in pregnancy.

Dataset Information

Shape information in repeated glucose curves during pregnancy provided significant physiological information for neonatal outcomes.

Objective

Study design and setting

Results

Conclusion

Publications

Shape information in repeated glucose curves during pregnancy provided significant physiological information for neonatal outcomes.

Similar Datasets

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