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Shape information from glucose curves: Functional data analysis compared with traditional summary measures
BACKGROUND: Plasma 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 yi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570313/ https://www.ncbi.nlm.nih.gov/pubmed/23327294 http://dx.doi.org/10.1186/1471-2288-13-6 |
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author | Frøslie, Kathrine Frey Røislien, Jo Qvigstad, Elisabeth Godang, Kristin Bollerslev, Jens Voldner, Nanna Henriksen, Tore Veierød, Marit B |
author_facet | Frøslie, Kathrine Frey Røislien, Jo Qvigstad, Elisabeth Godang, Kristin Bollerslev, Jens Voldner, Nanna Henriksen, Tore Veierød, Marit B |
author_sort | Frøslie, Kathrine Frey |
collection | PubMed |
description | BACKGROUND: Plasma 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. METHODS: OGTTs 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. RESULTS: Over 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. CONCLUSIONS: FDA 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. |
format | Online Article Text |
id | pubmed-3570313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35703132013-02-15 Shape information from glucose curves: Functional data analysis compared with traditional summary measures Frøslie, Kathrine Frey Røislien, Jo Qvigstad, Elisabeth Godang, Kristin Bollerslev, Jens Voldner, Nanna Henriksen, Tore Veierød, Marit B BMC Med Res Methodol Research Article BACKGROUND: Plasma 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. METHODS: OGTTs 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. RESULTS: Over 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. CONCLUSIONS: FDA 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. BioMed Central 2013-01-17 /pmc/articles/PMC3570313/ /pubmed/23327294 http://dx.doi.org/10.1186/1471-2288-13-6 Text en Copyright ©2013 Frøslie et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Frøslie, Kathrine Frey Røislien, Jo Qvigstad, Elisabeth Godang, Kristin Bollerslev, Jens Voldner, Nanna Henriksen, Tore Veierød, Marit B Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title | Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title_full | Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title_fullStr | Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title_full_unstemmed | Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title_short | Shape information from glucose curves: Functional data analysis compared with traditional summary measures |
title_sort | shape information from glucose curves: functional data analysis compared with traditional summary measures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570313/ https://www.ncbi.nlm.nih.gov/pubmed/23327294 http://dx.doi.org/10.1186/1471-2288-13-6 |
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