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Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus
BACKGROUND: Established risk factors for Gestational Diabetes Mellitus (GDM) include age, ethnicity, family history of diabetes and previous GDM. Additional significant influences have recently been demonstrated in the literature. The oral glucose tolerance test (OGTT) used for GDM diagnosis has sub...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009497/ https://www.ncbi.nlm.nih.gov/pubmed/35421942 http://dx.doi.org/10.1186/s12884-022-04629-8 |
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author | Di Filippo, Daria Bell, Chloe Chang, Melissa Han Yiin Darling, Justine Henry, Amanda Welsh, Alec |
author_facet | Di Filippo, Daria Bell, Chloe Chang, Melissa Han Yiin Darling, Justine Henry, Amanda Welsh, Alec |
author_sort | Di Filippo, Daria |
collection | PubMed |
description | BACKGROUND: Established risk factors for Gestational Diabetes Mellitus (GDM) include age, ethnicity, family history of diabetes and previous GDM. Additional significant influences have recently been demonstrated in the literature. The oral glucose tolerance test (OGTT) used for GDM diagnosis has sub-optimal sensitivity and specificity, thus often results in GDM misdiagnoses. Comprehensive screening of risk factors may allow more targeted monitoring and more accurate diagnoses, preventing the devastating consequences of untreated or misdiagnosed GDM. We aimed to develop a comprehensive online questionnaire of GDM risk factors and triangulate it with the OGTT and continuous glucose monitoring (CGM) parameters to better evaluate GDM risk and diagnosis. METHODS: Pregnant women participating in two studies on the use of CGM for GDM were invited to complete the online questionnaire. A risk score, based on published literature, was calculated for each participant response and compared with the OGTT result. A total risk score (TRS) was then calculated as a normalised sum of all risk factors. Triangulation of OGTT, TRS and CGM score of variability (CGMSV) was analysed to expand evaluation of OGTT results. RESULTS: Fifty one women completed the questionnaire; 29 were identified as ‘high-risk’ for GDM. High-risk ethnic background (p < 0.01), advanced age, a family diabetic history (p < 0.05) were associated with a positive OGTT result. The triangulation analysis (n = 45) revealed six (13%) probable misdiagnoses (both TRS and CGMSV discordant with OGTT), consisting of one probable false positive and five probable false negative by OGTT results. CONCLUSIONS: This study identified pregnant women at high risk of developing GDM based on an extended evaluation of risk factors. Triangulation of TRS, OGTT and CGMSV suggested potential misdiagnoses of the OGTT. Future studies to explore the correlation between TRS, CGMSV and pregnancy outcomes as well as additional GDM pregnancy biomarkers and outcomes to efficiently evaluate OGTT results are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-022-04629-8. |
format | Online Article Text |
id | pubmed-9009497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90094972022-04-15 Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus Di Filippo, Daria Bell, Chloe Chang, Melissa Han Yiin Darling, Justine Henry, Amanda Welsh, Alec BMC Pregnancy Childbirth Research BACKGROUND: Established risk factors for Gestational Diabetes Mellitus (GDM) include age, ethnicity, family history of diabetes and previous GDM. Additional significant influences have recently been demonstrated in the literature. The oral glucose tolerance test (OGTT) used for GDM diagnosis has sub-optimal sensitivity and specificity, thus often results in GDM misdiagnoses. Comprehensive screening of risk factors may allow more targeted monitoring and more accurate diagnoses, preventing the devastating consequences of untreated or misdiagnosed GDM. We aimed to develop a comprehensive online questionnaire of GDM risk factors and triangulate it with the OGTT and continuous glucose monitoring (CGM) parameters to better evaluate GDM risk and diagnosis. METHODS: Pregnant women participating in two studies on the use of CGM for GDM were invited to complete the online questionnaire. A risk score, based on published literature, was calculated for each participant response and compared with the OGTT result. A total risk score (TRS) was then calculated as a normalised sum of all risk factors. Triangulation of OGTT, TRS and CGM score of variability (CGMSV) was analysed to expand evaluation of OGTT results. RESULTS: Fifty one women completed the questionnaire; 29 were identified as ‘high-risk’ for GDM. High-risk ethnic background (p < 0.01), advanced age, a family diabetic history (p < 0.05) were associated with a positive OGTT result. The triangulation analysis (n = 45) revealed six (13%) probable misdiagnoses (both TRS and CGMSV discordant with OGTT), consisting of one probable false positive and five probable false negative by OGTT results. CONCLUSIONS: This study identified pregnant women at high risk of developing GDM based on an extended evaluation of risk factors. Triangulation of TRS, OGTT and CGMSV suggested potential misdiagnoses of the OGTT. Future studies to explore the correlation between TRS, CGMSV and pregnancy outcomes as well as additional GDM pregnancy biomarkers and outcomes to efficiently evaluate OGTT results are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-022-04629-8. BioMed Central 2022-04-14 /pmc/articles/PMC9009497/ /pubmed/35421942 http://dx.doi.org/10.1186/s12884-022-04629-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Di Filippo, Daria Bell, Chloe Chang, Melissa Han Yiin Darling, Justine Henry, Amanda Welsh, Alec Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title | Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title_full | Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title_fullStr | Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title_full_unstemmed | Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title_short | Development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
title_sort | development and evaluation of an online questionnaire to identify women at high and low risk of developing gestational diabetes mellitus |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009497/ https://www.ncbi.nlm.nih.gov/pubmed/35421942 http://dx.doi.org/10.1186/s12884-022-04629-8 |
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