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A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history

BACKGROUND: In India, the prevalence of gestational diabetes mellitus (GDM) is estimated to be 10%–14.3%, which is higher than in Western countries. Out of 10 pregnancies, one is associated with diabetes, and 90% of them are GDM. GDM influences not only maternal complications but also neonatal compl...

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Autores principales: Dhutraj, Pooja G., Shinde, Kiran P., Singh, Khushboo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810964/
https://www.ncbi.nlm.nih.gov/pubmed/36618139
http://dx.doi.org/10.4103/jfmpc.jfmpc_516_22
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author Dhutraj, Pooja G.
Shinde, Kiran P.
Singh, Khushboo
author_facet Dhutraj, Pooja G.
Shinde, Kiran P.
Singh, Khushboo
author_sort Dhutraj, Pooja G.
collection PubMed
description BACKGROUND: In India, the prevalence of gestational diabetes mellitus (GDM) is estimated to be 10%–14.3%, which is higher than in Western countries. Out of 10 pregnancies, one is associated with diabetes, and 90% of them are GDM. GDM influences not only maternal complications but also neonatal complications. Moreover, women with GDM and their children are at increased risk of developing type-2 diabetes later. METHOD AND MATERIAL: A cross-sectional study was conducted on 220 patients to develop an early risk prediction tool for GDM for antenatal women diagnosed with this condition based on their characteristics and past obstetric history. RESULTS: The mean age (in years) of patients in the study was 27.69 ± 5.07. One hundred and twenty-six patients (57.27%) had a family history of DM in their first relatives. Eighty-three (58.86%) patients had a history of complications in a previous pregnancy. CONCLUSION: The early risk predictor tool with age, prepregnancy, body mass index (BMI), family history of DM, gravidity, past history of menstrual cycle, and complications in a previous pregnancy was easy to operate, and all predictors were easily obtained in the first trimester in primary healthcare centers.
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spelling pubmed-98109642023-01-05 A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history Dhutraj, Pooja G. Shinde, Kiran P. Singh, Khushboo J Family Med Prim Care Original Article BACKGROUND: In India, the prevalence of gestational diabetes mellitus (GDM) is estimated to be 10%–14.3%, which is higher than in Western countries. Out of 10 pregnancies, one is associated with diabetes, and 90% of them are GDM. GDM influences not only maternal complications but also neonatal complications. Moreover, women with GDM and their children are at increased risk of developing type-2 diabetes later. METHOD AND MATERIAL: A cross-sectional study was conducted on 220 patients to develop an early risk prediction tool for GDM for antenatal women diagnosed with this condition based on their characteristics and past obstetric history. RESULTS: The mean age (in years) of patients in the study was 27.69 ± 5.07. One hundred and twenty-six patients (57.27%) had a family history of DM in their first relatives. Eighty-three (58.86%) patients had a history of complications in a previous pregnancy. CONCLUSION: The early risk predictor tool with age, prepregnancy, body mass index (BMI), family history of DM, gravidity, past history of menstrual cycle, and complications in a previous pregnancy was easy to operate, and all predictors were easily obtained in the first trimester in primary healthcare centers. Wolters Kluwer - Medknow 2022-10 2022-10-31 /pmc/articles/PMC9810964/ /pubmed/36618139 http://dx.doi.org/10.4103/jfmpc.jfmpc_516_22 Text en Copyright: © 2022 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Dhutraj, Pooja G.
Shinde, Kiran P.
Singh, Khushboo
A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title_full A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title_fullStr A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title_full_unstemmed A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title_short A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
title_sort cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810964/
https://www.ncbi.nlm.nih.gov/pubmed/36618139
http://dx.doi.org/10.4103/jfmpc.jfmpc_516_22
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