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Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome

OBJECTIVE: To explore the diagnostic value of homeostasis model assessment of insulin resistance (HOMA-IR), visceral fat index (VAI), and prepregnancy body mass index (BMI) in gestational metabolic syndrome (GMS). METHODS: From December 2019 to March 2021,122 GMS high-risk pregnant women who receive...

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Autores principales: Zhao, Laiping, Huang, Lichun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486542/
https://www.ncbi.nlm.nih.gov/pubmed/34603475
http://dx.doi.org/10.1155/2021/6709725
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author Zhao, Laiping
Huang, Lichun
author_facet Zhao, Laiping
Huang, Lichun
author_sort Zhao, Laiping
collection PubMed
description OBJECTIVE: To explore the diagnostic value of homeostasis model assessment of insulin resistance (HOMA-IR), visceral fat index (VAI), and prepregnancy body mass index (BMI) in gestational metabolic syndrome (GMS). METHODS: From December 2019 to March 2021,122 GMS high-risk pregnant women who received routine antenatal clinic visits and planned to give birth in our hospital were selected as the research objects. Pregnant women were divided into the GMS group (n = 79) and the control group (n = 43) according to GMS diagnostic criteria during the gestation period of 32–36 weeks. The general information such as age and gestational week of pregnant women as well as HOMA-IR, VAI, and BMI before pregnancy were compared between the two groups. The glucose and lipid metabolism indexes of pregnant women in two groups were analyzed, the detection rates of HOMA-IR, VAI, and prepregnancy BMI in GMS between the two groups were compared. Logistic regression was used to analyze the risk factors for GMS in pregnant women, and receiver operating characteristic curve (ROC) was used to analyze the diagnostic value of HOMA-IR, VAI, prepregnancy BMI, and the combination of the three for GMS. RESULTS: The body weight, systolic blood pressure, and diastolic blood pressure of the GMS group were higher than those of the control group, and the differences were statistically significant (P < 0.05). There was no significant difference in age, gestational week, and height between the two groups (P > 0.05). The levels of FPG, FINS, TC, TG, LDL-C, and FFA in the GMS group were higher than the control group, the level of HDL-C in the GMS group was lower than the control group, and the difference was statistically significant (P < 0.05). The levels of HOMA-IR, VAI, and prepregnancy BMI in the GMS group were higher than those in the control group, and the differences were statistically significant (P < 0.05). The positive detection rates of HOMA-IR, VAI, and prepregnancy BMI in the GMS group were 83.54%, 86.07%, and 81.01%, respectively. There was no significant difference in the positive detection rates of HOMA-IR, VAI, and prepregnancy BMI between the two groups (P > 0.05). High levels of HOMA-IR, VAI, and prepregnancy BMI were risk factors for GMS in pregnant women (P < 0.05). ROC curve showed area under the curve for HOMA-IR was 0.810, area under the curve for VAI was 0.771, and area under the curve for prepregnancy BMI was 0.749. The AUC for the combination of HOMA-IR, VAI, and prepregnancy BMI was 0.918. CONCLUSION: HOMA-IR, VAI, and prepregnancy BMI in GMS have a high detection rate and certain diagnostic value, and the combination of the three has higher clinical value.
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spelling pubmed-84865422021-10-02 Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome Zhao, Laiping Huang, Lichun Evid Based Complement Alternat Med Research Article OBJECTIVE: To explore the diagnostic value of homeostasis model assessment of insulin resistance (HOMA-IR), visceral fat index (VAI), and prepregnancy body mass index (BMI) in gestational metabolic syndrome (GMS). METHODS: From December 2019 to March 2021,122 GMS high-risk pregnant women who received routine antenatal clinic visits and planned to give birth in our hospital were selected as the research objects. Pregnant women were divided into the GMS group (n = 79) and the control group (n = 43) according to GMS diagnostic criteria during the gestation period of 32–36 weeks. The general information such as age and gestational week of pregnant women as well as HOMA-IR, VAI, and BMI before pregnancy were compared between the two groups. The glucose and lipid metabolism indexes of pregnant women in two groups were analyzed, the detection rates of HOMA-IR, VAI, and prepregnancy BMI in GMS between the two groups were compared. Logistic regression was used to analyze the risk factors for GMS in pregnant women, and receiver operating characteristic curve (ROC) was used to analyze the diagnostic value of HOMA-IR, VAI, prepregnancy BMI, and the combination of the three for GMS. RESULTS: The body weight, systolic blood pressure, and diastolic blood pressure of the GMS group were higher than those of the control group, and the differences were statistically significant (P < 0.05). There was no significant difference in age, gestational week, and height between the two groups (P > 0.05). The levels of FPG, FINS, TC, TG, LDL-C, and FFA in the GMS group were higher than the control group, the level of HDL-C in the GMS group was lower than the control group, and the difference was statistically significant (P < 0.05). The levels of HOMA-IR, VAI, and prepregnancy BMI in the GMS group were higher than those in the control group, and the differences were statistically significant (P < 0.05). The positive detection rates of HOMA-IR, VAI, and prepregnancy BMI in the GMS group were 83.54%, 86.07%, and 81.01%, respectively. There was no significant difference in the positive detection rates of HOMA-IR, VAI, and prepregnancy BMI between the two groups (P > 0.05). High levels of HOMA-IR, VAI, and prepregnancy BMI were risk factors for GMS in pregnant women (P < 0.05). ROC curve showed area under the curve for HOMA-IR was 0.810, area under the curve for VAI was 0.771, and area under the curve for prepregnancy BMI was 0.749. The AUC for the combination of HOMA-IR, VAI, and prepregnancy BMI was 0.918. CONCLUSION: HOMA-IR, VAI, and prepregnancy BMI in GMS have a high detection rate and certain diagnostic value, and the combination of the three has higher clinical value. Hindawi 2021-09-24 /pmc/articles/PMC8486542/ /pubmed/34603475 http://dx.doi.org/10.1155/2021/6709725 Text en Copyright © 2021 Laiping Zhao and Lichun Huang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhao, Laiping
Huang, Lichun
Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title_full Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title_fullStr Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title_full_unstemmed Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title_short Predictive Value of Homeostasis Model Assessment of Insulin Resistance, Visceral Fat Index, and Prepregnancy Body Mass Index in Gestational Metabolic Syndrome
title_sort predictive value of homeostasis model assessment of insulin resistance, visceral fat index, and prepregnancy body mass index in gestational metabolic syndrome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486542/
https://www.ncbi.nlm.nih.gov/pubmed/34603475
http://dx.doi.org/10.1155/2021/6709725
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