The yield of early-pregnancy homeostasis of model assessment -insulin resistance (HOMA-IR) for predicting gestational diabetes mellitus in different body mass index and age groups
BackgroundEarly prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development...
Saved in:
Published in | BMC pregnancy and childbirth Vol. 23; no. 1; pp. 1 - 9 |
---|---|
Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
BioMed Central
28.11.2023
BMC |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | BackgroundEarly prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.Materials and methodsThis study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018–2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24–28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.ResultsGDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6–6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.ConclusionThe present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM. |
---|---|
AbstractList | BackgroundEarly prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.Materials and methodsThis study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018–2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24–28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.ResultsGDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6–6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.ConclusionThe present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM. Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.BACKGROUNDEarly prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories.This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018-2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24-28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.MATERIALS AND METHODSThis study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018-2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24-28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM.GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6-6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.RESULTSGDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6-6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI.The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM.CONCLUSIONThe present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM. Abstract Background Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories. Materials and methods This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018–2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24–28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM. Results GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6–6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI. Conclusion The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM. |
ArticleNumber | 822 |
Author | Ghasemi, Amirabbas Ghafelehbashi, Seyyed Hamidreza Badri, Milad Hashemipour, Sima Chopani, Sarah Mirzaeei Kelishomi, Sara Esmaeili Modarresnia, Leila Panahi, Hamidreza Kolaji, Sepideh Zohal, Mahnaz |
Author_xml | – sequence: 1 givenname: Sima surname: Hashemipour fullname: Hashemipour, Sima – sequence: 2 givenname: Mahnaz surname: Zohal fullname: Zohal, Mahnaz – sequence: 3 givenname: Leila surname: Modarresnia fullname: Modarresnia, Leila – sequence: 4 givenname: Sepideh surname: Kolaji fullname: Kolaji, Sepideh – sequence: 5 givenname: Hamidreza surname: Panahi fullname: Panahi, Hamidreza – sequence: 6 givenname: Milad surname: Badri fullname: Badri, Milad – sequence: 7 givenname: Sarah Mirzaeei surname: Chopani fullname: Chopani, Sarah Mirzaeei – sequence: 8 givenname: Sara Esmaeili surname: Kelishomi fullname: Kelishomi, Sara Esmaeili – sequence: 9 givenname: Amirabbas surname: Ghasemi fullname: Ghasemi, Amirabbas – sequence: 10 givenname: Seyyed Hamidreza orcidid: 0000-0001-6786-0126 surname: Ghafelehbashi fullname: Ghafelehbashi, Seyyed Hamidreza |
BookMark | eNp9kk1v1DAQhiNURD_gD3CyxKUcAuM4H_YJVRWlKxVVQuVs-WOS9SqxFzup2N_FH6y3WyHaAyePZt738Xg8p8WRDx6L4j2FT5Ty9nOiFed1CRUroaWUlexVcULrjpYVE-zon_i4OE1pA0A73sCb4pjxHLJWnBR_7tZIdg5HS0JPUMVxV24jDl55syPrMGFIs0ou7ctTsDgSlRKmNKGfSel8WkbnScQsmbMHyfn17feLcvXjI-lDJJllnZmdH8iAWTG74NVIrFMaZ0xkwnF085JIhljX9xj3XB3sjkz5opy2-Jsob4kakAwxLNv0tnjdqzHhu6fzrPh59fXu8rq8uf22ury4KU1T07m0tAVb086A6ZAZENALaipkumFcK9FBXdmO9Qb6SlhogOsGqFGiVrTSoNhZsTpwbVAbuY1uUnEng3LyMRHiIFWcnRlRGt6KxgoBoHQNWmvVUt32jdC87ZpeZ9aXA2u76Amtya-ManwGfV7xbi2HcC8ptJxRgEw4fyLE8GvJs5STSyaPT3kMS5IVF03VCCZEln54Id2EJea5Z5WAitK26faq6qAyMaQUsf_bDQW5XzB5WDCZF0w-Lphk2cRfmIw7_Gru2o3_sz4AdZXY9w |
CitedBy_id | crossref_primary_10_31612_2616_4868_7_2024_04 crossref_primary_10_1007_s12020_024_04045_2 |
Cites_doi | 10.52547/pcnm.13.1.35 10.1007/s13340-020-00425-x 10.1016/S0020-7292(15)30007-2 10.1155/2019/7578403 10.3390/jpm13010060 10.1111/dme.13857 10.3109/14767058.2011.587921 10.1530/EJE-12-0452 10.1007/s00125-020-05185-6 10.1136/bmjdrc-2020-001728 10.1038/s41574-021-00512-2 10.2337/dbi20-0004 10.1080/09513590801948416 10.1007/s40618-015-0427-z 10.1177/20503121221109911 10.1016/j.jcte.2020.100226 10.1016/j.diabres.2019.107843 10.25048/tudod.1198697 10.4239/wjd.v1.i2.36 10.2337/dc12-1801 10.3390/ijms19113342 10.2337/db18-1151 10.1016/j.tjog.2016.04.032 10.2337/diacare.29.04.06.dc05-2568 10.1016/S2213-8587(20)30161-3 10.4103/shb.shb_127_22 10.1186/s12884-020-2740-6 10.2337/dc15-2672 10.2337/dc16-1732 10.3389/fendo.2014.00138 10.1186/s13098-020-0523-x 10.1111/aogs.13271 10.2337/dc15-S015 10.1186/s12884-022-04672-5 10.1016/j.diabres.2020.108044 10.1007/s40292-022-00542-5 10.1016/j.diabet.2022.101330 |
ContentType | Journal Article |
Copyright | 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2023. The Author(s). The Author(s) 2023 |
Copyright_xml | – notice: 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2023. The Author(s). – notice: The Author(s) 2023 |
DBID | AAYXX CITATION 3V. 7RV 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR CCPQU DWQXO FYUFA GHDGH K9- K9. KB0 M0R M0S M1P NAPCQ PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI 7X8 5PM DOA |
DOI | 10.1186/s12884-023-06113-3 |
DatabaseName | CrossRef ProQuest Central (Corporate) Nursing & Allied Health Database Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central ProQuest One Community College ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) Consumer Health Database ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Database (Alumni Edition) Consumer Health Database ProQuest Health & Medical Collection Medical Database Nursing & Allied Health Premium ProQuest Central Premium ProQuest One Academic Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
DatabaseTitle | CrossRef Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Family Health (Alumni Edition) ProQuest Central Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Family Health ProQuest One Academic Eastern Edition ProQuest Nursing & Allied Health Source ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest Nursing & Allied Health Source (Alumni) ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | Publicly Available Content Database MEDLINE - Academic |
Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 1471-2393 |
EndPage | 9 |
ExternalDocumentID | oai_doaj_org_article_c8695d9900ab40bbba61b6f59b8675fb PMC10683100 10_1186_s12884_023_06113_3 |
GrantInformation_xml | – fundername: ; grantid: IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266; IR.QUMS.REC.1399.266 |
GroupedDBID | --- 0R~ 23N 2WC 53G 5GY 5VS 6J9 6PF 7RV 7X7 88E 8FI 8FJ AAFWJ AAJSJ AASML AAWTL AAYXX ABDBF ABUWG ACGFO ACGFS ACUHS ADBBV ADRAZ ADUKV AENEX AFKRA AFPKN AHBYD AHMBA AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS AZQEC BAPOH BAWUL BCNDV BENPR BFQNJ BKNYI BMC BPHCQ BVXVI C6C CCPQU CITATION CS3 DIK DU5 E3Z EBD EBLON EBS ESX F5P FYUFA GROUPED_DOAJ GX1 HMCUK IAO ICW IHR INH INR ITC K9- KQ8 M0R M1P M48 M~E N8Y NAPCQ O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PQQKQ PROAC PSQYO RBZ RNS ROL RPM RSV SMD SOJ TR2 TUS UKHRP W2D WOQ WOW XSB ~8M 3V. 7XB 8FK DWQXO K9. PJZUB PKEHL PPXIY PQEST PQUKI 7X8 5PM PUEGO |
ID | FETCH-LOGICAL-c541t-d160d417c0c7e3c090f91c2e3b538ba97042d73fc0f29d0508b501ca94a12b0a3 |
IEDL.DBID | M48 |
ISSN | 1471-2393 |
IngestDate | Wed Aug 27 01:32:18 EDT 2025 Thu Aug 21 18:36:01 EDT 2025 Fri Jul 11 03:50:41 EDT 2025 Fri Jul 25 23:41:42 EDT 2025 Thu Apr 24 23:11:51 EDT 2025 Tue Jul 01 03:59:02 EDT 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Language | English |
License | Open Access This 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/. The Creative Commons Public Domain Dedication waiver (http://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. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c541t-d160d417c0c7e3c090f91c2e3b538ba97042d73fc0f29d0508b501ca94a12b0a3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ORCID | 0000-0001-6786-0126 |
OpenAccessLink | http://journals.scholarsportal.info/openUrl.xqy?doi=10.1186/s12884-023-06113-3 |
PMID | 38017369 |
PQID | 2902116579 |
PQPubID | 44759 |
PageCount | 9 |
ParticipantIDs | doaj_primary_oai_doaj_org_article_c8695d9900ab40bbba61b6f59b8675fb pubmedcentral_primary_oai_pubmedcentral_nih_gov_10683100 proquest_miscellaneous_2895259399 proquest_journals_2902116579 crossref_primary_10_1186_s12884_023_06113_3 crossref_citationtrail_10_1186_s12884_023_06113_3 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2023-11-28 |
PublicationDateYYYYMMDD | 2023-11-28 |
PublicationDate_xml | – month: 11 year: 2023 text: 2023-11-28 day: 28 |
PublicationDecade | 2020 |
PublicationPlace | London |
PublicationPlace_xml | – name: London |
PublicationTitle | BMC pregnancy and childbirth |
PublicationYear | 2023 |
Publisher | BioMed Central BMC |
Publisher_xml | – name: BioMed Central – name: BMC |
References | H - Alptekin (6113_CR21) 2016; 39 S -Bellary (6113_CR35) 2021; 17 S - Hashemipour (6113_CR38) 2022; 5 CA - Cheney (6113_CR32) 1985; 65 M - Fakhrul-Alam (6113_CR11) 2020; 20 6113_CR16 A - Jiwani (6113_CR2) 2012; 25 Y - Li (6113_CR14) 2020; 162 TT - Lao (6113_CR27) 2006; 29 FA - Rahnemaei (6113_CR28) 2022; 10 6113_CR30 MS - Kirkman (6113_CR34) 2012; 35 C - Aguayo-Mazzucato (6113_CR18) 2020; 63 P - Kumru (6113_CR22) 2016; 55 MA - Mehari (6113_CR13) 2020; 20 Y - Duo (6113_CR26) 2022; 13 V De Tata (6113_CR37) 2014; 5 P - Saravanan (6113_CR3) 2020; 8 JF - Plows (6113_CR4) 2018; 19 H - Aydın (6113_CR9) 2019; 36 JG - González-González (6113_CR19) 2022; 29 PG -Lee (6113_CR36) 2017; 40 B - Singh (6113_CR24) 2010; 1 J - Shou (6113_CR17) 2020; 12 CE - Powe (6113_CR7) 2020; 69 EE - Ozcimen (6113_CR20) 2008; 24 GO - Skajaa (6113_CR6) 2020; 8 H - Zhu (6113_CR5) 2019; 68 6113_CR25 E - Cosson (6113_CR29) 2022; 48 MK - Laine (6113_CR15) 2018; 97 S - Inoue (6113_CR33) 2020; 11 M - Hod (6113_CR1) 2015; 131 S - Zhang (6113_CR8) 2022; 22 S - Furukawa (6113_CR10) 2019; 2019 American Diabetes Association (6113_CR23) 2015; 38 CE - Powe (6113_CR31) 2016; 39 K - Mørkrid (6113_CR12) 2012; 167 |
References_xml | – ident: 6113_CR25 doi: 10.52547/pcnm.13.1.35 – volume: 11 start-page: 269 year: 2020 ident: 6113_CR33 publication-title: Diabetol Int doi: 10.1007/s13340-020-00425-x – volume: 131 start-page: 173 year: 2015 ident: 6113_CR1 publication-title: Int J Gynecol Obstet doi: 10.1016/S0020-7292(15)30007-2 – volume: 2019 start-page: 7578403 year: 2019 ident: 6113_CR10 publication-title: J Pregnancy doi: 10.1155/2019/7578403 – volume: 13 start-page: 60 issue: 1 year: 2022 ident: 6113_CR26 publication-title: J Personalized Med doi: 10.3390/jpm13010060 – volume: 36 start-page: 221 issue: 2 year: 2019 ident: 6113_CR9 publication-title: Diabet Med doi: 10.1111/dme.13857 – volume: 25 start-page: 600 issue: 6 year: 2012 ident: 6113_CR2 publication-title: J Matern Fetal Neonatal Med doi: 10.3109/14767058.2011.587921 – volume: 167 start-page: 579 issue: 4 year: 2012 ident: 6113_CR12 publication-title: Eur J Endocrinol doi: 10.1530/EJE-12-0452 – volume: 63 start-page: 2022 issue: 10 year: 2020 ident: 6113_CR18 publication-title: Diabetologia doi: 10.1007/s00125-020-05185-6 – volume: 8 start-page: e001728 issue: 2 year: 2020 ident: 6113_CR6 publication-title: BMJ Open Diabetes Research and Care doi: 10.1136/bmjdrc-2020-001728 – volume: 17 start-page: 534 issue: 9 year: 2021 ident: 6113_CR35 publication-title: Nat Reviews Endocrinol doi: 10.1038/s41574-021-00512-2 – volume: 69 start-page: 2064 issue: 10 year: 2020 ident: 6113_CR7 publication-title: Diabetes doi: 10.2337/dbi20-0004 – volume: 24 start-page: 224 issue: 4 year: 2008 ident: 6113_CR20 publication-title: Gynecol Endocrinol doi: 10.1080/09513590801948416 – volume: 39 start-page: 577 year: 2016 ident: 6113_CR21 publication-title: J Endocrinol Investig doi: 10.1007/s40618-015-0427-z – volume: 10 start-page: 205031212211099 year: 2022 ident: 6113_CR28 publication-title: SAGE Open Medicine doi: 10.1177/20503121221109911 – volume: 20 start-page: 100226 year: 2020 ident: 6113_CR11 publication-title: J Clin Transl Endocrinol doi: 10.1016/j.jcte.2020.100226 – ident: 6113_CR16 doi: 10.1016/j.diabres.2019.107843 – ident: 6113_CR30 doi: 10.25048/tudod.1198697 – volume: 1 start-page: 36 issue: 2 year: 2010 ident: 6113_CR24 publication-title: World J Diabetes doi: 10.4239/wjd.v1.i2.36 – volume: 35 start-page: 2650 issue: 12 year: 2012 ident: 6113_CR34 publication-title: Diabetes Care doi: 10.2337/dc12-1801 – volume: 19 start-page: 3342 issue: 11 year: 2018 ident: 6113_CR4 publication-title: Int J Mol Sci doi: 10.3390/ijms19113342 – volume: 68 start-page: 696 issue: 4 year: 2019 ident: 6113_CR5 publication-title: Diabetes doi: 10.2337/db18-1151 – volume: 55 start-page: 815 issue: 6 year: 2016 ident: 6113_CR22 publication-title: Taiwan J Obstet Gynecol doi: 10.1016/j.tjog.2016.04.032 – volume: 29 start-page: 948 issue: 4 year: 2006 ident: 6113_CR27 publication-title: Diabetes Care doi: 10.2337/diacare.29.04.06.dc05-2568 – volume: 8 start-page: 793 issue: 9 year: 2020 ident: 6113_CR3 publication-title: The Lancet Diabetes & Endocrinology doi: 10.1016/S2213-8587(20)30161-3 – volume: 5 start-page: 180 issue: 4 year: 2022 ident: 6113_CR38 publication-title: Asian J Social Health Behav doi: 10.4103/shb.shb_127_22 – volume: 65 start-page: 17 issue: 1 year: 1985 ident: 6113_CR32 publication-title: Obstet Gynecol – volume: 20 start-page: 60 issue: 1 year: 2020 ident: 6113_CR13 publication-title: BMC Pregnancy Childbirth doi: 10.1186/s12884-020-2740-6 – volume: 39 start-page: 1052 issue: 6 year: 2016 ident: 6113_CR31 publication-title: Diabetes Care doi: 10.2337/dc15-2672 – volume: 40 start-page: 444 issue: 4 year: 2017 ident: 6113_CR36 publication-title: Diabetes Care doi: 10.2337/dc16-1732 – volume: 5 start-page: 138 year: 2014 ident: 6113_CR37 publication-title: Front Endocrinol doi: 10.3389/fendo.2014.00138 – volume: 12 start-page: 14 year: 2020 ident: 6113_CR17 publication-title: Diabetol Metab Syndr doi: 10.1186/s13098-020-0523-x – volume: 97 start-page: 187 issue: 2 year: 2018 ident: 6113_CR15 publication-title: Acta Obstet Gynecol Scand doi: 10.1111/aogs.13271 – volume: 38 start-page: 1 year: 2015 ident: 6113_CR23 publication-title: Diabetes Care doi: 10.2337/dc15-S015 – volume: 22 start-page: 336 issue: 1 year: 2022 ident: 6113_CR8 publication-title: BMC Pregnancy Childbirth doi: 10.1186/s12884-022-04672-5 – volume: 162 start-page: 108044 year: 2020 ident: 6113_CR14 publication-title: Diabetes Res Clin Pract doi: 10.1016/j.diabres.2020.108044 – volume: 29 start-page: 547 issue: 6 year: 2022 ident: 6113_CR19 publication-title: High Blood Pressure & Cardiovascular Prevention doi: 10.1007/s40292-022-00542-5 – volume: 48 start-page: 101330 issue: 3 year: 2022 ident: 6113_CR29 publication-title: Diabetes Metab doi: 10.1016/j.diabet.2022.101330 |
SSID | ssj0017850 |
Score | 2.3795764 |
Snippet | BackgroundEarly prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to... Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate... Abstract Background Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study... |
SourceID | doaj pubmedcentral proquest crossref |
SourceType | Open Website Open Access Repository Aggregation Database Enrichment Source Index Database |
StartPage | 1 |
SubjectTerms | Advanced maternal age Age groups Aging Body mass index Chronic illnesses Gestational diabetes Gestational Diabetes Mellitus Glucose HOMA-IR Homeostasis Insulin resistance Metabolism Pathogenesis Pregnancy Regression analysis Sample size Statistical analysis Womens health |
SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Jb9QwFLZQD4gLYhWhLXpIHEDIqp04sX0siGpAGpAQlXqLvLaVmKRqMof5XfzBPmcZNRe4cMkhdhwnb_H3vHyPkHc66JRwO1Jhck2Fx4s1MlDNhKuU5nGczFl_r1bn4ttFeXEv1VfaEzbSA48_7sSpSpcefSYzVjBrram4rWKprUKsG23yvjjmzcHUtH4gVcnmIzKqOunQCytBcXxKmQx4QYvFMDSw9S8g5nKD5L0R5-wJeTxBRTgdu_iUPAjNM_JwPS2GPyd_UMSwSzvQoI0QElMxvbkNl4lCYwdX7Sa0CP266y4VDxlvwOx5OIFOu9AB4-2EIVH48H71Y31Kv_78AAhlAdvy6cBIcwlpEWqaNYR5thY2icuz33aAjcx5Vnqwrd_BBl8EAxEjmMYD-iwYjo90L8j52Zdfn1d0ysFAXSl4Tz2vmBdcOuZkKBzTLGru8lBY9JTWaIlG72URHYu59gzhni0Zd0YLw3PLTPGSHDRtE14R8FEKEQsX0W8IlxttrEQ4VhnpAvMuZoTPIqndRFCe8mT8rodARVX1KMYaxVgPYqyLjHzcP3Mz0nP8tfanJOl9zUStPdxAhasnhav_pXAZOZr1pJ7svatzjViJV6XUGXm7L0ZLTcsvpgntFusoXWKwiYgwI2qhX4sOLUua66uB8xsj95QSjr3-H59wSB7lyRY4p7k6Igf97TYcI7bq7ZvBjO4AjTYlIA priority: 102 providerName: Directory of Open Access Journals – databaseName: Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Ji9RAFC50BPEirhgd5QkeFCmmKqksdZJRHFqhFcSBvoVaewbspO10H_p3-Qd9L5205jKXHFKVBd7-qur7GHujgybC7ciVSTVXHi_WlIFroVxRaRkPzZz5t2J2qb4u8sXQcOuGbZWjT-wdtW8d9cjPUo3RSBZ5qT-sf3NijaLV1YFC4za7Q9BlpNXl4lhwEfG8GA_KVMVZh764UhyjFPEZyIxnk2DUY_ZPEs3pNsn_4s7FA3Z_SBjh_CDhh-xWaB6xu_NhSfwx-4OChj3tQ4M2QiC8Yr7ehCUBaezhql2FFhPA7rqj4Z73BswRjRP4sBcdsOqmTBJVAN7Ovs_P-Zcf7wATWsB3eTo20iyBlqKG3iGMPVtYEaLndtcBvmRkW9mCbf0eVvgh6OEYwTQe0HNBf4ike8IuLz7__DTjAxMDd7mSW-5lIbySpROuDJkTWkQtXRoyi_7SGl2i6fsyi07EVHuBSZ_NhXRGKyNTK0z2lJ00bROeMfCxVCpmLqL3UC412tgSk7LClC4I72LC5CiS2g0w5cSW8avuy5WqqA9irFGMdS_GOkvY--Mz6wNIx42zP5KkjzMJYLu_0W6W9WCvtasKnXsM1cJYJay1ppC2iLm2FZZY0SbsdNSTerD6rv6nowl7fRxGe6VFGNOEdodzKp1jyYl5YcKqiX5Nfmg60lxf9cjfWL8TMZx4fvPXX7B7KWm5lDytTtnJdrMLLzF32tpXvYH8Bb1QHBw priority: 102 providerName: ProQuest |
Title | The yield of early-pregnancy homeostasis of model assessment -insulin resistance (HOMA-IR) for predicting gestational diabetes mellitus in different body mass index and age groups |
URI | https://www.proquest.com/docview/2902116579 https://www.proquest.com/docview/2895259399 https://pubmed.ncbi.nlm.nih.gov/PMC10683100 https://doaj.org/article/c8695d9900ab40bbba61b6f59b8675fb |
Volume | 23 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3bitNAGB72AOKNeMSuaxnBC0VGZ5JJJnMhspVdVqGrFAvFmzDH7sI2WZsW7HP5gv4zTaqBRfAmF5npJM1_nsP3IfRSOhkItz3hKpGEW7hoJRyRlJu8kMxvJ3PGF_n5lH-eZbM91NEdtR-wubW0C3xS0-X1258_Nh_A4N9Hgy_ydw342IITiD6Bp4ClJN1HhxCZRGA0GPM_qwqiiIytDBwyCdBf3SGaW8foBaqI599LQvtbKP-KSWf30b02mcQnW-k_QHuueojujNvl8kfoFygB3oQ9arj22AUsY3KzdPMAsrHBl_XC1ZAcNldNaI6cOFjtkDoxafepY6jIQ5YJ6oFfnX8Zn5BPk9cYkl0MY9lwpKSa47BM1c4r4m4-Fy8C2udq3WAYpGNiWWFd2w1ewINwhGrEqrIYvBqOB0yax2h6dvrt4zlpWRqIyThbEctyauFjG2qESw2V1EtmEpdq8KVaSQFuwYrUG-oTaSkkhDqjzCjJFUs0VekTdFDVlXuKsPWCc58aD56Fm0RJpQUkbLkSxlFr_ACxTiSlaSHMA5PGdRlLmSIvt2IsQYxlFGOZDtCb3W9utgAe_-w9CpLe9Qzg2_FGvZyXrS2XpshlZiGMU6U51VqrnOncZ1IXUH55PUDHnZ6UnUKXiYRsiuWZkAP0YtcMthwWaFTl6jX0KWQG5SjkjANU9PSr90L9lurqMqKCQ20fSOPo0X_94WfobhKUnoFFFMfoYLVcu-eQZq30EO2LmRiiw9HpxdfJME5WDKM9wXUy-v4bOpkpZw |
linkProvider | Scholars Portal |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF6VIgEXxFMECgwSSCC06q69fuwBofKoEtoUCbVSbmafaSVihzgRyp_iwh9k1rEDvvTWiw_ezTrSzM58s4_vI-SldDIIbnsqVCSpsPjQKnNUMmHSXHK_WcwZn6TDM_Flkkx2yO_uLkw4VtnFxCZQ28qENfL9SGI24mmSyffznzSoRoXd1U5CY-MWR279C0u2-t3oE9r3VRQdfj79OKStqgA1ieBLannKrOCZYSZzsWGSeclN5GKNc18rmaEb2yz2hvlIWoYARieMGyWF4pFmKsZxr5HrmHhZKPayybbAC0L3rLuYk6f7Ncb-XFDMikE_gcc07iW_RiOgB2z7xzL_y3OHd8jtFqDCwcaj7pIdV94jN8btFvx98gcdC9bh3BtUHlzgR6bzhZsG4o41nFczVyHgrC_q0Nzo7IDasn8Cbc--A1b5Abmiy8Hr4dfxAR19ewMIoAHHsuGaSjmFsPXVrlVCt0YMs8AgulzVgIN06i5L0JVdwww_BA39I6jSAkZKaC6t1A_I2ZXY6CHZLavSPSJgfSaEj43HaCVMpKTSGYLAVGXGMWv8gPDOJIVpadGDOsePoimP8rTYmLFAMxaNGYt4QN5ufzPfkIJc2vtDsPS2ZyD0bl5Ui2nRxofC5KlMLEIDprRgWmuVcp36ROocSzqvB2Sv85OijTJ18W9ODMiLbTPGh7Dpo0pXrbBPLhMscRGHDkje86_eH-q3lBfnDdM4Z2kQomOPL__6c3JzeDo-Lo5HJ0dPyK0oeDznNMr3yO5ysXJPEbct9bNmsgD5ftWz8y_awVgH |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+yield+of+early-pregnancy+homeostasis+of+model+assessment+-insulin+resistance+%28HOMA-IR%29+for+predicting+gestational+diabetes+mellitus+in+different+body+mass+index+and+age+groups&rft.jtitle=BMC+pregnancy+and+childbirth&rft.au=Hashemipour%2C+Sima&rft.au=Zohal%2C+Mahnaz&rft.au=Modarresnia%2C+Leila&rft.au=Kolaji%2C+Sepideh&rft.date=2023-11-28&rft.issn=1471-2393&rft.eissn=1471-2393&rft.volume=23&rft.issue=1&rft_id=info:doi/10.1186%2Fs12884-023-06113-3&rft.externalDBID=n%2Fa&rft.externalDocID=10_1186_s12884_023_06113_3 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1471-2393&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1471-2393&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1471-2393&client=summon |