Early postpartum dyslipidemia and its potential predictors during pregnancy in women with a history of gestational diabetes mellitus

Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). Methods This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up a...

Full description

Saved in:
Bibliographic Details
Published inLipids in health and disease Vol. 19; no. 1; pp. 1 - 8
Main Authors Pei, Ling, Xiao, Huangmeng, Lai, Fenghua, Li, Zeting, Li, Zhuyu, Yue, Shufan, Chen, Haitian, Li, Yanbing, Cao, Xiaopei
Format Journal Article
LanguageEnglish
Published London BioMed Central Ltd 10.10.2020
BioMed Central
BMC
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). Methods This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6-12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values. Results A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733. Conclusions A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy. Keywords: Gestational diabetes mellitus, Predictor, Lipid, postpartum, Cardiovascular disease
AbstractList Abstract Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). Methods This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6–12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values. Results A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733. Conclusions A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy.
Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). Methods This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6-12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values. Results A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733. Conclusions A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy. Keywords: Gestational diabetes mellitus, Predictor, Lipid, postpartum, Cardiovascular disease
This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM).BACKGROUNDThis study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM).This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6-12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values.METHODSThis was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6-12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values.A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733.RESULTSA total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733.A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy.CONCLUSIONSA lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy.
This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6-12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values. A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733. A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy.
Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes mellitus (GDM). Methods This was a retrospective study. Five hundred eighty-nine women diagnosed with GDM were enrolled and followed up at 6–12 weeks after delivery. A 75 g oral glucose tolerance test (OGTT) and lipid levels were performed during mid-trimester and the early postpartum period. Participants were divided into the normal lipid group and dyslipidemia group according to postpartum lipid levels. Demographic and metabolic parameters were analyzed. Multiple logistic regression was performed to analyze the potential predictors for early postpartum dyslipidemia. A receiver operating characteristic curve (ROC) was calculated to determine the cut-off values. Results A total of 38.5% of the 589 women developed dyslipidemia in early postpartum and 60% of them had normal glucose metabolism. Delivery age, systolic blood pressure (SBP), glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) were independent predictors of early postpartum dyslipidemia in women with a history of GDM. The cut-offs of maternal age, SBP, HbA1c values, and LDL-C levels were 35 years, 123 mmHg, 5.1%, and 3.56 mmol/L, respectively. LDL-C achieved a balanced mix of high sensitivity (63.9%) and specificity (69.2%), with the highest area under the receiver operating characteristic curve (AUC) (0.696). When LDL-C was combined with age, SBP, and HbA1c, the AUC reached to 0.733. Conclusions A lipid metabolism evaluation should be recommended in women with a history of GDM after delivery, particularly those with a maternal age > 35 years, SBP > 123 mmHg before labor, HbA1c value > 5.1%, or LDL-C levels > 3.56 mmol/L in the second trimester of pregnancy.
ArticleNumber 220
Audience Academic
Author Yue, Shufan
Cao, Xiaopei
Li, Zeting
Pei, Ling
Li, Zhuyu
Chen, Haitian
Xiao, Huangmeng
Lai, Fenghua
Li, Yanbing
Author_xml – sequence: 1
  givenname: Ling
  surname: Pei
  fullname: Pei, Ling
– sequence: 2
  givenname: Huangmeng
  surname: Xiao
  fullname: Xiao, Huangmeng
– sequence: 3
  givenname: Fenghua
  surname: Lai
  fullname: Lai, Fenghua
– sequence: 4
  givenname: Zeting
  surname: Li
  fullname: Li, Zeting
– sequence: 5
  givenname: Zhuyu
  surname: Li
  fullname: Li, Zhuyu
– sequence: 6
  givenname: Shufan
  surname: Yue
  fullname: Yue, Shufan
– sequence: 7
  givenname: Haitian
  surname: Chen
  fullname: Chen, Haitian
– sequence: 8
  givenname: Yanbing
  surname: Li
  fullname: Li, Yanbing
– sequence: 9
  givenname: Xiaopei
  surname: Cao
  fullname: Cao, Xiaopei
BookMark eNp9ks-L1DAcxYusuLuj_4CngBcvXfOraXIRlmXVhQUvCt5CmqSdDG1Sk9Rl7v7hpjMrOotIIS3fvPcpeXmX1ZkP3lbVawSvEOLsXUJYUFpDDGuIiOA1elZdINqyukHo29lf3-fVZUo7WJQtYy-qc0IgYQzRi-rnrYrjHswh5VnFvEzA7NPoZmfs5BRQ3gCXU9nP1menRjBHa5zOISZgluj8sE4Gr7zeA-fBQ5hsWV3eAgW2LhXhHoQeDDZllV3wBWGc6my2CUx2HF1e0svqea_GZF89vjfV1w-3X24-1fefP97dXN_XuqEw10Rh3nKiYN_23GihEWYd4h3mDbGsxdiwDkIougbhnmtNsYXEdB1kSFikDNlUd0euCWon5-gmFfcyKCcPgxAHWTJwerRStIJQShpimKHYKEF1IfTYCt2K7sB6f2TNSzdZo0s8UY0n0NMd77ZyCD9k29C2gU0BvH0ExPB9KfHIySVdElHehiVJTKkQDYdilb55It2FJZYoV1WDBMGYwj-qQZUDON-H8l-9QuU1I5wyRot0U139Q1We9cJ1KVjvyvzEwI8GHUNK0fZSu-NVFqMbJYJybaM8tlGWjslDGyUqVvzE-jue_5h-AQL_5KU
CitedBy_id crossref_primary_10_1097_HJH_0000000000003664
crossref_primary_10_1007_s11883_022_01026_6
crossref_primary_10_1186_s12884_023_06167_3
crossref_primary_10_1007_s11883_022_01030_w
crossref_primary_10_1007_s13300_023_01387_4
crossref_primary_10_1038_s41598_025_92299_9
crossref_primary_10_1113_JP285943
crossref_primary_10_1093_ehjopen_oeae032
crossref_primary_10_1007_s11892_024_01552_4
crossref_primary_10_1161_HYPERTENSIONAHA_124_22919
crossref_primary_10_3389_fendo_2022_840331
crossref_primary_10_1016_j_obmed_2022_100446
crossref_primary_10_1016_j_xagr_2023_100214
crossref_primary_10_3390_nu17030387
Cites_doi 10.2337/dc08-0706
10.1007/s00592-017-1099-2
10.1016/j.plefa.2016.10.001
10.1136/bmjdrc-2017-000445
10.1161/CIRCULATIONAHA.115.008728
10.1016/j.diabres.2013.10.012
10.1001/jama.285.19.2486
10.1016/j.cjca.2016.07.510
10.3390/nu10070839
10.1161/CIRCULATIONAHA.115.015293
10.1016/j.placenta.2018.05.011
10.1136/heartjnl-2013-303945
10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S
10.1038/s41572-019-0098-8
10.1007/s00125-019-4840-2
10.1093/eurheartj/ehw106
10.7326/0003-4819-150-4-200902170-00005
10.1111/jdi.12854
10.1016/j.plefa.2020.102098
10.1111/obr.12645
10.1016/j.jogc.2019.03.008
10.1002/lipd.12040
10.1210/jc.2010-0361
10.1136/bmjdrc-2019-000870
10.1016/j.diabres.2015.10.004
10.1016/j.jacl.2019.10.002
10.1016/j.atherosclerosis.2019.08.014
10.1016/S0140-6736(12)62027-3
10.1161/HYPERTENSIONAHA.114.04850
10.1016/j.yjmcc.2012.08.023
10.1371/journal.pone.0087863
10.1038/ejcn.2016.171
10.1016/S0140-6736(09)60731-5
10.1186/s12889-019-7827-5
10.1161/CIRCULATIONAHA.115.018352
10.1080/09513590.2018.1512094
10.1097/MOL.0b013e328304b670
10.1136/bmjdrc-2016-000250
10.1210/en.2009-0252
10.1111/jdi.13039
10.2337/db15-1383
10.1007/s11845-016-1474-y
ContentType Journal Article
Copyright COPYRIGHT 2020 BioMed Central Ltd.
2020. 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.
The Author(s) 2020
Copyright_xml – notice: COPYRIGHT 2020 BioMed Central Ltd.
– notice: 2020. 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: The Author(s) 2020
DBID AAYXX
CITATION
3V.
7X7
7XB
88E
8FD
8FE
8FH
8FI
8FJ
8FK
ABUWG
AFKRA
AZQEC
BBNVY
BENPR
BHPHI
CCPQU
DWQXO
FR3
FYUFA
GHDGH
GNUQQ
HCIFZ
K9.
LK8
M0S
M1P
M7P
P64
PHGZM
PHGZT
PIMPY
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
RC3
7X8
5PM
DOA
DOI 10.1186/s12944-020-01398-1
DatabaseName CrossRef
ProQuest Central (Corporate)
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
Technology Research Database
ProQuest SciTech Collection
ProQuest Natural Science Collection
ProQuest Hospital Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
Biological Science Collection
ProQuest Central
Natural Science Collection
ProQuest One Community College
ProQuest Central Korea
Engineering Research Database
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
Biological Sciences
ProQuest Health & Medical Collection
PML(ProQuest Medical Library)
Biological Science Database
Biotechnology and BioEngineering Abstracts
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 Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
Genetics Abstracts
MEDLINE - Academic
PubMed Central (Full Participant titles)
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
ProQuest Central Student
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Natural Science Collection
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Health & Medical Research Collection
Genetics Abstracts
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
Natural Science Collection
ProQuest Central Korea
Health & Medical Research Collection
Biological Science Collection
ProQuest Central (New)
ProQuest Medical Library (Alumni)
ProQuest Biological Science Collection
ProQuest One Academic Eastern Edition
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
Biological Science Database
ProQuest SciTech Collection
ProQuest Hospital Collection (Alumni)
Biotechnology and BioEngineering Abstracts
ProQuest Health & Medical Complete
ProQuest Medical Library
ProQuest One Academic UKI Edition
Engineering Research Database
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList

MEDLINE - Academic

Publicly Available Content Database
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
Anatomy & Physiology
EISSN 1476-511X
EndPage 8
ExternalDocumentID oai_doaj_org_article_979344353d6d42da94c1adf2e9c79bad
PMC7547505
A638466419
10_1186_s12944_020_01398_1
GeographicLocations China
GeographicLocations_xml – name: China
GrantInformation_xml – fundername: ;
  grantid: 2018YFC1314100
– fundername: ;
  grantid: 201803010101
– fundername: ;
  grantid: 2017001
GroupedDBID ---
0R~
29L
2WC
53G
5GY
5VS
7X7
88E
8FE
8FH
8FI
8FJ
A8Z
AAFWJ
AAHBH
AAJSJ
AASML
AAYXX
ABDBF
ABUWG
ACGFO
ACGFS
ACPRK
ACUHS
ADBBV
ADRAZ
ADUKV
AENEX
AFKRA
AFPKN
AHBYD
AHMBA
AHYZX
ALIPV
ALMA_UNASSIGNED_HOLDINGS
AMKLP
AMTXH
AOIJS
BAPOH
BAWUL
BBNVY
BCNDV
BENPR
BFQNJ
BHPHI
BMC
BPHCQ
BVXVI
C6C
CCPQU
CITATION
CS3
DIK
E3Z
EAD
EAP
EAS
EBD
EBLON
EBS
EMB
EMK
EMOBN
ESX
F5P
FYUFA
GROUPED_DOAJ
GX1
HCIFZ
HH5
HMCUK
HYE
IAO
IGS
IHR
INH
INR
ITC
KQ8
LK8
M1P
M48
M7P
M~E
O5R
O5S
OK1
OVT
P2P
P6G
PGMZT
PHGZM
PHGZT
PIMPY
PQQKQ
PROAC
PSQYO
RBZ
RNS
ROL
RPM
RSV
SBL
SOJ
SV3
TR2
TUS
U2A
UKHRP
W2D
WOQ
WOW
XSB
PMFND
3V.
7XB
8FD
8FK
AZQEC
DWQXO
FR3
GNUQQ
K9.
P64
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQUKI
RC3
7X8
5PM
PUEGO
ID FETCH-LOGICAL-c540t-3a28783a0f7f8dc9c126b18b2853e6722d6b0009b512f8cc42e03dbb0619e1ad3
IEDL.DBID M48
ISSN 1476-511X
IngestDate Wed Aug 27 01:09:25 EDT 2025
Thu Aug 21 18:25:37 EDT 2025
Fri Jul 11 01:50:41 EDT 2025
Fri Jul 25 19:16:19 EDT 2025
Tue Jun 17 21:38:43 EDT 2025
Tue Jun 10 20:30:39 EDT 2025
Thu Apr 24 22:58:56 EDT 2025
Tue Jul 01 00:23:15 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
License 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/. 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-c540t-3a28783a0f7f8dc9c126b18b2853e6722d6b0009b512f8cc42e03dbb0619e1ad3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink https://www.proquest.com/docview/2451932240?pq-origsite=%requestingapplication%
PMID 33036614
PQID 2451932240
PQPubID 42587
PageCount 8
ParticipantIDs doaj_primary_oai_doaj_org_article_979344353d6d42da94c1adf2e9c79bad
pubmedcentral_primary_oai_pubmedcentral_nih_gov_7547505
proquest_miscellaneous_2449958095
proquest_journals_2451932240
gale_infotracmisc_A638466419
gale_infotracacademiconefile_A638466419
crossref_citationtrail_10_1186_s12944_020_01398_1
crossref_primary_10_1186_s12944_020_01398_1
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2020-10-10
PublicationDateYYYYMMDD 2020-10-10
PublicationDate_xml – month: 10
  year: 2020
  text: 2020-10-10
  day: 10
PublicationDecade 2020
PublicationPlace London
PublicationPlace_xml – name: London
PublicationTitle Lipids in health and disease
PublicationYear 2020
Publisher BioMed Central Ltd
BioMed Central
BMC
Publisher_xml – name: BioMed Central Ltd
– name: BioMed Central
– name: BMC
References R Kessous (1398_CR17) 2013; 99
JA Bernstein (1398_CR31) 2017; 5
G Chodick (1398_CR14) 2020; 8
B Yan (1398_CR6) 2019; 10
AC O'Higgins (1398_CR13) 2017; 186
R Retnakaran (1398_CR15) 2010; 95
MJ Pletcher (1398_CR27) 2009; 150
F Mach (1398_CR38) 2019; 290
G López Stewart (1398_CR22) 2014; 103
BR Shah (1398_CR19) 2008; 31
MC DeRuiter (1398_CR43) 2008; 19
A Khaire (1398_CR41) 2020; 157
B Mihaylova (1398_CR28) 2012; 380
S Opoku (1398_CR35) 2019; 19
Y Ma (1398_CR40) 2019; 35
JA Bernstein (1398_CR30) 2016; 4
TJ Anderson (1398_CR37) 2016; 32
C Song (1398_CR11) 2018; 19
KA Wilmot (1398_CR2) 2015; 132
KG Alberti (1398_CR24) 1998; 15
Y Wu (1398_CR1) 2016; 133
C Chee (1398_CR36) 2016; 65
M Dong (1398_CR42) 2013; 55
EG Nabel (1398_CR4) 2015; 132
L Bellamy (1398_CR10) 2009; 373
Y Xu (1398_CR16) 2014; 9
JH Veerbeek (1398_CR33) 2015; 65
HD McIntyre (1398_CR7) 2019; 5
H Berger (1398_CR21) 2019; 41
MF Piepoli (1398_CR29) 2016; 37
A Herrera Martínez (1398_CR26) 2018; 35
F Echeverría (1398_CR45) 2016; 114
C Gao (1398_CR5) 2019; 10
O Ajala (1398_CR12) 2015; 110
CK Kramer (1398_CR20) 2019; 62
C Barrera (1398_CR8) 2018; 10
M Prados (1398_CR25) 2018; 53
S McKenzie-Sampson (1398_CR18) 2018; 55
Expert Panel on Detection E (1398_CR23) 2001; 285
DK Arnett (1398_CR3) 2019; 140
Y Wang (1398_CR9) 2017; 71
F Delhaes (1398_CR44) 2018; 69
S Rütti (1398_CR39) 2009; 150
C Wen (1398_CR32) 2019; 13
JR Zhu (1398_CR34) 2018; 15
References_xml – volume: 31
  start-page: 1668
  year: 2008
  ident: 1398_CR19
  publication-title: Diabetes Care
  doi: 10.2337/dc08-0706
– volume: 55
  start-page: 315
  year: 2018
  ident: 1398_CR18
  publication-title: Acta Diabetol
  doi: 10.1007/s00592-017-1099-2
– volume: 114
  start-page: 28
  year: 2016
  ident: 1398_CR45
  publication-title: Prostaglandins Leukot Essent Fat Acids
  doi: 10.1016/j.plefa.2016.10.001
– volume: 5
  start-page: e000445
  year: 2017
  ident: 1398_CR31
  publication-title: BMJ Open Diabetes Res Care
  doi: 10.1136/bmjdrc-2017-000445
– volume: 133
  start-page: 2545
  year: 2016
  ident: 1398_CR1
  publication-title: Circulation
  doi: 10.1161/CIRCULATIONAHA.115.008728
– volume: 15
  start-page: 1
  year: 2018
  ident: 1398_CR34
  publication-title: J Geriatr Cardiol
– volume: 103
  start-page: 341
  year: 2014
  ident: 1398_CR22
  publication-title: Diabetes Res Clin Pr
  doi: 10.1016/j.diabres.2013.10.012
– volume: 285
  start-page: 2486
  year: 2001
  ident: 1398_CR23
  publication-title: JAMA
  doi: 10.1001/jama.285.19.2486
– volume: 32
  start-page: 1263
  year: 2016
  ident: 1398_CR37
  publication-title: Can J Cardiol
  doi: 10.1016/j.cjca.2016.07.510
– volume: 10
  start-page: 839
  year: 2018
  ident: 1398_CR8
  publication-title: Nutrients.
  doi: 10.3390/nu10070839
– volume: 132
  start-page: 997
  year: 2015
  ident: 1398_CR2
  publication-title: Circulation
  doi: 10.1161/CIRCULATIONAHA.115.015293
– volume: 69
  start-page: 118
  year: 2018
  ident: 1398_CR44
  publication-title: Placenta.
  doi: 10.1016/j.placenta.2018.05.011
– volume: 99
  start-page: 1118
  year: 2013
  ident: 1398_CR17
  publication-title: Heart
  doi: 10.1136/heartjnl-2013-303945
– volume: 15
  start-page: 539
  year: 1998
  ident: 1398_CR24
  publication-title: Diabet Med
  doi: 10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S
– volume: 5
  start-page: 47
  year: 2019
  ident: 1398_CR7
  publication-title: Nat Rev Dis Primers
  doi: 10.1038/s41572-019-0098-8
– volume: 62
  start-page: 905
  year: 2019
  ident: 1398_CR20
  publication-title: Diabetologia.
  doi: 10.1007/s00125-019-4840-2
– volume: 37
  start-page: 2315
  year: 2016
  ident: 1398_CR29
  publication-title: Eur Heart J
  doi: 10.1093/eurheartj/ehw106
– volume: 150
  start-page: 243
  year: 2009
  ident: 1398_CR27
  publication-title: Ann Intern Med
  doi: 10.7326/0003-4819-150-4-200902170-00005
– volume: 10
  start-page: 154
  year: 2019
  ident: 1398_CR5
  publication-title: J Diabetes Invest
  doi: 10.1111/jdi.12854
– volume: 157
  start-page: 102098
  year: 2020
  ident: 1398_CR41
  publication-title: Prostaglandins Leukot Essent Fat Acids
  doi: 10.1016/j.plefa.2020.102098
– volume: 19
  start-page: 421
  year: 2018
  ident: 1398_CR11
  publication-title: Obes Rev
  doi: 10.1111/obr.12645
– volume: 41
  start-page: 1814
  year: 2019
  ident: 1398_CR21
  publication-title: J Obstet Gynaecol Can
  doi: 10.1016/j.jogc.2019.03.008
– volume: 53
  start-page: 387
  year: 2018
  ident: 1398_CR25
  publication-title: Lipids.
  doi: 10.1002/lipd.12040
– volume: 95
  start-page: 4345
  year: 2010
  ident: 1398_CR15
  publication-title: J Clin Endocrinol Metab
  doi: 10.1210/jc.2010-0361
– volume: 8
  start-page: e870
  year: 2020
  ident: 1398_CR14
  publication-title: BMJ Open Diabetes Res Care
  doi: 10.1136/bmjdrc-2019-000870
– volume: 35
  start-page: 698
  year: 2018
  ident: 1398_CR26
  publication-title: Nutr Hosp
– volume: 110
  start-page: 309
  year: 2015
  ident: 1398_CR12
  publication-title: Diabetes Res Clin Pr
  doi: 10.1016/j.diabres.2015.10.004
– volume: 13
  start-page: 1008
  year: 2019
  ident: 1398_CR32
  publication-title: J Clin Lipidol
  doi: 10.1016/j.jacl.2019.10.002
– volume: 290
  start-page: 140
  year: 2019
  ident: 1398_CR38
  publication-title: Atherosclerosis
  doi: 10.1016/j.atherosclerosis.2019.08.014
– volume: 380
  start-page: 581
  year: 2012
  ident: 1398_CR28
  publication-title: Lancet.
  doi: 10.1016/S0140-6736(12)62027-3
– volume: 65
  start-page: 600
  year: 2015
  ident: 1398_CR33
  publication-title: Hypertension.
  doi: 10.1161/HYPERTENSIONAHA.114.04850
– volume: 55
  start-page: 111
  year: 2013
  ident: 1398_CR42
  publication-title: J Mol Cell Cardiol
  doi: 10.1016/j.yjmcc.2012.08.023
– volume: 9
  start-page: e87863
  year: 2014
  ident: 1398_CR16
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0087863
– volume: 71
  start-page: 149
  year: 2017
  ident: 1398_CR9
  publication-title: Eur J Clin Nutr
  doi: 10.1038/ejcn.2016.171
– volume: 373
  start-page: 1773
  year: 2009
  ident: 1398_CR10
  publication-title: Lancet
  doi: 10.1016/S0140-6736(09)60731-5
– volume: 19
  start-page: 1500
  year: 2019
  ident: 1398_CR35
  publication-title: BMC Public Health
  doi: 10.1186/s12889-019-7827-5
– volume: 132
  start-page: 989
  year: 2015
  ident: 1398_CR4
  publication-title: Circulation.
  doi: 10.1161/CIRCULATIONAHA.115.018352
– volume: 35
  start-page: 174
  year: 2019
  ident: 1398_CR40
  publication-title: Gynecol Endocrinol
  doi: 10.1080/09513590.2018.1512094
– volume: 19
  start-page: 333
  year: 2008
  ident: 1398_CR43
  publication-title: Curr Opin Lipidol
  doi: 10.1097/MOL.0b013e328304b670
– volume: 140
  start-page: e596
  year: 2019
  ident: 1398_CR3
  publication-title: Circulation.
– volume: 4
  start-page: e000250
  year: 2016
  ident: 1398_CR30
  publication-title: BMJ Open Diabetes Res Care
  doi: 10.1136/bmjdrc-2016-000250
– volume: 150
  start-page: 4521
  year: 2009
  ident: 1398_CR39
  publication-title: Endocrinology.
  doi: 10.1210/en.2009-0252
– volume: 10
  start-page: 1358
  year: 2019
  ident: 1398_CR6
  publication-title: J Diabetes Invest
  doi: 10.1111/jdi.13039
– volume: 65
  start-page: 840
  year: 2016
  ident: 1398_CR36
  publication-title: Diabetes.
  doi: 10.2337/db15-1383
– volume: 186
  start-page: 403
  year: 2017
  ident: 1398_CR13
  publication-title: Irish J Med Sci
  doi: 10.1007/s11845-016-1474-y
SSID ssj0020766
Score 2.3262405
Snippet Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational...
This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of gestational diabetes...
Abstract Background This study aimed to analyze the incidence of early postpartum dyslipidemia and its potential predictors in women with a history of...
SourceID doaj
pubmedcentral
proquest
gale
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Enrichment Source
Index Database
StartPage 1
SubjectTerms Age
Analysis
Blood pressure
Cardiovascular disease
Cholesterol
Diabetes mellitus
Dyslipidemia
Gestational diabetes
Gestational diabetes mellitus
Glucose
Glucose metabolism
Glucose tolerance
Glucose tolerance test
Glycosylated hemoglobin
Hemoglobin
Lipid metabolism
Lipid, postpartum
Lipids
Low density lipoprotein
Low density lipoproteins
Meat
Metabolic disorders
Metabolism
Mortality
Nutrition research
Physiological aspects
Plasma
Postpartum
Predictor
Pregnancy
Pregnant women
Regression analysis
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/eLvHCXMwrV1Nb9QwELVQD4gLoi2IQIuMVMEBRU1sJ7GPW0RVVSonKvVm-RNWYrOrJnvYOz-8M06yakCCC9fYVmLP2POeM34m5AxQvCu8izkPhclF9EWuZCxyFyDWSuAHPGVV3nytr27F9V119-iqL8wJG-SBh4E7V-BAAmI697UXzBslXGl8ZEG5RlnjcfWFmDeRqZFqATuvpyMysj7vIKoJkSNVQsgDvGkWhpJa_59r8u95ko8Cz-UL8nxEjHQxfOkheRLaI3K8aIEtr3b0A005nGlz_Ig8vRl_lR-TX0m6mG7WXb-BXm5X1O8AUw4XwhpqWk-XfQflPeYLwQs299gWL9-hw9lFfPId9Th2dNnSJNVAcduWGjqoFO_oOlL8PzVuKNJpI5euUOaz33Yvye3ll2-fr_LxyoXcAXTrc26AQUluithE6Z1yJattKS2DqB7qhjFfJ1hmASdE6ZxgoeDeWkAFKoBd-Cty0K7b8JpQ3lgZDIx7kEqwaFWsKl7bYBWvfNWojJSTBbQb9cjxWoyfOvESWevBahqsppPVdJmRT_s2m0GN46-1L9Cw-5qopJ0egH_p0b_0v_wrIx_RLTTOd_g8Z8ZjC9BJVM7SC1jAUKK_hA6dzGrCPHXz4smx9LhOdJqJhKABVmXk_b4YW2LuWxvWW6wDrLSSgIUz0swcctazeUm7_JG0wptKACas3vyPoXhLnjGcQpjPU5yQg_5-G04BkvX2XZp9D1pgNfo
  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/eLvHCXMwfV3fi9QwEA56gvgieqdYPSWC6IOUa5u0TZ5kFY9DOJ882LeQXz0X3La37T7su3-4M2l2zyrca5PQzc5k5pvJ9BtC3gGKt5mzTcp8plPeuCyVoslS68HXCogPWKiqvPxeXVzxb8tyGRNuQyyr3NvEYKhdZzFHflbwgDXAAX3qb1LsGoW3q7GFxn3yAKnLUKvr5W3ABTF6tf9QRlRnA_g2zlMMmBD4QPQ0c0aBs_9_y_xvteRf7uf8CXkccSNdTIJ-Su759picLFqImdc7-p6GSs6QIj8mDy_jhfkJ-R0IjGnfDWMPSrJdU7cDZDm1hdVUt46uxgHGR6waghf0G1yLLXjo9AUjPrlGVo4dXbU0EDZQTN5STSeu4h3tGoq3VDGtSPfpXLpGss9xOzwjV-dff3y5SGPjhdQCgBtTpiGOEkxnTd0IZ6XNi8rkwhTg231VF4WrAjgzgBYaYS0vfMacMYANpM-1Y8_JUdu1_gWhrDbCa_jfvZC8aIxsypJVxhvJSlfWMiH5XgLKRlZybI7xS4XoRFRqkpoCqakgNZUn5ONhTT9xctw5-zMK9jAT-bTDg25zreLxVBLMFAfkyFzleOG05Bb20RRe2loa7RLyAdVC4amHn2d1_HgBNon8WWoBZgyJ-nPY0OlsJpxWOx_eK5aK1mJQt7qdkLeHYVyJFXCt77Y4B2LTUgAiTkg9U8jZzuYj7epnYAyvSw7IsHx598tfkUcFHg6s18lOydG42frXALlG8yacqz_YJiza
  priority: 102
  providerName: ProQuest
Title Early postpartum dyslipidemia and its potential predictors during pregnancy in women with a history of gestational diabetes mellitus
URI https://www.proquest.com/docview/2451932240
https://www.proquest.com/docview/2449958095
https://pubmed.ncbi.nlm.nih.gov/PMC7547505
https://doaj.org/article/979344353d6d42da94c1adf2e9c79bad
Volume 19
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3di9QwEA_3AeKL6J3ieucSQfRBqm2aNs2DyJ7ccQh7iLiwbyFfvVu47e7tdsF99w93Jm0Xq4fga5O0TTKT-U0y-Q0hrwHF29jZMkp9rCNeujiSRRlH1oOtLcA_SENU5fgqv5zwL9Nsuke6dEftAK7vde0wn9Rkdfv-x932Eyj8x6DwRf5hDTaL8wgdIQQ04BXtk0OwTAIzGoz57lSBgc_e3DYSeQRAY9pdorn3HT1DFfj8_161_4yk_M00XTwmj1pMSUeNEDwhe746IsejCvzp-Za-oSHKM2yfH5EH4_Yw_Zj8DOTGdLlY10sQoM2cui2gziZlrKa6cnRWr6G8xogi-MByhW0xPQ9tbjfik2tk7NjSWUUDmQPFjV2qacNjvKWLkuIJVrvlSLutXjpHItB6s35KJhfn3z9fRm1ShsgCuKujVIOPVaQ6LkVZOCttwnKTFIaB3fe5YMzlAbgZQBJlYS1nPk6dMYAbpE-0S5-Rg2pR-eeEpsIUXsO4-0JyVhpZZlmaG29kmrlMyAFJuhlQtmUsx8QZtyp4LkWumllTMGsqzJpKBuTdrs2y4ev4Z-0znNhdTeTaDg8Wq2vVqq6SsIRxQJWpyx1nTktuoR8l89IKabQbkLcoFgplFH7P6vZiA3QSubXUCJY4JPFPoEOnvZqgybZf3AmW6hRBMR4wNgCvAXm1K8aWGB1X-cUG64DfmhWAlgdE9ASy17N-STW7CWziIuOAGrMX_zVwJ-QhQ13B0J74lBzUq41_CeisNkOyL6ZiSA7Pzq--fhuGPY5hUMNfbuM5UQ
linkProvider Scholars Portal
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELZKkYALghbEQgEj8TigqInjPHxAaHlUW9rtqZV6M36lrMQmyyYrtHd-D7-RGSfZEpB66zW2N-vMeOb77PEMIS8BxZvQmiKIXagCXtgwEHkRBsaBr82BH8Q-qnJ6kk7O-Jfz5HyL_O7vwmBYZW8TvaG2lcE98n3GPdYAB_R-8SPAqlF4utqX0GjV4sitfwJlq98dfgL5vmLs4PPpx0nQVRUIDKCTJogVkIQ8VmGRFbk1wkQs1VGuGTgul2aM2dQjDw2usMiN4cyFsdUaHJ9wkbIx_O4NchMcb4hkLzu_JHhhlqb9xZw83a_Bl3IeIEFDoAVsbeD8fI2A_z3Bv9GZf7m7g3vkbodT6bhVrPtky5U7ZHdcAkefr-lr6iNH_Zb8Drk17Q7od8kvnzCZLqq6WYBSrubUrgHJtmVoFVWlpbOmhvYGo5TgBYsljsWSP7S9MYlPLjALyJrOSuoTRFDcLKaKtrmR17QqKJ6KdduYtN8-pnNMLtqs6gfk7FpE8pBsl1XpHhEaZzp3Cr67ywVnhRZFksSpdlrEiU0yMSJRLwFpuizoWIzju_RsKE9lKzUJUpNeajIakbebMYs2B8iVvT-gYDc9MX-3f1AtL2RnDqQAs8gBqcY2tZxZJbiBeRTMCZMJreyIvEG1kGhl4O8Z1V2WgElivi45BrOJhQEimNDeoCdYBzNs7hVLdtaplpdraURebJpxJEbcla5aYR_gwkkOCHxEsoFCDmY2bCln33yG8izhgESTx1e__Dm5PTmdHsvjw5OjJ-QOw4WCsULhHtluliv3FOBeo5_5NUbJ1-te1H8AWG1o6w
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=Early+postpartum+dyslipidemia+and+its+potential+predictors+during+pregnancy+in+women+with+a+history+of+gestational+diabetes+mellitus&rft.jtitle=Lipids+in+health+and+disease&rft.au=Pei%2C+Ling&rft.au=Xiao%2C+Huangmeng&rft.au=Lai%2C+Fenghua&rft.au=Li%2C+Zeting&rft.date=2020-10-10&rft.issn=1476-511X&rft.eissn=1476-511X&rft.volume=19&rft.issue=1&rft_id=info:doi/10.1186%2Fs12944-020-01398-1&rft.externalDBID=n%2Fa&rft.externalDocID=10_1186_s12944_020_01398_1
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1476-511X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1476-511X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1476-511X&client=summon