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Xu X, Luo S, Lin J, Zhou J, Zheng L, Yang L, Zhang Z, Dong Y, Ma M, Li H, Lin S, Xie X, Luo J, Wu S. Association between maternal lipid profiles and lipid ratios in early to middle pregnancy as well as their dynamic changes and gestational diabetes mellitus. BMC Pregnancy Childbirth 2024; 24:510. [PMID: 39075387 PMCID: PMC11285337 DOI: 10.1186/s12884-024-06692-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 07/10/2024] [Indexed: 07/31/2024] Open
Abstract
BACKGROUND Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between lipid profiles, lipid ratios and GDM during pregnancy. AIMS To prospectively investigate the relationship between lipid profile and lipid ratios in early and mid-pregnancy and their pattern of change from early to mid-pregnancy and the risk of GDM. METHODS This nested case-control study was based on maternal and child healthcare hospitals from Fujian Province, China. We included pregnant women who delivered in the hospital from January 2021 to June 2023. Lipid profiles (TC, TG, ApoA1, ApoB, HDL-c, LDL-c) and fasting glucose were measured before 14 weeks of gestation and between 20 and 28 weeks of gestation, and lipid ratios (triglyceride glucose index, TG/HDL-c and TC/HDL-c) was constructed. Logistic regression was used to assess the relationship between lipid profile, lipid ratios and GDM. RESULTS Of 1586 pregnant women, 741 were diagnosed with GDM. After adjusting for potential confounders, TG, ApoA1, ApoB, LDL-c, triglyceride glucose index, TG/HDL-c, and TC/HDL-c in early pregnancy were positively associated with the risk of GDM (odds ratios [95% CI] for extreme interquartile comparisons were 2.040 (1.468-2.843), 1.506 (1.091-2.082), 1.529 (1.110-2.107), 1.504 (1.086-2.086), 1.952 (1.398-2.731), 2.127 (1.526-2.971), and 2.370 (1.700-3.312), all trend P < 0.05). HDL-c was negatively associated with the risk of GDM (0.639: 0.459-0.889, trend P all less than 0.05). Similarly, in mid-pregnancy, lower levels of HDL-c, higher levels of triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio were associated with increased risk of GDM (all trends P < 0.05). Stably high levels (both ≥ median for early and mid-pregnancy) of triglyceride glucose index, TG/HDL-c and TC/HDL-c were associated with increased risk of GDM (OR [95% CI]: 2.369 (1.438-3.940), 1.588 (1.077-2.341), 1.921 (1.309-2.829), respectively). The opposite was true for HDL-c, where stable high levels were negatively associated with GDM risk (OR [95% CI]: 0.599 (0.405-0.883)). CONCLUSION Increases in triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio in early and mid-pregnancy, as well as their stable high levels from early to mid-pregnancy, are associated with a higher risk of GDM. In contrast, increased levels of HDL-c, both in early and mid-pregnancy, and their stable high levels from early to mid-pregnancy were associated with a lower risk of GDM. That highlighted their possible clinical relevance in identifying those at high risk of GDM.
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Affiliation(s)
- Xingyan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Suping Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Jie Lin
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
- The Second Attached Hospital of Fujian Medical University, Quanzhou, 362000, China
| | - Jungu Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Liuyan Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Le Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Zhiyu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Yuting Dong
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Mei Ma
- Department of Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350001, China
| | - Huangyuan Li
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, 350122, China
| | - Shaowei Lin
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China
| | - Xiaoxu Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China.
| | - Jinying Luo
- Department of Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350001, China.
| | - Siying Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, Fujian, China.
- Department of Epidemiology and Health Statistics, the Key Laboratory of Environment and Health among Universities and Colleges in Fujian, School of Public Health, Fujian Medical University, Minhou County, Fuzhou, China.
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Zhu YT, Xiang LL, Chen YJ, Zhong TY, Wang JJ, Zeng Y. Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus. World J Diabetes 2024; 15:1242-1253. [PMID: 38983822 PMCID: PMC11229959 DOI: 10.4239/wjd.v15.i6.1242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/05/2024] [Accepted: 04/25/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants. AIM To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA. METHODS The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses. RESULTS After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram's prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit. CONCLUSION Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.
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Affiliation(s)
- Yi-Tian Zhu
- Department of Clinical Laboratory, Jinling Clinical Medical College of Nanjing Medical University, Nanjing 210002, Jiangsu Province, China
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
| | - Lan-Lan Xiang
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
| | - Ya-Jun Chen
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
| | - Tian-Ying Zhong
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
| | - Jun-Jun Wang
- Department of Clinical Laboratory, Jinling Clinical Medical College of Nanjing Medical University, Nanjing 210002, Jiangsu Province, China
| | - Yu Zeng
- Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
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Cao Y, Sheng J, Zhang D, Chen L, Jiang Y, Cheng D, Su Y, Yu Y, Jia H, He P, Wang L, Xu X. The role of dietary fiber on preventing gestational diabetes mellitus in an at-risk group of high triglyceride-glucose index women: a randomized controlled trial. Endocrine 2023; 82:542-549. [PMID: 37737931 DOI: 10.1007/s12020-023-03478-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 08/01/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND Pregnant women with a high triglyceride-glucose (TyG) index during early pregnancy may increase the risk of gestational diabetes mellitus (GDM), and dietary fiber could play an important role in glucose and lipid metabolism. However, no trials have tested the effects of dietary fiber on preventing GDM in women with a high TyG index. This study aims to investigate whether GDM can be prevented by dietary fiber supplementation in women with a TyG index ≥8.5 during early pregnancy (<20 weeks). METHODS A randomized clinical trial was performed among 295 women with a TyG index ≥8.5 before 20 weeks of gestation, divided into a fiber group (24 g dietary fiber powder/day) or a control group (usual care). The intervention was conducted from 20 to 24+6 gestational weeks, and both groups received guidance on exercise and diet. The primary outcomes were the incidence of GDM diagnosed by a 75 g oral glucose tolerance test at 25-28 gestational weeks, and levels of maternal blood glucose, lipids. Secondary outcomes include gestational hypertension, postpartum hemorrhage, preterm birth, and other maternal and neonatal complications. RESULTS GDM occurred at 11.2% (10 of 89) in the fiber group, which was significantly lower than 23.7 (44 of 186) in the control group (P = 0.015). The mean gestational weeks increased dramatically in the fiber group compared with the control group (39.07 ± 1.08 vs. 38.58 ± 1.44 weeks, P = 0.006). The incidence of preterm birth was 2.3% (2 of 86) of women randomized to the fiber group compared with 9.4% (17 of 181) in the control group (P = 0.032). The concentrations of 2 h postprandial blood glucose showed statistically higher in the control group compared with the intervention group (6.69 ± 1.65 vs. 6.45 ± 1.25 mmol/L, P = 0.026). There were no other significant differences between groups in lipid profile values, or other secondary outcomes. CONCLUSION An intervention with dietary fiber supplementation during pregnancy may prevent GDM and preterm birth in women with a TyG index ≥8.5 before 20 weeks of gestation.
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Affiliation(s)
- Yannan Cao
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Jing Sheng
- Department of Radiology, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
| | - Dongyao Zhang
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
- Department of Obstetrics and Gynecology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China
| | - Li Chen
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Ying Jiang
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
- Nursing Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Decui Cheng
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Yao Su
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Yuexin Yu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Haoyi Jia
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Pengyuan He
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Li Wang
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China
| | - Xianming Xu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201600, China.
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Li H, Miao C, Liu W, Gao H, Li W, Wu Z, Cao H, Zhu Y. First-Trimester Triglyceride-Glucose Index and Risk of Pregnancy-Related Complications: A Prospective Birth Cohort Study in Southeast China. Diabetes Metab Syndr Obes 2022; 15:3705-3715. [PMID: 36465992 PMCID: PMC9717426 DOI: 10.2147/dmso.s378964] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/01/2022] [Indexed: 11/29/2022] Open
Abstract
Purpose To evaluate the relationships of the triglyceride-glucose (TyG) index with pregnancy-related complications (PRCs) and to clarify the predictability of the TyG index for PRCs. Patients and Methods Totally of 11,387 women with a singleton pregnancy were prospectively followed until after delivery. Maternal fasting lipids and glucose concentration were measured in the first trimester (11 weeks gestation on average). The TyG index was calculated as ln [triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2]. We used generalized linear models to calculate the relative risks and 95% confidence intervals. Receiver-operating characteristic curve analysis was employed to assess the ability of the TyG index to predict the risks of PRCs. Results Smooth spline reveals that the probability of gestational diabetes mellitus (GDM) is intensified with the increasing TyG index. Multivariate logistic regression adjusted for risk factors demonstrates a 1-unit and a 1-SD increment in the TyG index raises the risk of GDM by 3.63 and 1.57 times, respectively. Identically, the risk of GDM maximizes in the TyG quintile 5 (OR: 3.14; 95% CI: 2.55~3.85) relative to the lowest TyG index group. However, no association between TyG index and the risk of other PRCs was observed after full adjustment. The area under receiver operating characteristic curves is 0.647 (95% CI: 0.632-0.66) for GDM, and the optimal predictive cut-off is 8.55, with a specificity of 0.679 and sensitivity of 0.535. Conclusion The first-trimester TyG index is significantly associated with the risk of incident GDM, while the relationships between the TyG index and other PRCs need further exploration.
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Affiliation(s)
- Haibo Li
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Chong Miao
- Department of Information, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
| | - Wenjuan Liu
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
- Division of Birth Cohort Study, Fujian Children’s Hospital, Fuzhou, People’s Republic of China
| | - Haiyan Gao
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
- Division of Birth Cohort Study, Fujian Obstetrics and Gynecology Hospital, Fuzhou, People’s Republic of China
| | - Wei Li
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
- Division of Birth Cohort Study, Fujian Obstetrics and Gynecology Hospital, Fuzhou, People’s Republic of China
| | - Zhengqin Wu
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
- Division of Birth Cohort Study, Fujian Obstetrics and Gynecology Hospital, Fuzhou, People’s Republic of China
| | - Hua Cao
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Disease Research, Fuzhou, People’s Republic of China
| | - Yibing Zhu
- Division of Birth Cohort Study, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, People’s Republic of China
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Salvatori B, Linder T, Eppel D, Morettini M, Burattini L, Göbl C, Tura A. TyGIS: improved triglyceride-glucose index for the assessment of insulin sensitivity during pregnancy. Cardiovasc Diabetol 2022; 21:215. [PMID: 36258194 PMCID: PMC9580191 DOI: 10.1186/s12933-022-01649-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/28/2022] [Indexed: 11/21/2022] Open
Abstract
Background The triglyceride-glucose index (TyG) has been proposed as a surrogate marker of insulin resistance, which is a typical trait of pregnancy. However, very few studies analyzed TyG performance as marker of insulin resistance in pregnancy, and they were limited to insulin resistance assessment at fasting rather than in dynamic conditions, i.e., during an oral glucose tolerance test (OGTT), which allows more reliable assessment of the actual insulin sensitivity impairment. Thus, first aim of the study was exploring in pregnancy the relationships between TyG and OGTT-derived insulin sensitivity. In addition, we developed a new version of TyG, for improved performance as marker of insulin resistance in pregnancy. Methods At early pregnancy, a cohort of 109 women underwent assessment of maternal biometry and blood tests at fasting, for measurements of several variables (visit 1). Subsequently (26 weeks of gestation) all visit 1 analyses were repeated (visit 2), and a subgroup of women (84 selected) received a 2 h-75 g OGTT (30, 60, 90, and 120 min sampling) with measurement of blood glucose, insulin and C-peptide for reliable assessment of insulin sensitivity (PREDIM index) and insulin secretion/beta-cell function. The dataset was randomly split into 70% training set and 30% test set, and by machine learning approach we identified the optimal model, with TyG included, showing the best relationship with PREDIM. For inclusion in the model, we considered only fasting variables, in agreement with TyG definition. Results The relationship of TyG with PREDIM was weak. Conversely, the improved TyG, called TyGIS, (linear function of TyG, body weight, lean body mass percentage and fasting insulin) resulted much strongly related to PREDIM, in both training and test sets (R2 > 0.64, p < 0.0001). Bland–Altman analysis and equivalence test confirmed the good performance of TyGIS in terms of association with PREDIM. Different further analyses confirmed TyGIS superiority over TyG. Conclusions We developed an improved version of TyG, as new surrogate marker of insulin sensitivity in pregnancy (TyGIS). Similarly to TyG, TyGIS relies only on fasting variables, but its performances are remarkably improved than those of TyG. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-022-01649-8.
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Affiliation(s)
| | - Tina Linder
- Department of Obstetrics and Gynaecology, Medical University of Vienna, 1090, Vienna, Austria
| | - Daniel Eppel
- Department of Obstetrics and Gynaecology, Medical University of Vienna, 1090, Vienna, Austria
| | - Micaela Morettini
- Department of Information Engineering, Università Politecnica Delle Marche, 60131, Ancona, Italy
| | - Laura Burattini
- Department of Information Engineering, Università Politecnica Delle Marche, 60131, Ancona, Italy
| | - Christian Göbl
- Department of Obstetrics and Gynaecology, Medical University of Vienna, 1090, Vienna, Austria
| | - Andrea Tura
- CNR Institute of Neuroscience, Corso Stati Uniti 4, 35127, Padua, Italy.
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Shen L, Wang D, Huang Y, Ye L, Zhu C, Zhang S, Cai S, Wang Z, Chen H. Longitudinal trends in lipid profiles during pregnancy: Association with gestational diabetes mellitus and longitudinal trends in insulin indices. Front Endocrinol (Lausanne) 2022; 13:1080633. [PMID: 36714591 PMCID: PMC9880552 DOI: 10.3389/fendo.2022.1080633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023] Open
Abstract
OBJECTIVE To investigate the correlation of trends in lipid profiles from first to second trimester with trends in insulin indices and gestational diabetes mellitus (GDM). METHODS Secondary analysis of an ongoing prospective cohort study was conducted on 1234 pregnant women in a single center. Lipid profiles, glucose metabolism and insulin indices were collected in the first and second trimesters. Trends in lipid profiles were divided into four subgroups: low-to-low, high-to-high, high-to-low and low-to-high group. Insulin indices including homeostasis model assessment of insulin resistance and quantitative insulin sensitivity check index were calculated to evaluate insulin resistance (IR). Trends in insulin indices were described as: no IR, persistent IR, first-trimester IR alone and second-trimester IR alone. Pearson correlation analysis and multivariate logistic regression were performed to assess the associations of lipid profiles subgroups with insulin indices and GDM. RESULTS First- and second-trimester total cholesterol (TC), triglycerides (TG) and high-density lipoprotein cholesterol were strongly correlated to first- and second-trimester insulin indices. Only TG had a sustained correlation with glucose metabolism indices. High-to-high low-density lipoprotein cholesterol (LDL-c) was an independent risk factor for GDM. High-to-high TG and high-to-low TG groups were independent risk factors for persistent IR. High-to-high TG and low-to-high TG groups were independent risk factors for second-trimester IR alone. CONCLUSION TG has a sustained correlation with insulin indices and glucose metabolism indices. Persistently high TG is an independent risk factor for persistent IR and second-trimester IR alone. Regardless of whether pregnant women have first-trimester IR, lower TG levels help reduce the risk for persistent IR or subsequent development of IR. These results highlight the benefit of lowering TG levels in early and middle pregnancy to prevent the development of IR.
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Affiliation(s)
| | | | | | | | | | | | | | - Zilian Wang
- *Correspondence: Haitian Chen, ; Zilian Wang,
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Song S, Zhang Y, Qiao X, Duo Y, Xu J, Peng Z, Zhang J, Chen Y, Nie X, Sun Q, Yang X, Lu Z, Liu S, Zhao T, Yuan T, Fu Y, Dong Y, Zhao W, Sun W, Wang A. HOMA-IR as a risk factor of gestational diabetes mellitus and a novel simple surrogate index in early pregnancy. Int J Gynaecol Obstet 2021; 157:694-701. [PMID: 34449903 DOI: 10.1002/ijgo.13905] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/26/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVE To assess the association between insulin resistance and gestational diabetes mellitus (GDM) in early pregnancy and find a simple surrogate index of the homeostasis model assessment of insulin resistance (HOMA-IR). METHODS A total of 700 pregnant women were included in this prospective, double-center, observational cohort study. The glucose and lipid metabolic characterization was performed at 6-12 weeks of pregnancy. All participants underwent a 75-g oral glucose tolerance test at 24-28 weeks of pregnancy. Linear regression analysis was applied to find a novel surrogate index of HOMA-IR. Binary logistic analysis was applied to estimate possible associations of different indices with GDM and insulin resistance. RESULTS GDM was diagnosed in 145 of 700 women with singleton pregnancies (20.7%). HOMA-IR was higher in the GDM group than in the normal glucose tolerance (NGT) group and was an individual risk factor for GDM (adjusted risk ratio RR 1.371, 95% confidence interval [CI] 1.129-1.665, P < 0.001). TyHGB index as the surrogate index of HOMA-IR was represented as TG/HDL-C + 0.7*FBG (mmol/L) +0.1*preBMI (kg/m2 )(where TG/HDL-C is triglyceride/high-density lipoprotein cholesterol; FBG is fasting blood glucose, and preBMI is the pre-pregnancy body mass index [calculated as weight in kilograms divided by the square of height in meters]). The cut-off point of the TyHGB index was 6.0 (area under the curve 0.827, 95% CI 0.794-0.861, P < 0.001) for mild insulin resistance. CONCLUSION Increased HOMA-IR in early pregnancy was a risk factor of GDM. TyHGB index could be a surrogate index of HOMA-IR and had a predictive value for GDM.
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Affiliation(s)
- Shuoning Song
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yuemei Zhang
- Department of Obstetrics, Haidian District Maternal and Child Health Care Hospital, Beijing, China
| | - Xiaolin Qiao
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, China
| | - Yanbei Duo
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Jiyu Xu
- Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Zhenyao Peng
- Department of Dean's Office, Haidian District Maternal and Child Health Care Hospital, Beijing, China
| | - Jing Zhang
- Department of Laboratory, Haidian District Maternal and Child Health Care Hospital, Beijing, China
| | - Yan Chen
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, China
| | - Xiaorui Nie
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, China
| | - Qiujin Sun
- Department of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, China
| | - Xianchun Yang
- Department of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing, China
| | - Zechun Lu
- National Center for Women and Children's Health, China CDC, Beijing, China
| | - Shixuan Liu
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Tianyi Zhao
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Tao Yuan
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yong Fu
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yingyue Dong
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Weigang Zhao
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Wei Sun
- Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Ailing Wang
- National Center for Women and Children's Health, China CDC, Beijing, China
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8
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Kim JA, Kim J, Roh E, Hong SH, Lee YB, Baik SH, Choi KM, Noh E, Hwang SY, Cho GJ, Yoo HJ. Triglyceride and glucose index and the risk of gestational diabetes mellitus: A nationwide population-based cohort study. Diabetes Res Clin Pract 2021; 171:108533. [PMID: 33157117 DOI: 10.1016/j.diabres.2020.108533] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 08/29/2020] [Accepted: 10/26/2020] [Indexed: 01/31/2023]
Abstract
AIMS Pre-pregnancy insulin resistance is one of the main pathophysiologies of gestational diabetes mellitus (GDM). Triglyceride-glucose (TyG) index is a marker of insulin resistance. We aimed to evaluate the association between pre-pregnancy TyG index and GDM in primipara women. METHODS A total of 380,208 women who underwent a Korean national health screening exam within 2 years before their first delivery, between January 1, 2012 and December 31, 2015, were included. The TyG index was calculated as ln [triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2]. RESULTS Among the 380,208 primipara women, 17,239 women were diagnosed with GDM (4.53%). Multivariate logistic regression analysis adjusted for risk factors showed a higher odds ratio of 1.73 for GDM (95% CI 1.65-1.81) in the highest quartile than that in the lowest quartile. A 1-SD increase in the TyG index increased the risk of GDM (31%) and GDM requiring insulin therapy (82%) in the fully adjusted model. A 1-unit increase in the TyG index significantly increased the risk of GDM and GDM requiring insulin treatment by 1.81 and 3.69 times, respectively.The impact of a high TyG index on the risk of GDM was more profound in the subjects aged ≥ 35 years, with obesity, with impaired fasting glucose, who are current smokers, and with a family history of diabetes mellitus. CONCLUSIONS Increased pre-pregnancy TyG index is associated with a risk of GDM. Elevation of the TyG index may be an early marker of GDM.
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Affiliation(s)
- Jung A Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Jinsil Kim
- Smart Healthcare Cancer, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Eun Roh
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - So-Hyeon Hong
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - You-Bin Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Sei Hyun Baik
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Kyung Mook Choi
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Eunjin Noh
- Smart Healthcare Cancer, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Soon Young Hwang
- Department of Biostatistics, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Geum Joon Cho
- Department of Obstetrics and Gynecology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Hye Jin Yoo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
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9
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Sánchez-García A, Rodríguez-Gutiérrez R, Saldívar-Rodríguez D, Guzmán-López A, Castillo-Castro C, Mancillas-Adame L, Santos-Santillana K, González-Nava V, González-González JG. Diagnostic accuracy of the triglyceride-glucose index for gestational diabetes screening: a practical approach. Gynecol Endocrinol 2020; 36:1112-1115. [PMID: 32233827 DOI: 10.1080/09513590.2020.1742687] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
The oral glucose tolerance test (OGTT) remains as the gold standard to diagnose gestational diabetes mellitus (GDM); however, this test may be inconvenient and costly. Hence, other easy to perform and accurate diagnostic alternatives would be valuable for maternal care. The objective of the study was to assess the diagnostic performance of the TyG index to screen for GDM at 24-28 of pregnancy. A total of 140 pregnant women who received the one-step 2 h 75 g OGTT were included. Overall GDM prevalence was 27.1% according to IADSPG criteria. The mean TyG index value in the GDM group was significantly higher than the TyG index for the no GDM group (4.88 ± 0.70 versus 4.68 ± 0.19, p<.001). A sensitivity of 89% [95% CI 0.75-0.97] and a specificity of 50% [95% CI 0.39-0.60)], accompanied by a high negative predictive value of 93% was observed. No differences were found in maternal and neonatal outcomes irrespective of the TyG cutoff value for GDM. According to our results, the TyG index may be a highly sensitive and easy to perform screening test for GDM.
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Affiliation(s)
- Adriana Sánchez-García
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - René Rodríguez-Gutiérrez
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
- Universidad Autonoma de Nuevo Leon, Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Monterrey, Nuevo León, Mexico
- Knowledge and Evaluation Research Unit in Endocrinology, Mayo Clinic, Rochester, MN, USA
- Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Research Unit, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - Donato Saldívar-Rodríguez
- Obstetrics and Gynecology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - Abel Guzmán-López
- Obstetrics and Gynecology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - Carolina Castillo-Castro
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - Leonardo Mancillas-Adame
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
- Universidad Autonoma de Nuevo Leon, Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Monterrey, Nuevo León, Mexico
| | - Karla Santos-Santillana
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
| | - Victoria González-Nava
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
- Universidad Autonoma de Nuevo Leon, Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Monterrey, Nuevo León, Mexico
| | - José Gerardo González-González
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
- Universidad Autonoma de Nuevo Leon, Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Monterrey, Nuevo León, Mexico
- Facultad de Medicina y Hospital Universitario "Dr Jose Eleuterio Gonzalez", Research Unit, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico
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10
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Zhang Y, Qin P, Lou Y, Zhao P, Li X, Qie R, Wu X, Han M, Huang S, Zhao Y, Liu D, Wu Y, Li Y, Yang X, Zhao Y, Feng Y, Wang C, Ma J, Peng X, Chen H, Zhao D, Xu S, Wang L, Luo X, Zhang M, Hu D, Hu F. Association of TG/HDLC ratio trajectory and risk of type 2 diabetes: A retrospective cohort study in China. J Diabetes 2020; 13:402-412. [PMID: 33074586 DOI: 10.1111/1753-0407.13123] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/20/2020] [Accepted: 10/15/2020] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND The association of ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-C ratio) change trajectory with risk of type 2 diabetes mellitus (T2DM) remains unknown. The aim of this study was to evaluate the association between risk of T2DM and TG/HDL-C ratio change trajectory. METHODS A total of 18 444 participants aged 18-80 years old were included in this cohort study. Linear regression and quadratic regression models were used to determine the TG/HDL-C ratio change trajectory. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between TG/HDL-C ratio change trajectory and probability of T2DM. RESULTS T2DM developed in 714 participants during a median follow-up of 5.74 years (92 076.23 person-years of follow-up). After adjusting for baseline potential confounders, odds of T2DM were greater for participants with the increasing, U-shape, bell-shape, and other shape change vs decreasing change (adjusted OR [aOR] 2.01, 95% CI 1.42-2.81; 1.56, 1.15-2.13; 1.60, 1.17-2.20; and 1.49, 1.13-2.00, respectively). The results were robust in the sensitivity analyses on excluding baseline participants with T2DM. Moreover, the associations remained significant with male sex, age <60 years and body mass index <24 kg/m2 . CONCLUSIONS This retrospective study revealed increased probability of T2DM with increasing, U-shape, bell-shape, and other-shape TG/HDL-C ratio change trajectories, especially with male sex, age <60 years and body mass index <24 kg/m2 .
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Affiliation(s)
- Yanyan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Pei Qin
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Yanmei Lou
- Department of Health Management, Beijing Xiaotangshan Hospital, Beijing, People's Republic of China
| | - Ping Zhao
- Department of Health Management, Beijing Xiaotangshan Hospital, Beijing, People's Republic of China
| | - Xue Li
- Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Ranran Qie
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Xiaoyan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Minghui Han
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Shengbing Huang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Yuying Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Yang Li
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Xingjin Yang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Yifei Feng
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Changyi Wang
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Jianping Ma
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Xiaolin Peng
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Hongen Chen
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Dan Zhao
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Shan Xu
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Li Wang
- Department of Non-communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease, Shenzhen, People's Republic of China
| | - Xinping Luo
- School of Basic Medicine, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Ming Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
| | - Fulan Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Center, Shenzhen, People's Republic of China
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11
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Sánchez-García A, Rodríguez-Gutiérrez R, Saldívar-Rodríguez D, Guzmán-López A, Mancillas-Adame L, González-Nava V, Santos-Santillana K, González-González JG. Early triglyceride and glucose index as a risk marker for gestational diabetes mellitus. Int J Gynaecol Obstet 2020; 151:117-123. [PMID: 32679624 DOI: 10.1002/ijgo.13311] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/08/2020] [Accepted: 07/14/2020] [Indexed: 12/26/2022]
Abstract
OBJECTIVE To assess the risk of gestational diabetes mellitus (GDM) according to the triglyceride and glucose (TyG) index values during the first trimester of pregnancy in Latin American women. METHODS Pregnant women were enrolled at their first prenatal visit at the Obstetric Division in the University Hospital "Dr. José E. González". Triglycerides and fasting plasma glucose (FPG) were collected to determine the TyG index. GDM diagnosis was performed by a single-step 2-hour 75-g oral glucose tolerance test. Generalized linear models were used to determine risk ratios; pregnancy outcomes at delivery were collected from the hospital medical records. RESULTS A total of 164 pregnant women were included. GDM was present in 29 (17.7%) women. No significant differences in age, first-trimester body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters), family history of diabetes, and TyG index were observed between GDM cases and the reference group without GDM. The adjusted analysis showed no association between TyG and GDM (risk ratio [RR] 1.03, 95% confidence interval [CI] 0.57-1.88]). Higher TyG index values between women with and without a diagnosis of GDM in the second trimester were observed. No significant differences were identified in pregnancy outcomes, although a trend was observed for hyperbilirubinemia in women with first-trimester TyG index values greater than 8.7. CONCLUSIONS Our findings do not support the use of the TyG index for GDM prediction in Latin American women.
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Affiliation(s)
- Adriana Sánchez-García
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - René Rodríguez-Gutiérrez
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Knowledge and Evaluation Research Unit in Endocrinology, Mayo Clinic, Rochester, MN, USA.,Research Unit, Facultad de Medicina y Hospital Universitario "Dr. Jose E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - Donato Saldívar-Rodríguez
- Obstetric Division, Facultad de Medicina y Hospital Universitario "Dr. Jose E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - Abel Guzmán-López
- Obstetric Division, Facultad de Medicina y Hospital Universitario "Dr. Jose E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - Leonardo Mancillas-Adame
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - Victoria González-Nava
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - Karla Santos-Santillana
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
| | - José G González-González
- Endocrinology Division, Facultad de Medicina y Hospital Universitario "Dr. José E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit México), Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico.,Research Unit, Facultad de Medicina y Hospital Universitario "Dr. Jose E. González", Universidad Autónoma de Nuevo León, Monterrey, NL, Mexico
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12
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Liu PJ, Liu Y, Ma L, Yao AM, Chen XY, Hou YX, Wu LP, Xia LY. The Predictive Ability of Two Triglyceride-Associated Indices for Gestational Diabetes Mellitus and Large for Gestational Age Infant Among Chinese Pregnancies: A Preliminary Cohort Study. Diabetes Metab Syndr Obes 2020; 13:2025-2035. [PMID: 32606861 PMCID: PMC7305827 DOI: 10.2147/dmso.s251846] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/27/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND/AIMS To investigate the potential of maternal first-trimester triglyceride (TG) to high-density lipoprotein cholesterol (TG/HDL-c) ratio, triglyceride glucose index (TyG) and total cholesterol (TC)/HDL-c to predict the risk of later gestational diabetes mellitus (GDM) and large for gestational age (LGA) newborn in Chinese women. METHODS We included 352 women with a singleton pregnancy, who were followed up prospectively from the first prenatal visit until delivery. Fasting glucose and plasma lipid profiles including TG, TC, HDL-c, and low-density lipoprotein cholesterol (LDL-c) were measured in the first trimester. A binary logistic regression analysis was performed to determine the odds ratios (ORs) and 95% confidence intervals (CIs) of GDM and LGA according to tertiles of those indices, respectively. Receiver-operating characteristic curve (ROC) and areas under the curve (AUC) were employed to evaluate the ability of those indices to predict the risk of GDM and LGA infants, and differences in the AUC values between them were compared. RESULTS Women with the top tertile of TG/HDL-c or TyG other than TC/HDL-c had a significantly higher risk of GDM (ORTG/HDL-c=2.388, 95% CI 1.026-5.467; ORTyG=3.535, 95% CI 1.483-8.426, respectively) and LGA infant delivery (ORTG/HDL-c=3.742, 95% CI 1.114-12.569; ORTyG=3.011, 95% CI 1.012-8.962, respectively) than women with the lowest tertile of TG/HDL-c or TyG after adjusting for confounders. The AUC of TG/HDL-c and TyG to detect GDM was 0.664 (95% CI 0.595-0.733) and 0.686 (95% CI 0.615-0.756), respectively, and that to detect LGA was 0.646 (95% CI 0.559-0.734) and 0.643 (95% CI 0.552-0.735), respectively (all P < 0.01). There were no statistical differences between TG/HDL-c and TyG in the ability of predicting the risk of GDM or LGA infants. CONCLUSION Maternal first-trimester TG/HDL-c and TyG are both good indicators in predicting the risk of later GDM and LGA newborn, and it may be useful to evaluate them in early pregnancy.
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Affiliation(s)
- Peng Ju Liu
- Department of Clinical Nutrition, Peking Union Medical College Hospital, China Academic Medical Science and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yanping Liu
- Department of Clinical Nutrition, Peking Union Medical College Hospital, China Academic Medical Science and Peking Union Medical College, Beijing, People’s Republic of China
| | - Liangkun Ma
- Department of Gynaecology and Obstetrics, Peking Union Medical College Hospital, China Academic Medical Science and Peking Union Medical College, Beijing, People’s Republic of China
| | - Ai Min Yao
- Department of Gynaecology and Obstetrics, Shunyi District Maternal and Child Health Hospital, Beijing, People’s Republic of China
| | - Xiao Yan Chen
- Department of Gynaecology and Obstetrics, Quanzhou Maternal and Child Health Hospital, Fujian, People’s Republic of China
| | - Yi Xuan Hou
- Peking Union Medical College School of Nursing, Beijing, People’s Republic of China
| | - Li Ping Wu
- Peking Union Medical College School of Nursing, Beijing, People’s Republic of China
| | - Liang Yu Xia
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College Hospital, China Academic Medical Science and Peking Union Medical College, Beijing, People’s Republic of China
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13
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Barratclough A, Gomez FM, Morey JS, Deming A, Parry C, Meegan JM, Carlin KP, Schwacke L, Venn-Watson S, Jensen ED, Smith CR. Pregnancy profiles in the common bottlenose dolphin (Tursiops truncatus): Clinical biochemical and hematological variations during healthy gestation and a successful outcome. Theriogenology 2019; 142:92-103. [PMID: 31585227 DOI: 10.1016/j.theriogenology.2019.09.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 08/15/2019] [Accepted: 09/18/2019] [Indexed: 11/19/2022]
Abstract
The physiological demands of pregnancy inevitably result in changes of both biochemical and hematological parameters as the fetus develops. Alterations in blood parameters have been observed to shift according to both trimester and species, to support fetal physiological needs and maternal basal requirements. Establishing normal reference ranges for each stage in gestation is important to facilitate diagnosis of underlying health concerns and prevent over-diagnosing abnormalities. Despite bottlenose dolphins (Tursiops truncatus) being one of the most highly studied cetaceans, the blood profile changes occurring as a result of pregnancy have not been previously described. A retrospective analysis was performed from blood samples obtained from 42 successful pregnancies from 20 bottlenose dolphins in a managed population over 30 years. Samples were compared to non-pregnant states and among trimesters of pregnancy. Blood profile fluctuations occurred throughout gestation, however significant alterations predominantly occurred between the 2nd and 3rd trimester. Hematological changes from the 2nd to the 3rd trimester included a decrease in lymphocytes, decrease in platelet count, and hemoconcentration with increased hematocrit and hemoglobin. Biochemical changes in the 3rd trimester included significant reductions in ALKP (alkaline phosphatase), ALT (alanine aminotransferase) and AST (aspartate aminotransferase) with significant increases observed in albumin, globulins, total protein, cholesterol, triglycerides and CO2. It's important to note that despite significant shifts occurring between the 2nd and 3rd trimester, there was no significant change in platelets, hematocrit, hemoglobin, lymphocytes or CO2 between non-pregnant and 3rd trimester blood samples. The normal reference ranges for each trimester established herein, will enable future identification of abnormalities occurring during pregnancy and help improve our understanding of factors potentially influencing a failed or successful pregnancy outcome.
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Affiliation(s)
- Ashley Barratclough
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Forrest M Gomez
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Jeanine S Morey
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Alissa Deming
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States
| | - Celeste Parry
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Jennifer M Meegan
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Kevin P Carlin
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States; U.S. Navy Marine Mammal Program, 53560 Hull Street, San Diego, CA, 92152, United States.
| | - Lori Schwacke
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
| | - Stephanie Venn-Watson
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States
| | - Eric D Jensen
- U.S. Navy Marine Mammal Program, 53560 Hull Street, San Diego, CA, 92152, United States.
| | - Cynthia R Smith
- National Marine Mammal Foundation, 2240 Shelter Island Drive, Suite 200, San Diego, CA, 92106, United States.
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