The Predictive Ability of Hepatic Steatosis Index for Gestational Diabetes Mellitus and Large for Gestational Age Infant Compared with Other Noninvasive Indices Among Chinese Pregnancies: A Preliminary Double-center Cohort Study

Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus

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.

Diagnostic Approach to Elevated Liver Function Tests during Pregnancy: A Pragmatic Narrative Review

Liver disease is not uncommon during pregnancy and is associated with increased maternal and fetal/neonatal morbidity and mortality. Physiological changes during pregnancy, including a hyperestrogenic state, increase in circulating plasma volume and/or reduction in splanchnic vascular resistance, and hemostatic imbalance, may mimic or worsen liver disease. For the clinician, it is important to distinguish among the first presentation or exacerbation of chronic liver disease, acute liver disease non-specific to pregnancy, and pregnancy-specific liver disease. This last group classically includes conditions such as hyperemesis gravidarum, intrahepatic cholestasis of pregnancy, liver disorders associated with the pre-eclampsia spectrum, and an acute fatty liver of pregnancy. All of these disorders often share pathophysiological mechanisms, symptoms, and laboratory findings (such as elevated liver enzymes), but a prompt and correct diagnosis is fundamental to guide obstetric conduct, reduce morbidity and mortality, and inform upon the risk of recurrence or development of other chronic diseases later on in life. Finally, the cause of elevated liver enzymes during pregnancy is unclear in up to 30-40% of the cases, and yet, little is known on the causes and mechanisms underlying these alterations, or whether these findings are associated with worse maternal/fetal outcomes. In this narrative review, we aimed to summarize pragmatically the diagnostic work-up and the management of subjects with elevated liver enzymes during pregnancy.

Incidence of Prediabetes/Diabetes among Women with Prior Gestational Diabetes and Non-Alcoholic Fatty Liver Disease: A Prospective Observational Study

Background and Objectives

This prospective longitudinal study aims to evaluate and compare the incidence of prediabetes/diabetes among women stratified at the baseline postpartum visit according to the prior GDM and NAFLD status.

Methods

Of the 309 women with baseline postpartum assessment at a median of 16 months following the index delivery, 200 (64.7%) [GDM: 137 (68.5%), normoglycaemia: 63 (31.5%)] were available for the follow-up analysis (performed at median of 54 months following the index delivery) and were participants for this study. We obtained relevant demographic, medical and obstetric details and performed a 75 g OGTT with glucose estimation at 0 and 120 min. NAFLD status was defined by ultrasonography at the baseline visit. Participants were divided into four groups: no NAFLD and no prior GDM (group 1), NAFLD but no prior GDM (group 2), prior GDM but no NAFLD (group 3), and NAFLD and prior GDM (group 4).

Results

The mean age of study participants (n = 200) was 32.2 ± 5.1 years, and the mean interval between the two visits was 34.8 ± 5.5 months. A total of 74 (37%) women had progression to prediabetes/diabetes [incidence rate of 12.8/100 woman-years]. The incidence rates (per 100 woman-years) were 8.6, 8.9, 13.4 and 15.3 in groups 1, 2, 3 and 4, respectively. The adjusted hazard ratio for incident (new-onset) prediabetes/diabetes in group 4 (reference: group 1) was 1.99 (95% CI 0.80, 4.96, P = 0.140). Among women with baseline NAFLD (irrespective of GDM status), the risk of incident prediabetes/diabetes increased with an increase in the duration of follow-up (3.03-fold higher per year of follow-up, P = 0.029) and was significantly higher in women who were not employed (6.43, 95% CI 1.74, 23.7, P = 0.005) and in women with GDM requiring insulin/metformin during pregnancy (4.46, 95% CI 1.27, 15.64, P = 0.019).

Conclusion

NAFLD and GDM increased the risk for glycaemic deterioration in young Indian women. Future studies should focus on evaluating the effectiveness of lifestyle and behavioural interventions in such high-risk women.

Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women

BACKGROUND

Liver plays an important role in maintaining glucose homeostasis. We aimed to examine the associations of liver enzymes and hepatic steatosis index (HSI, a reliable biomarker for non-alcoholic fatty liver disease) in early pregnancy with subsequent GDM risk, as well as the potential mediation effects of lipid metabolites on the association between HSI and GDM.

METHODS

In a birth cohort, liver enzymes were measured in early pregnancy (6-15 gestational weeks, mean 10) among 6,860 Chinese women. Multivariable logistic regression was performed to examine the association between liver biomarkers and risk of GDM. Pearson partial correlation and least absolute shrinkage and selection operator (LASSO) regression were conducted to identify lipid metabolites that were significantly associated with HSI in a subset of 948 women. Mediation analyses were performed to estimate the mediating roles of lipid metabolites on the association of HSI with GDM.

RESULTS

Liver enzymes and HSI were associated with higher risks of GDM after adjustment for potential confounders, with ORs ranging from 1.42 to 2.24 for extreme-quartile comparisons (false discovery rate-adjusted P-trend ≤0.005). On the natural log scale, each SD increment of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and HSI was associated with a 1.15-fold (95% CI: 1.05, 1.26), 1.10-fold (1.01, 1.20), 1.21-fold (1.10, 1.32), 1.15-fold (1.04, 1.27), and 1.33-fold (1.18, 1.51) increased risk of GDM, respectively. Pearson partial correlation and LASSO regression identified 15 specific lipid metabolites in relation to HSI. Up to 52.6% of the association between HSI and GDM risk was attributed to the indirect effect of the HSI-related lipid score composed of lipid metabolites predominantly from phospholipids (e.g., lysophosphatidylcholine and ceramides) and triacylglycerol.

CONCLUSIONS

Elevated liver enzymes and HSI in early pregnancy, even within a normal range, were associated with higher risks of GDM among Chinese pregnant women. The association of HSI with GDM was largely mediated by altered lipid metabolism.

Elevated Hepatic Steatosis Index is Associated with the Development of Adverse Maternal, but Not Adverse Neonatal, Outcomes: A Retrospective Cohort Study

Objective

To determine whether an elevated hepatic steatosis index (HSI), a non-invasive test for possible metabolic dysfunction-associated fatty liver disease (MAFLD), is associated with the development of adverse pregnancy outcomes.

Material and Methods

A retrospective cohort study was conducted on adult women with singleton pregnancies who delivered at two tertiary hospitals from August 2014 to December 2017. Aspartate aminotransaminase (AST) and alanine aminotransaminase (ALT) levels obtained 12 months pre-gravid, or during pregnancy but prior to screening for gestational diabetes mellitus (GDM), were extracted and linked with oral glucose tolerance test results. The HSI was calculated using the following equation: 8 × (ALT/AST ratio) + BMI (+2 if female; +2 if diabetes mellitus present) and considered elevated if >36. Multiple logistic regression analysis was used to quantify the association between elevated HSI and each composite adverse pregnancy outcome after adjusting for independent maternal risk factors.

Results

Over 40-months, 11929 women were eligible and of these, 1885 had liver enzymes collected. Women with an elevated HSI (>36) were more likely multiparous and overweight/obese compared to those women with a non-elevated HSI (≤36). Elevated HSI was significantly associated with a composite of adverse maternal outcomes (adjusted odds ratio (aOR) 1.55 95% CI 1.11-2.17, p=0.01), although a non-significant increased risk of a composite of adverse neonatal outcomes occurred after multivariable adjustment (aOR 1.17, 95% CI 0.94-1.45, p=0.17).

Conclusion

Over and above known maternal risk factors, women with elevated HSI were more likely to develop adverse maternal, but not adverse neonatal outcomes.

Management of obesity across women's life course: FIGO Best Practice Advice

Obesity is a chronic, progressive, relapsing, and treatable multifactorial, neurobehavioral disease. According to the World Health Organization, obesity affects 15% of women and has long-term effects on women's health. The focus of care in patients with obesity should be on optimizing health outcomes rather than on weight loss. Appropriate and common language, considering cultural sensitivity and trauma-informed care, is needed to discuss obesity. Pregnancy is a time of significant physiological change. Pre-, ante-, and postpartum clinical encounters provide opportunities for health optimization for parents with obesity in terms of, but not limited to, fertility and breastfeeding. Pre-existing conditions may also be identified and managed. Beyond pregnancy, women with obesity are at an increased risk for gastrointestinal and liver diseases, impaired kidney function, obstructive sleep apnea, and venous thromboembolism. Gynecological and reproductive health of women living with obesity cannot be dismissed, with accommodations needed for preventive health screenings and consideration of increased risk for gynecologic malignancies. Mental wellness, specifically depression, should be screened and managed appropriately. Obesity is a complex condition and is increasing in prevalence with failure of public health interventions to achieve significant decrease. Future research efforts should focus on interprofessional care and discovering effective interventions for health optimization.

Diagnostic ability using fatty liver and metabolic markers for metabolic-associated fatty liver disease stratified by metabolic/glycemic abnormalities

AIMS/INTRODUCTION

Although several noninvasive predictive markers for fatty liver and metabolic markers have been used for fatty liver prediction, whether such markers can also predict metabolic-associated fatty liver disease (MAFLD) remains unclear. We aimed to examine the ability of existing fatty liver or metabolic markers to predict MAFLD.

MATERIALS AND METHODS

Participants in a high-volume center in Tokyo were classified into groups with and without MAFLD, based on the presence of metabolic abnormalities and fatty liver diagnosed through abdominal ultrasonography, between 2008 and 2018. The diagnostic abilities of three fatty liver markers: fatty liver index (FLI), hepatic steatosis index (HSI), and lipid accumulation product (LAP), and three common metabolic markers: waist-to-height ratio (WHR), body mass index (BMI), and waist circumference (WC), for predicting MAFLD, were evaluated. Analyses stratified by MAFLD subtypes were performed.

RESULTS

Of 92,374 individuals, 19,392 (36.1%) had MAFLD. The diagnostic performances for MAFLD prediction, measured as c-statistics, for FLI, HSI, LAP, WHR, BMI, and WC were 0.906, 0.892, 0.878, 0.844, 0.877, and 0.878, respectively. Optimal cutoff values for diagnosing MAFLD for FLI, HSI, LAP, WHR, BMI, and WC were 20.3, 32.7, 20.0, 0.49, 22.9, and 82.1, respectively. Analyses stratified by MAFLD subtypes, based on BMI and metabolic/glycemic abnormalities, suggested that FLI and HSI had acceptable (c-statistics >0.700) diagnostic abilities throughout all the analyses.

CONCLUSIONS

All six markers were excellent predictors of MAFLD in diagnosing among the general population, with FLI and HSI particularly useful among all sub-populations.

TyGIS: improved triglyceride-glucose index for the assessment of insulin sensitivity during pregnancy

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.

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study

Purpose

In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM).

Methods

To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over the established risk factors using the C-statistic, the IDI, and the NRI.

Results

During a median follow-up period of 2.97 years, 433 (1.97%) participants developed new-onset T2DM. The smoothing curve fit plot showed a positive correlation between HSI and the risk of T2DM. After adjusting for all noncollinear variables, the risk of T2DM increased by 62% for every 1 standard deviation (SD) increase in HSI. Subgroup analysis indicated that higher HSI levels were associated with a higher risk of T2DM in those aged < 40 years. The addition of HSI enhanced the reclassification and discrimination of established risk factors, with an IDI of 0.027 and an NRI of 0.348 (both P < 0.001).

Conclusion

Our findings suggest that an elevated HSI is substantially associated with a greater risk of T2DM in the Chinese population. HSI has the potential to be an available and supplementary monitoring method for the management of T2DM risk stratification in the Chinese population.