Longitudinal trends in lipid profiles during pregnancy: Association with gestational diabetes mellitus and longitudinal trends in insulin indices

Association between triglycerides and lumbar bone mineral density in Chinese patients with osteoporotic fractures: a retrospective cross-sectional study

The association between lumbar bone mineral density (BMD) and triglyceride (TG) levels has been extensively studied; however, the results remain controversial. Therefore, this research aimed to elucidate the association of TG levels with lumbar BMD in patients with osteoporotic fractures (OPFs) who have undergone surgery. This cross-sectional study analyzed 3,558 OPF patients (aged 50 years and above) who were admitted to the First People's Hospital of Kunshan and assessed their TG levels, lumbar BMD, and other variables. The outcome variable of this research was bone density, whereas the baseline glycerol trihydrate levels were considered as the exposure variable. An analysis adjustment was conducted for various covariates, including age, gender, body mass index (BMI), and other baseline laboratory and clinical results. Furthermore, the potential non-linear relationships were assessed via the smooth curve fitting, and threshold effect analyses. The mean age of 3,558 included OPF patients was 68.87 ± 10.55 years. In the fully adjusted multivariate regression analysis, a positive correlation was found between TG levels and lumbar BMD (β = 0.015, 95% CI: 0.001-0.028, p = 0.033). Furthermore, the threshold effect analysis revealed a curvilinear relationship between TG levels and lumbar BMD, with a turning point at 1.26 mmol/L. Moreover, on both sides of the turning point, different patterns were observed. On the left side, TG levels were positively correlated with lumbar BMD. However, despite higher TG levels, the differences in lumbar BMD on the right side of the turning point, were not statistically significant, indicating a lack of significant association (p = 0.712). In summary, this research indicated that in OPF patients, higher TG levels were significantly positively associated with lumbar BMD. Furthermore, there was a threshold value of 1.26 mmol/L, indicating that TG levels in OPF patients with concomitant hypertriglyceridemia should be maintained within the normal range, and reducing TG levels below 1.26 mmol/L requires continuous monitoring. This approach effectively controls TG levels without adversely impacting lumbar BMD.

Lipid profile in women of different ethnicity with gestational diabetes: Relationship with fetal growth

AIMS/INTRODUCTION

Pregnancy complicated by gestational diabetes mellitus (GDM) is characterized by excessive insulin resistance that impairs the metabolism of glucose and lipids. the aim of the study was to examine lipid profiles during pregnancy of women with GDM, and its impact on fetal growth in a multiethnic population.

MATERIALS AND METHODS

The study included 322 pregnant women of different ethnicity with GDM attending a clinical unit specializing in metabolic diseases.

RESULTS

The area under the curve for the 75-g oral glucose tolerance test and glycated hemoglobin were significantly different among all groups. At the time of being diagnosed with GDM, Asian and African mothers had significantly lower levels of total and low-density liprotein cholesterol than European mothers (P < 0.001). The trend for high-density liprotein cholesterol was similar. Triglycerides levels in the Asian group (193.6 ± 65.5 mg/dL) were higher than in the African group (133.2 ± 49.6 mg/dL, P < 0.001), whereas the European group presented intermediate values (175.8 ± 58.8 mg/dL), which differed significantly only versus the African group (P < 0.001). Pre-partum lipid profiles showed a trend quite similar to that observed at diagnosis. The newborn's birthweight was significantly different, with that of African women (3,437 ± 503 g) being the highest, followed by that of European women (3,294 ± 455 g) and of Asian women (3,006 ± 513 g). The rates of macrosomia showed a trend with higher values in the African group (13.5%), followed by the European group (5.7%, P = 0.1162), whereas that of the Asian group was zero (P = 0.0023 vs African).

CONCLUSIONS

Our data show that lipid profiles in women with GDM differ by ethnicity. The impact of lipid profile on fetal growth is limited and uninfluenced by ethnicity.

Establishment and evaluation of a risk prediction model for gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is a condition characterized by high blood sugar levels during pregnancy. The prevalence of GDM is on the rise globally, and this trend is particularly evident in China, which has emerged as a significant issue impacting the well-being of expectant mothers and their fetuses. Identifying and addressing GDM in a timely manner is crucial for maintaining the health of both expectant mothers and their developing fetuses. Therefore, this study aims to establish a risk prediction model for GDM and explore the effects of serum ferritin, blood glucose, and body mass index (BMI) on the occurrence of GDM.

AIM

To develop a risk prediction model to analyze factors leading to GDM, and evaluate its efficiency for early prevention.

METHODS

The clinical data of 406 pregnant women who underwent routine prenatal examination in Fujian Maternity and Child Health Hospital from April 2020 to December 2022 were retrospectively analyzed. According to whether GDM occurred, they were divided into two groups to analyze the related factors affecting GDM. Then, according to the weight of the relevant risk factors, the training set and the verification set were divided at a ratio of 7:3. Subsequently, a risk prediction model was established using logistic regression and random forest models, and the model was evaluated and verified.

RESULTS

Pre-pregnancy BMI, previous history of GDM or macrosomia, hypertension, hemoglobin (Hb) level, triglyceride level, family history of diabetes, serum ferritin, and fasting blood glucose levels during early pregnancy were de-termined. These factors were found to have a significant impact on the development of GDM (P < 0.05). According to the nomogram model's prediction of GDM in pregnancy, the area under the curve (AUC) was determined to be 0.883 [95% confidence interval (CI): 0.846-0.921], and the sensitivity and specificity were 74.1% and 87.6%, respectively. The top five variables in the random forest model for predicting the occurrence of GDM were serum ferritin, fasting blood glucose in early pregnancy, pre-pregnancy BMI, Hb level and triglyceride level. The random forest model achieved an AUC of 0.950 (95%CI: 0.927-0.973), the sensitivity was 84.8%, and the specificity was 91.4%. The Delong test showed that the AUC value of the random forest model was higher than that of the decision tree model (P < 0.05).

CONCLUSION

The random forest model is superior to the nomogram model in predicting the risk of GDM. This method is helpful for early diagnosis and appropriate intervention of GDM.