Highlights
Highlights
Traditional fixed thresholds for oral glucose tolerance test (OGTT) results may inadequately prevent adverse pregnancy outcomes in twin pregnancies. This study explores latent OGTT patterns and their association with adverse outcomes.
This study retrospectively analyzed 2644 twin pregnancies using latent mixture models to identify glucose level patterns (high, HG; medium, MG; and low, LG) and their relationship with maternal/neonatal characteristics, gestational age at delivery, and adverse outcomes.
Three distinct glucose patterns, HG, MG, and LG patterns were identified. Among the participants, 16.3% were categorized in the HG pattern. After adjustment, compared with the LG pattern, the HG pattern was associated with a 1.79-fold, 1.66-fold, and 1.32-fold increased risk of stillbirth, neonatal respiratory distress, and neonatal hyperbilirubinemia, respectively. The risk of neonatal ICU admission for MG and HG patterns increased by 1.22 times and 1.32 times, respectively, compared with the LG pattern. As gestational weeks increase, although there is an overlap in the confidence intervals between the HG pattern and other patterns in the restricted cubic splines analysis, the trend suggests that pregnant women with the HG pattern are more likely to face risks of their newborns requiring neonatal intensive care unit admission, and adverse comprehensive outcomes, compared with other patterns. In addition, with age and body mass index increasing in HG mode, gestation weeks at delivery tend to be later than in other modes.
Distinct OGTT glucose patterns in twin pregnancies correlate with different risks of adverse perinatal outcomes. The HG pattern warrants closer glucose monitoring and targeted intervention.
The composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi-omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels.
We conducted a multi-omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids.
The linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of Bacteroides_nordii, Bacteroides_cellulosilyticus in the glycemic control (GC) group, while Bacteroides_coprocola and Sutterella_wadsworthensis were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. Bacteroides_nordii exhibited a negative association with D-fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway.
We identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (Bacteroides_nordii, Bacteroides_coprocola), metabolites (D-fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.
Du et al.1 conducted a prospective study to investigate the effect of healthy sleep pattern on subsequent mortality risk of acute myocardial infarction (AMI) in people with diabetes. The adjusted hazard ratio (HR) (95% confidence interval [CI]) of healthy sleep score for AMI mortality was 0.87 (0.77–0.98). Especially, adequate sleep duration reduced 29% risk of AMI mortality. They finally mentioned that types of diabetes should be stratified for the analysis, and I think that interactions of diabetes on the inverse association between healthy sleep score and AMI mortality may be existed. In their Figure 1, there is a wide range of HR for the risk of AMI mortality in lower healthy sleep score, which did not reach a significant level. There is a possibility that people with lower healthy sleep score would have several cardiometabolic risk factors, and contribution rate of sleep variables to the risk of AMI would become smaller. I speculate that irregular sleep pattern in daily life reflects one of the unhealthy lifestyles, and it would contribute to diabetes and AMI risk. I present recent reports on the association between irregular sleep and subsequent risk of type 2 diabetes (T2D) or cardiometabolic disorder.
Zuraikat et al.2 defined irregular sleep pattern as the standard deviation of each sleep parameter, and it was closely related to the increased risk of T2D and cardiometabolic risk. Although causal association cannot be determined, irregular sleep pattern may contribute to the risk of several metabolic disorders.
Liu et al.3 conducted a meta-analysis on the relationship between daytime napping and incident diabetes, and longer period of napping should be avoided to reduce a risk of diabetes. I suppose that long napping would affect nighttime sleep depth and duration, which may also relate to irregular sleep pattern.
Zhang and Qin4 reported the potential mechanisms regarding the effect of irregular sleep pattern on subsequent cardiometabolic risk, including circadian dysfunction, inflammation, autonomic dysfunction, endocrinological disorder, and gut dysbiosis. Glucose metabolism may be affected by unstable sleep–wake cycle and their duration, which would be closely related to the level of physical activity and nutritional intake.
Finally, Zhu et al.5 reviewed and concluded that sleep variability was significantly associated with weight gain and increased hemoglobin A1c, although decreased insulin sensitivity was not consistent findings in several studies.
There is no financial support for this study.
The author declares that he has no competing interests. No ethical statement is needed for this study.
It is known that the risk of ischemic heart disease increases in patients with type 2 diabetes mellitus (T2DM). For female patients, the incidence of heart disease can be even greater after menopause, accompanied by dramatic changes in sex hormones. We investigated the correlations between sex hormones and markers of ischemic heart diseases in postmenopausal females with T2DM patients.
This cross-sectional study collected data from 324 hospitalized postmenopausal females with T2DM. Multiple linear regression analyses were conducted to determine the correlations between sex hormones and cardiac markers including high-sensitive cardiac troponin T (hs-cTnT) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) levels.
Multiple linear regression analyses revealed that luteinizing hormone (LH) was positively and independently associated with hs-cTnT concentrations in postmenopausal females with T2DM (β = 0.189, p = 0.002). Postmenopausal females with T2DM and subclinical myocardial injury had higher LH levels than those without subclinical myocardial injury (29.67 vs. 25.08 mIU/mL, p < 0.001). A multivariate logistic regression analysis confirmed an independent and significant association between elevated LH and subclinical myocardial injury in postmenopausal females with T2DM (adjusted odds ratio [OR] = 1.077, 95% confidence interval [CI], 1.033–1.124; p < 0.001). As another gonadotropin, the follicle-stimulating hormone did not show independent correlations with hs-cTnT or NT-proBNP (p > 0.05). Neither estrogen nor testosterone was correlated with cardiac markers.
Elevated LH levels were positively and independently associated with increased hs-cTnT levels in postmenopausal women with T2DM. Our findings suggest that LH could serve as a potential marker for assessing the risk of subclinical myocardial injury in postmenopausal females with T2DM.
The global prevalence of diabetes has increased significantly, leading to various complications and a negative impact on quality of life. Hyperglycemia hyperglycemic-induced oxidative stress (OS) and inflammation are closely associated with the development and progression of type 2 diabetes mellitus (T2D) and its complications. This review explores the effect of T2D on target organ damage and potential treatments to minimize this damage. The paper examines the pathophysiology of T2D, focusing on low-grade chronic inflammation and OS and on their impact on insulin resistance. The review discusses the role of inflammation and OS in the development of microvascular and macrovascular complications. The findings highlight the mechanisms by which inflammatory cytokines, stress kinases, and reactive oxygen species (ROS) interfere with insulin signaling pathways, leading to impaired glucose metabolism and organ dysfunction. Lifestyle interventions, including a balanced diet and exercise, can help reduce chronic inflammation and OS, thereby preventing and controlling T2D and its associated complications. Additionally, various antioxidants and anti-inflammatory agents show potential in reducing OS and inflammation. Some anti-diabetic drugs, like pioglitazone, metformin, and glucagon-like peptide-1 (GLP-1) agonists, may also have anti-inflammatory effects. Further research, including randomized controlled trials, is needed to evaluate the efficacy of these interventions.
The objective of this study was to evaluate the impact of dysglycemia on perioperative outcomes, in patients with and without diabetes, and how prior glycemic control modifies these relationships.
Consecutive surgical patients admitted to six South Australian tertiary hospitals between 2017 and 2023 were included. Blood glucose levels within 48 h pre- and post-operatively were assessed in an adjusted analyses against a priori selected covariates. Dysglycemia metrics were hyperglycemia (>10.0 mmol/L), hypoglycemia (<4.0 mmol/L), glycemic variability (standard deviation of mean blood glucose >1.7 mmol/L), and stress hyperglycemic ratio (SHR). The primary outcome was hospital mortality.
Of 52 145 patients, 7490 (14.4%) had recognized diabetes. Inpatient mortality was observed in 787 patients (1.5%), of which 150 (19.1%) had diabetes mellitus. Hyperglycemia was associated with increased mortality in patients with diabetes (odds ratio [OR] = 2.99, 95% CI: 1.63–5.67, p = 0.004) but not in non-diabetics, who instead had an increased odds of intensive care unit (ICU) admission if hyperglycemic (OR = 1.95, 95% CI: 1.40–2.72, p < 0.0001). Glycemic variability was associated with increased mortality in patients with diabetes (OR = 1.46, 95% CI: 1.05–2.01, p < 0.05) but not in non-diabetics. Preoperative glycemic control (HbA1c) attenuated both of these associations in a dose-dependent fashion. Hypoglycemia was associated with increased mortality in non-diabetics (OR = 2.14, 95% CI: 1.92–2.37, p < 0.001) but not in patients with diabetes.
In surgical patients with diabetes, prior exposure to hyperglycemia attenuates the impact of perioperative hyperglycemia and glycemic variability on inpatient mortality and ICU admission. In patients without diabetes mellitus, all absolute thresholds of dysglycemia are associated with ICU admission, unlike those with diabetes, suggesting the need to use more relative measures such as the SHR.
Foot ulcers are a major complication of diabetes mellitus that increase morbidity and mortality in patients with diabetes, affect their quality of life, and increase the overall social burden. A considerable number of patients with diabetic foot ulcers (DFUs) require amputations every year.
This nation population–based study included 1 923 483 patients with diabetes who underwent regular health screening through the National Health Insurance Service during January 2009 and December 2012. We investigated the association between changes in physical activity (PA) status and the incidence of lower extremity amputation (LEA). Based on changes in PA status, participants were categorized into four groups: “remained inactive,” “remained active,” “active-to-inactive,” and “inactive-to-active.”
Regular PA is an independent factor associated with a decreased risk of LEA in patients with diabetes. During the follow-up period, 0.23% (n = 4454) of the patients underwent LEA. Compared with the “remained inactive” group, the “remained active” group were at the lowest risk of LEA (adjusted hazard ratio 0.5888; 95% confidence interval 0.524–0.66). A protective effect of regular PA against LEA was observed in the “remaining active” group.
Our findings suggest a protective role of PA against LEA in individuals with diabetes. This highlights the importance of recommending appropriate levels of PA for patients with diabetes. The study also showed a dose–response relationship, indicating that engaging in vigorous-intensity PA was most beneficial, and higher amounts of PA may provide additional benefits.
Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), a class of injectable antidiabetic drugs, have shown significant efficacies in improving glycemic and weight control in patients with type 2 diabetes (T2D). However, the long-term safety of GLP-1 RAs remains insufficiently studied. This study aimed to provide real-world evidence on potential adverse outcomes associated with GLP-1 RAs use in T2D patients without major chronic diseases including impaired cardiac or renal function.
We conducted a retrospective cohort study involving 7746 T2D patients on GLP-1 RAs in Shenzhen, China. They were compared with 124 371 metformin-only users and 36 146 insulin-only users, forming two therapy control groups. GLP-1 RAs users were also further 1:2 paired with the control groups. Competing risk survival analyses were conducted to assess the incidence risks, presenting subdistributional hazard ratios (sHRs) with 95% confidence intervals (CIs) for various adverse outcomes associated with GLP-1 RAs use.
Compared with metformin-only users, GLP-1 RAs use was associated with increased risks of various adverse outcomes (sHRs with 95% CIs), including pancreatitis (2.01, 1.24–3.24), acute nephritis (3.20, 2.17–4.70), kidney failure (3.73, 2.74–5.08), thyroid cancer (2.25, 1.23–4.10), and thyroid dysfunction (1.27, 1.00–1.63), respectively; Similar results were also found when compared with insulin-only users. Importantly, long-term (≥12 months) GLP-1 RAs use may further elevate the incidence risks of pancreatitis, acute nephritis, thyroid cancer, and thyroid dysfunction.
Compared with traditional T2D treatments, GLP-1 RAs use may be associated with increased risks of various adverse outcomes in a Chinese population. Cautions were strongly warranted in the use of GLP-1 RAs. Further validation is crucial across diverse populations.
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