Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy最新文献

This article discusses innovations, advancements, and discoveries in continuous glucose monitoring (CGM) that were presented at the European Association for the Study of Diabetes 2024 Conference in Madrid, Spain, held in September 2024. Specifically, the author will discuss data from studies that discuss the impact of CGM on hemoglobin A1C in people with type 2 diabetes; the impact of CGM use in hospitalization settings for people with diabetes; the effectiveness of CGM in those who have undergone cardiac surgery; the efficacy of real-time CGM in adults hospitalized with diabetic ketoacidosis; time in rage in older individuals; and new devices for glucose sensing.

Background: The association between lipoprotein(a) (Lp(a)) and sarcopenia in T2DM patients of general age is unclear, and whether this association differs by sex remains uncertain. We intend to analyze the association between Lp(a) and sarcopenia in patients with type 2 diabetes mellitus (T2DM) and whether this association differs by sex.

Methods: T2DM patients between December 2021 and December 2022 were consecutively enrolled. Sarcopenia was defined according to the criteria of Consensus of the Asian Working Group for Sarcopenia (AWGS) 2019.A multivariable logistic regression model was used to calculate the odds ratio of Lp(a)≥30 mg/dL for sarcopenia in total T2DM patients and in all sexes. Restricted cubic splines were also used to evaluate the association between Lp(a) and sarcopenia.

Results: Among the 426 patients, the mean age was 58.6 years and 56.3% were males. The prevalence of sarcopenia was 31.7% in total patients, 34.2% in male and 28.5% in female. The percentages of Lp(a)≥30 mg/dL were 19.0% in total patients. Compared with patients in Lp(a)<30 mg/dL group, those in Lp(a)≥30 mg/dL group showed an increased risk of sarcopenia (adjusted odds ratio [aOR]: 2.19, 95% CI: 1.09 to 4.39, p = 0.027). Results from restricted cubic splines were robust. When analyzing each sex, there was also a significant association between Lp(a)≥30 mg/dL and sarcopenia (male: aOR: 2.59, 95% CI: 1.09 to 6.21, p = 0.032; female: aOR: 2.45, 95% CI: 1.06 to 6.03, p = 0.039).

Conclusion: In T2DM patients, elevated Lp(a) was associated with an increased risk of sarcopenia and such an association did not differ by sex. Screening for sarcopenia should be emphasized in T2DM patients with Lp(a)≥30 mg/dL, both men and women.

Background: Aging diabetic patients have an increased incidence of hypoglycemia due to long disease history, multiple medications, and other factors. The higher the frequency of hypoglycemia, the greater the fear of it, and the heavier the psychological burden. This fear can have a significant negative impact on the patient's personal psychological distress related to the disease, self-care, and the quality of life of other family members. Therefore, analyzing the factors contributing to the fear of hypoglycemia is crucial for finding effective ways to overcome them.

Objective: To analyze the correlation between hypoglycemic fear (FOH), psychological well-being, and family support function in older adults patients with diabetes mellitus (DM).

Methods: Seventy-eight older adults patients with DM were recruited from the community for the study. The Chinese version of the hypoglycemia fear survey scale (CHFSII-WS), WHO-5 happiness index scale and family support function scale were used to analyze the influencing factors of FOH in older adults DM patients to clarify the correlation between FOH, psychological well-being, and family support function.

Results: Low academic qualification, long course of disease, the frequency of hypoglycemia episodes > 2 in the last one year were the risk factor for FOH in older adults DM patients, and hypoglycemia prevention education, psychological well-being and family support function were protective factors. Family support function had a mediating effect.

Conclusion: Older adults patients with DM have higher levels of FOH, which has many influencing factors, and family support function has an obvious mediating effect between FOH and psychological well-being. High-intensity FOH can be improved by actively developing hypoglycemia prevention education for patients and caregivers and improving family support function and psychological well-being.

Purpose: This study aims to explore the relationship between BMI and chronic inflammation and to investigate the interaction and mediation of physical activity (PA), cardiopulmonary function, and visfatin.

Methods: A total of 119 participants were included in the study, 60 in the obesity group, 30 in the normal weight group, and 29 in the overweight group. PA, VO_2max, visfatin, high-sensitivity C-reactive protein (hs-CRP), and four blood lipid indices (TC, TG, HDLC, LDLC) were analyzed. Regression analysis was used to understand the effect of BMI on chronic inflammation. Covariate analysis was conducted to screen effective covariates affecting BMI to predict chronic inflammation and test the interaction and intermediary role of effective covariates.

Results: The increase in BMI could aggravate chronic inflammation. PA, VO_2max, and visfatin had interactive effects on BMI affecting chronic inflammation, and visfatin played an intermediary role in BMI affecting chronic inflammation. The effect value of BMI on chronic inflammation in terms of low PA was 3.5 times higher than that of high PA, that of low VO_2max was 2.8 times higher than that of high VO_2max, and that of high visfatin was 3.65 times higher than that of low visfatin. Approximately 19.35% of the effect was mediated by visfatin.

Conclusion: An increase in BMI can aggravate chronic inflammation. Increases in PA and VO_2max can alleviate chronic inflammation, and visfatin plays a positive mediating role.

Introduction: Diabetes is a significant public health concern worldwide, having increased rapidly in recent decades among younger generations. The correlation between metabolic/obesity phenotypes and the development of pre-diabetes in children and adolescents remains unclear.

Methods: This study aimed to explore this association within a cohort of 1,524 subjects aged 7 to 18 years. Subjects were categorized into four groups based on their metabolic and obesity status: Metabolically Unhealthy with Normal Body Weight (MUNW), Metabolically Healthy Overweight/Obesity (MHO), Metabolic Healthy with Normal Body Weight (MHNW), and Metabolically Unhealthy Overweight/Obesity (MUO). Physical parameters such as body mass, as well as biochemical markers including blood pressure, fasting glucose, triglycerides, and high-density lipoprotein cholesterol, were measured.

Results: A total of 61.9% of children were within the normal range for both body weight and metabolism (MHNW), while 24.4% were classified as MUNW, 5.7% as MHO, and 8% as MUO. The risks of diabetes in the MUNW and MUO groups were 8.89 and 9.18 times higher than in the MHNW group for boys, and 8.15 and 11.24 times higher for girls (P<0.05).

Conclusion: These findings suggest that abnormal metabolism, irrespective of body weight, significantly increases the risk of diabetes, while obesity alone does not predict pre-diabetes unless accompanied by metabolic dysregulation. Metabolic markers may serve as more sensitive indicators for assessing diabetes risk in this population.

Objective: To investigate changes in cardiometabolic risk factors after completion of cardiac rehabilitation (CR) for coronary heart disease (CHD) and ascertain whether the magnitude of improvement in cardiometabolic health differs between those with and without metabolic syndrome (MetS).

Methods: In this observational cohort study, data were analyzed from 1984 patients enrolled in CR at the University of Michigan between 2011-01-01 and 2020-02-29 for the indication of CHD. Patient characteristics were collected from standardized health questionnaires and during CR intake evaluations. Cardiometabolic biomarkers were recorded from baseline laboratory data and re-examined upon completion of CR. Differences in baseline patient characteristics by MetS status were compared using chi-square tests. Wilcoxon rank-sum tests were used to compare baseline differences, and signed-rank tests were used to evaluate the change in variables between baseline and completion of CR. The difference of change by MetS status was assessed using difference-in-differences regression models.

Results: Of the 1984 patients, 1070 (53.9%) met the criteria for MetS at baseline, of which 770 were male (72.0%). Those with MetS lost 1.43 pounds more (95% CI: 0.56, 2.31, P = 0.001), experienced a 0.21 larger drop in body mass index (95% CI: 0.03, 0.37, P = 0.02), and had a 0.31 greater reduction in waist circumference (95% CI: 0.08, 0.54, P = 0.008). Difference-in-differences regression models revealed those with MetS experienced a greater reduction in triglycerides and fasting glucose, with a difference of change of -8.70 for triglycerides (95% CI: -15.04, -2.37, P = 0.007) and -5.48 for glucose (95% CI: -10.44, -0.53, P = 0.03). There was no significant difference in the change in HDL-C or LDL-C for MetS status.

Conclusion: Compared to those without MetS, patients with MetS experienced a comparable or greater benefit from CR, particularly with respect to improvements in MetS components.

Hyperinsulinemic Hypoglycemia (HH) is a rare condition that affects newborn children in the postnatal period, represented by dangerously low levels of blood glucose in a persistent manner, which puts the baby at high risk of multiple issues, especially regarding the brain cells if the baby does not take the appropriate medication or have the correct diagnosis. Hyperinsulinemic Hypoglycemia can happen due to an active or inactive mutation in 16 genes responsible for glucose metabolism and insulin secretion (GLUD1, GCK, SLC16A1, HK1, CACNA1D, KCNJ11, ABCC8, FOXA2, HNF1A, HNF4A, HADH, PGM1, UCP2, KCNQ1, PMM2, EIF2S3). These mutations can take place in many forms, either defused or local, affecting several or all pancreatic beta cells respectively. This review summarizes genetic variations diagnosis and treatment of Hyperinsulinemic Hypoglycemia.

Purpose: To explore the correlation between fasting C-peptide to diabetes duration ratio (FCP/DD) and diabetic peripheral neuropathy (DPN).

Methods: The study was conducted on 816 patients with type 2 diabetes (T2DM). Subjects were classified into a diabetic peripheral neuropathy group (DPN, n=408) and a non-diabetic peripheral neuropathy group (NDPN, n=408) depending on the presence of DPN. Collected patients' baseline data, calculated the FCP/DD ratio, and analyzed the correlation between FCP/DD and DPN.

Results: A comparative analysis of general characteristics revealed that the DPN group exhibited higher values for age, DD, proportion of hypertension, proportion of DN, and proportion of DR compared to the NDPN group, Conversely, the DPN group demonstrated lower proportions of eGFR, FCP/DD, FCP, and fatty liver relative to the NDPN group, with all differences achieving statistical significance (P < 0.05). Compared to the high FCP/DD group, the low FCP/DD group exhibited higher values in age, DD, the proportion of DPN, DN, DR, and hypertension, as well as elevated levels of HDL-C and NEUT (P<0.05). Conversely, the low FCP/DD group demonstrated a lower proportion of patients who smoked and those with fatty liver, along with reduced BMI, ALB, FBG, UA, eGFR, TC, TG, and LDL-C levels (P < 0.05). In patients with T2DM, after adjusting for confounding factors, high levels of FCP/DD were found to be a protective factor for DPN (P < 0.05). The area under the curve of the FCP/DD Model predicting DPN (AUC=0.737) was higher than that of single FCP (AUC=0.587), DD (AUC=0.665).

Conclusion: The high FCP/DD ratio was a protective factor for T2DM with DPN. Additionally, the FCP/DD ratio was found to be a better predictor for the occurrence of DPN in T2DM compared to FCP and DD alone.

Background: Functional defects caused by mutations in the insulin receptor (INSR) gene often lead to severe hereditary insulin resistance syndromes, including but not limited to type A insulin resistance syndrome.

Method and result: Here, we report a case of a 12-year-old girl with elevated fasting blood glucose detected by opportunistic testing, associated with severe insulin resistance and hyperandrogenemia. She had axillary hair, acne, clitoral hypertrophy, prominent labia minora hypertrophy and thickened voice with BMI 20.57kg/m², and ultrasound imaging showed that she had multiple follicles in both ovaries. Insulin was initially administered, but the glycemic control was poor. Accordingly, the prescription was later switched to metformin, maintaining euglycemic blood glucose level. The whole exome sequencing from peripheral blood revealed that the patient carries NM_000208.2:c.1225_1227delTTC (p.Phe409del) heterozygous mutation in the INSR gene. She was tentatively diagnosed as type A insulin resistance syndrome based on her clinical features and heterozygous mutation in the INSR gene.

Conclusion: Our results demonstrated that type A insulin resistance syndrome in patients presenting with severe insulin resistance and hyperandrogenemia was associated with a heterozygous variant of c.1225_1227delTTC (p.Phe409del), suggesting that exon sequencing would be beneficial to detect the potential mutations in the INSR gene of these patients for precise diagnosis and intervention in clinical practice.

Objective: This study aimed to systematically review the existing research on risk prediction models for mild cognitive impairment in patients with type 2 diabetes mellitus and to analyze the predictive performance of these models.

Methods: A systematic computerized search was conducted for studies published in CNKI, Wanfang, VIP, CBM, PubMed, Embase, Cochrane Library, CINAHL, and Web of Science regarding risk prediction models for mild cognitive impairment in patients with type 2 diabetes mellitus, covering the period the inception of the databases through November 10, 2024. Two independent reviewers performed literature screening and data extraction based on predefined inclusion and exclusion criteria. The risk of bias and the applicability of the included studies were subsequently evaluated using the Risk of Bias Assessment Tool for Prediction Models. A meta-analysis of the predictive performance of the models was performed using Stata 17.0 software.

Results: A total of 12 studies and 17 prediction models were included in the analysis, with the area under the receiver operating characteristic curve (AUC) for the models ranging from 0.743 to 0.987. All studies were assessed to be at high risk of bias, particularly concerning the issue of underreporting in the area of data analysis. The combined AUC value of the six validated models was 0.854, indicating that these models exhibited favorable predictive performance. The multivariate models consistently identified age, education, disease duration, depression, and glycosylated hemoglobin level as independent predictors.

Conclusion: The development of risk prediction models for mild cognitive impairment in patients with type 2 diabetes mellitus is still in its infancy. In order to develop more accurate and practical risk prediction models for mild cognitive impairment in patients with type 2 diabetes mellitus, future studies must rely on large-sample, multicenter prospective cohorts and adhere to rigorous study designs.