Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be \'objective\' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

We hypothesized that the triglyceride-glucose (TyG)-alanine aminotransferase (ALT) index, which combines the TyG index with ALT, may enhance sensitivity and specificity in detecting the severity of nonalcoholic fatty liver disease (NAFLD). A total of 131 NAFLD patients with a mean age of 11.5 ± 2.29 years were enrolled, and severity was assessed by ultrasound fatty liver index (US-FLI) scoring. The TyG-ALT index was defined as ln(fasting triglyceride [mg/dL] × fasting glucose [mg/dL] × ALT [IU/L]/2). Multiple linear regression analysis revealed a significant association between the TyG-ALT index and US-FLI (β = 0.317, P < .001) after controlling for sex, age, and body mass index. The TyG-ALT index showed a more stable and superior ability to detect the severity of NAFLD compared to both ALT and the TyG index. The area under the curve values, listed in the order of ALT, TyG index, and TyG-ALT index, were as follows: 0.737 (P < .001), 0.599 (P = .055), and 0.704 (P < .001) at US-FLI ≥ 4 points; 0.717 (P < .001), 0.720 (P < .001), and 0.775 (P < .001) at US-FLI ≥ 5 points; and 0.689 (P < .05), 0.748 (P < .01), and 0.775 (P < .001) at US-FLI ≥ 6 points. The TyG-ALT index is associated with US-FLI score and superior to both ALT and the TyG index in predicting NAFLD severity. These findings indicate the potential of the TyG-ALT index in the management of pediatric NAFLD progression.

UNASSIGNED: The triglyceride-glucose (TyG) index is a sign of atherosclerosis in cardiovascular diseases. The TyG index is thought to have clinical significance for the assessment of vascular damage. In this study we aimed to demonstrate the connection between the TyG index and retinal vein occlusion (RVO).
UNASSIGNED: This case-control observational study involved 492 participants aged 40-90, admitted to the ophthalmology outpatient clinic of our hospital. TyG index was calculated using the formula: ln(fasting TG [mg/dL] × fasting plasma glucose [mg/dL]/2).
UNASSIGNED: The RVO group included 387 patients (181 women and 206 men) and the control group included 115 patients (61 women and 54 men). The average patient age was 62.9±11.1 years in the RVO group and 56.7±8.7 years in the control group. The TyG index was higher in the RVO group (8.9±0.7) than in the control group (8.8±0.6). This difference was statistically significant (p=0.04). The correlation was statistically significant when evaluated according to age and sex by multivariate logistic regression analysis (odds ratio: 1.45, confidence interval: 1.03- 2.02, p=0.03).
UNASSIGNED: The TyG index is a novel atherogenicity index that is derived from routine blood tests and can be used to determine the risk of RVO in at-risk individuals with a simple calculation. Therefore, the TyG index could help as a reliable guide to identify individuals at RVO with high risk and initiate early intervention.

Type 1 diabetes mellitus (T1DM) is the most severe form of diabetes, which is characterized by absolute insulin deficiency induced by the destruction of pancreatic beta cells. The aim of this study was to evaluate the effect of a structural analogue of apelin-12 ((NαMe)Arg-Pro-Arg-Leu-Ser-His-Lys-Gly-Pro-Nle-Pro-Phe-OH, metilin) on hyperglycemia, mitochondrial (MCh) respiration in permeabilized cardiac left ventricular (LV) fibers, the myocardial energy state, and cardiomyocyte membranes damage in a model of streptozotocin (STZ) diabetes in rats. Metilin was prepared by solid-phase synthesis using the Fmoc strategy and purified using HPLC. Four groups of animals were used: initial state (IS); control (C), diabetic control (D) and diabetic animals additionally treated with metilin (DM). The following parameters have been studied: blood glucose, MCh respiration in LV fibers, the content of cardiac ATP, ADP, AMP, phosphocreatine (PCr) and creatine (Cr), the activity of creatine kinase-MB (CK-MB) and lactate dehydrogenase (LDH) in blood plasma. Administration of metilin to STZ-treated rats decreased blood glucose, increased state 3 oxygen consumption, the respiratory control ratio in MCh of permeabilized LV fibers, and increased the functional coupling of mitochondrial CK (mt-CK) to oxidative phosphorylation compared with these parameters in group D. In STZ-treated animals metilin administration caused an increase in the PCr content and prevention of the loss of total creatine (ΣCr=PCr+Cr) in the diabetic hearts, as well as restoration of the PCr/ATP ratio in the myocardium and a decrease in the activity of CK-MB and LDH in plasma to initial values. Thus, metilin prevented energy disorders disturbances in cardiomyocytes of animals with experimental T1DM.

UNASSIGNED: To analyze the influencing factors for progression from newly diagnosed prediabetes (PreDM) to diabetes within 3 years and establish a prediction model to assess the 3-year risk of developing diabetes in patients with PreDM.
UNASSIGNED: Subjects who were diagnosed with new-onset PreDM at the Physical Examination Center of the First Affiliated Hospital of Soochow University from October 1, 2015 to May 31, 2023 and completed the 3-year follow-up were selected as the study population. Data on gender, age, body mass index (BMI), waist circumference, etc. were collected. After 3 years of follow-up, subjects were divided into a diabetes group and a non-diabetes group. Baseline data between the two groups were compared. A prediction model based on logistic regression was established with nomogram drawn. The calibration was also depicted.
UNASSIGNED: Comparison between diabetes group and non-diabetes group: Differences in 24 indicators including gender, age, history of hypertension, fatty liver, BMI, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, HbA1c, etc. were statistically significant between the two groups (P<0.05). Differences in smoking, creatinine and platelet count were not statistically significant between the two groups (P>0.05). Logistic regression analysis showed that ageing, elevated BMI, male gender, high fasting blood glucose, increased LDL-C, fatty liver, liver dysfunction were risk factors for progression from PreDM to diabetes within 3 years (P<0.05), while HDL-C was a protective factor (P<0.05). The derived formula was: In(p/1-p)=0.181×age (40-54 years old)/0.973×age (55-74 years old)/1.868×age (≥75 years old)-0.192×gender (male)+0.151×blood glucose-0.538×BMI (24-28)-0.538×BMI (≥28)-0.109×HDL-C+0.021×LDL-C+0.365×fatty liver (yes)+0.444×liver dysfunction (yes)-10.038. The AUC of the model for predicting progression from PreDM to diabetes within 3 years was 0.787, indicating good predictive ability of the model.
UNASSIGNED: The risk prediction model for developing diabetes within 3 years in patients with PreDM constructed based on 8 influencing factors including age, BMI, gender, fasting blood glucose, LDL-C, HDL-C, fatty liver and liver dysfunction showed good discrimination and calibration.

UNASSIGNED: Previous studies have confirmed that the triglyceride glucose (TyG) index, recognized as a reliable marker of insulin resistance, is an important risk factor for diabetic kidney disease (DKD). However, it is still unclear whether the DKD risk continues to increase linearly with the elevation of TyG index. This study aimed to thoroughly investigated the intrinsic relationship between TyG index and DKD risk in type 2 diabetes (T2D).
UNASSIGNED: This cross-sectional study included 933 patients with T2D in China, who were categorized into DKD and non-DKD groups and stratified by TyG index levels. Logistic regression analysis identified the independent risk factors for DKD. The association between DKD risk and TyG index was evaluated using the restricted cubic spline (RCS) curves analysis. The R package \'CatPredi\' was utilized to determine the optimal cut-off point for the relationship between DKD risk and TyG index, followed by threshold effect analysis.
UNASSIGNED: The prevalence of DKD was 33.01%. After adjusting for confounding factors, TyG index was identified as a prominent clinical risk factor for DKD, showing the highest odds ratio (OR 1.57 (1.26 - 1.94), P<0.001). RCS analysis revealed a non-linear relationship with a threshold interval effect between the TyG index and DKD risk. When TyG index ≤ 9.35, DKD risk plateaued at a low level; however, when TyG index > 9.35, DKD risk increased gradually with rising TyG index. Among patients with TyG index > 9.35, each 1-unit increase was associated with a 1.94-fold increased DKD risk (OR=1.94 (1.10 - 3.43), P=0.022).
UNASSIGNED: The DKD risk presented a threshold effect with the increase of TyG index, initially stable at a low level, and then gradually rising when the TyG index is above 9.35.

BACKGROUND: Triglyceride glucose (TyG) index combined with obesity-related indicators [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist to height ratio (TyG-WHtR), triglyceride glucose-waist circumference (TyG-WC)], represents emerging methodologies for assessing insulin resistance. The objective of this investigation was to explore the correlation between TyG-related indices and gallstone disease.
METHODS: The study included 3740 adults from the 2017-2020 period of the National Health and Nutrition Examination Survey. TyG-BMI, TyG-WC, and TyG-WHtR were integrated as both continuous and categorical variables within the multivariate logistic model, respectively to evaluate the connection between various TyG-related indices and gallstone disease. Additionally, restriction cubic splines and subgroup analysis were employed to deepen our understanding of this relationship.
RESULTS: When analyzed as continuous variables, positive correlations were observed between TyG-BMI, TyG-WC, TyG-WHtR and gallstone disease. The OR(95%CI) were 1.063(1.045,1.082) for TyG-BMI (per 10-unit), 1.026(1.018,1.034) for TyG-WC (per 10-unit) and 1.483(1.314,1.676) for TyG-WHtR (per 1-unit), respectively. When categorized into quartiles, these three TyG-related indices still show statistically significant associations with gallstone disease. Descending in order, the diagnostic capability for gallstone disease is demonstrated as follows: TyG-WHtR (AUC = 0.667), TyG-BMI (AUC = 0.647), and TyG-WC (AUC = 0.640).
CONCLUSIONS: There were significantly positive associations between TyG-related indices, including TyG-BMI, TyG-WC, and TyG-WHtR, and gallstone disease. Of these indices, TyG-WHtR demonstrated the most favorable performance in identifying the risk of gallstone disease.

BACKGROUND: Efficient monitoring of glucose concentration in the human body necessitates the utilization of electrochemically active sensing materials in nonenzymatic glucose sensors. However, prevailing limitations such as intricate fabrication processes, lower sensitivity, and instability impede their practical application. Herein, ternary Cu-Co-Ni-S sulfides nanoporous network structure was synthesized on carbon fiber paper (CP) by an ultrafast, facile, and controllable technique through on-step cyclic voltammetry, serving as a superior self-supporting catalytic electrode for the high-performance glucose sensor.
RESULTS: The direct growth of free-standing Cu-Co-Ni-S on the interconnected three-dimensional (3D) network of CP boosted the active site of the composites, improved ion diffusion kinetics, and significantly promoted the electron transfer rate. The multiple oxidation states and synergistic effects among Co, Ni, Cu, and S further promoted glucose electrooxidation. The well-architected Cu-Co-Ni-S/CP presented exceptional electrocatalytic properties for glucose with satisfied linearity of a broad range from 0.3 to 16,000 μM and high sensitivity of 6829 μA mM- 1 cm- 2. Furthermore, the novel sensor demonstrated excellent selectivity and storage stability, which could successfully evaluate the glucose levels in human serum. Notably, the novel Cu-Co-Ni-S/CP showed favorable biocompatibility, proving its potential for in vivo glucose monitoring.
CONCLUSIONS: The proposed 3D hierarchical morphology self-supported electrode sensor, which demonstrates appealing analysis behavior for glucose electrooxidation, holds great promise for the next generation of high-performance glucose sensors.

BACKGROUND: Clinical guidelines recommend basic carbohydrate counting (BCC), or similar methods to improve carbohydrate estimation skills and to strive for higher consistency in carbohydrate intake potentially improving glycaemic control. However, evidence for this approach in type 2 diabetes (T2D) is limited.
OBJECTIVE: To examine the efficacy of a structured education program in BCC as add-on to standard dietary care on glycaemic control in individuals with T2D.
METHODS: The BCC Study was a randomized, controlled, open-label, parallel-group trial. Individuals with T2D aged 18-75 years with glycated haemoglobin A1c (HbA1c) 53-97 mmol/mol (7.0-11.0%) were randomly assigned (1:1) to BCC or standard dietary care. The primary outcomes were differences in changes in HbA1c or glycaemic variability (calculated as mean amplitude of glycaemic excursions [MAGE]) between groups after six months of intervention.
RESULTS: Between September 2018 and July 2021, 48 participants were randomly assigned, 23 to BCC and 25 to standard dietary care. Seven participants did not receive the allocated intervention. From a baseline-adjusted mean of 65 mmol/mol (95% CI 62-68 [8.1%, 7.8-8.4]), HbA1c changed by -5 mmol/mol (-8 to -1 [-0.5%, -0.7 to -0.1]) in BCC and -3 mmol/mol (-7 to 1 [-0.3%, -0.6 to 0.1]) in standard care with an estimated treatment effect of -2 mmol/mol (-7 to 4 [-0.2%, -0.6 to 0.4]); p = 0.554. From a baseline-adjusted mean of 4.2 mmol/l (3.7 to 4.8), MAGE changed by -16% (-33 to 5) in BCC and by -3% (-21 to 20) in standard care with an estimated treatment effect of -14% (-36 to 16); p = 0.319. Only median carbohydrate estimation error in favour of BCC (estimated treatment difference -55% (-70 to -32); p < 0.001) remained significant after multiple testing adjustment.
CONCLUSIONS: No glycaemic effects were found but incorporating BCC as a supplementary component to standard dietary care led to improved skills in estimating carbohydrate intake among individuals with T2D.

BACKGROUND: We previously reported predictors of mortality in 1786 adults with diabetes or stress hyperglycemia (glucose>180 mg/dL twice in 24 hours) admitted with COVID-19 from March 2020 to February 2021 to five university hospitals. Here, we examine predictors of readmission.
METHODS: Data were collected locally through retrospective reviews of electronic medical records from 1786 adults with diabetes or stress hyperglycemia who had a hemoglobin A1c (HbA1c) test on initial admission with COVID-19 infection or within 3 months prior to initial admission. Data were entered into a Research Electronic Data Capture (REDCap) web-based repository, and de-identified. Descriptive data are shown as mean±SD, per cent (%) or median (IQR). Student\'s t-test was used for comparing continuous variables with normal distribution and Mann-Whitney U test was used for data not normally distributed. X2 test was used for categorical variable.
RESULTS: Of 1502 patients who were alive after initial hospitalization, 19.4% were readmitted; 90.3% within 30 days (median (IQR) 4 (0-14) days). Older age, lower estimated glomerular filtration rate (eGFR), comorbidities, intensive care unit (ICU) admission, mechanical ventilation, diabetic ketoacidosis (DKA), and longer length of stay (LOS) during the initial hospitalization were associated with readmission. Higher HbA1c, glycemic gap, or body mass index (BMI) were not associated with readmission. Mortality during readmission was 8.0% (n=23). Those who died were older than those who survived (74.9±9.5 vs 65.2±14.4 years, p=0.002) and more likely had DKA during the first hospitalization (p<0.001). Shorter LOS during the initial admission was associated with ICU stay during readmission, suggesting that a subset of patients may have been initially discharged prematurely.
CONCLUSIONS: Understanding predictors of readmission after initial hospitalization for COVID-19, including older age, lower eGFR, comorbidities, ICU admission, mechanical ventilation, statin use and DKA but not HbA1c, glycemic gap or BMI, can help guide treatment approaches and future research in adults with diabetes.