Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort.

BACKGROUND: Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. METHODS: We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. RESULTS: Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. CONCLUSION: Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Association of neutrophil-lymphocyte ratio with all-cause and cardiovascular mortality in US adults with diabetes and prediabetes: a prospective cohort study.

BACKGROUND: The neutrophil-lymphocyte ratio (NLR) is a novel hematological parameter to assess systemic inflammation. Prior investigations have indicated that an increased NLR may serve as a potential marker for pathological states such as cancer and atherosclerosis. However, there exists a dearth of research investigating the correlation between NLR levels and mortality in individuals with diabetes and prediabetes. Consequently, this study aims to examine the connection between NLR and all-cause as well as cardiovascular mortality in the population of the United States (US) with hyperglycemia status. METHODS: Data were collected from a total of 20,270 eligible individuals enrolled for analysis, spanning ten cycles of the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The subjects were categorized into three groups based on tertiles of NLR levels. The association of NLR with both all-cause and cardiovascular mortality was evaluated using Kaplan-Meier curves and Cox proportional hazards regression models. Restricted cubic splines were used to visualize the nonlinear relationship between NLR levels and all-cause and cardiovascular mortality in subjects with diabetes after accounting for all relevant factors. RESULTS: Over a median follow-up period of 8.6 years, a total of 1909 subjects with diabetes died, with 671 deaths attributed to cardiovascular disease (CVD). And over a period of 8.46 years, 1974 subjects with prediabetes died, with 616 cases due to CVD. The multivariable-adjusted hazard ratios (HRs) comparing high to low tertile of NLR in diabetes subjects were found to be 1.37 (95% CI, 1.19-1.58) for all-cause mortality and 1.63 (95% CI, 1.29-2.05) for CVD mortality. And the correlation between high to low NLR tertile and heightened susceptibility to mortality from any cause (HR, 1.21; 95% CI, 1.03-1.43) and CVD mortality (HR, 1.49; 95% CI, 1.08-2.04) remained statistically significant (both p-values for trend < 0.05) in prediabetes subjects. The 10-year cumulative survival probability was determined to be 70.34%, 84.65% for all-cause events, and 86.21%, 94.54% for cardiovascular events in top NLR tertile of diabetes and prediabetes individuals, respectively. Furthermore, each incremental unit in the absolute value of NLR was associated with a 16%, 12% increase in all-cause mortality and a 25%, 24% increase in cardiovascular mortality among diabetes and prediabetes individuals, respectively. CONCLUSIONS: The findings of this prospective cohort study conducted in the US indicate a positive association of elevated NLR levels with heightened risks of overall and cardiovascular mortality among adults with diabetes and prediabetes. However, potential confounding factors for NLR and the challenge of monitoring NLR's fluctuations over time should be further focused.

Investigating the Role of FABP4 in Diabetes and Obesity and the Influence of Age and Ethnicity: A Comprehensive Analysis of a Cohort from the KEDP-Study.

Adipocyte P2 (aP2), also known as FABP4, is an adipokine that adipose tissue produces and expresses in macrophages. Its primary role is to facilitate the transportation of fatty acids across cell membranes. Numerous studies have reported associations between FABP4 and the development of metabolic disorders. However, there is limited knowledge regarding FABP4 expression in diabetes and obesity, especially about different age groups, genders, and ethnicities. This study aims to investigate the association between FABP4 levels, diabetes mellitus, and obesity within various ethnic groups. We measured plasma FABP4 concentrations in a cohort of 2083 patients from the KDEP study and gathered anthropometric data. Additionally, we collected and analyzed clinical, biochemical, and glycemic markers using multivariate regression analysis. The average FABP4 concentration was significantly higher in female participants than in males (18.8 ng/mL vs. 14.4 ng/mL, p < 0.001, respectively), and in those over 50 years old compared to those under 50 years of age (19.3 ng/mL vs. 16.2 ng/mL, p < 0.001, respectively). In this study, significant positive associations were found between the plasma level of FABP4 and obesity markers: BMI (r = 0.496, p < 0.001), hip circumference (r = 0.463, p < 0.001), and waist circumference (WC) (r = 0.436, p < 0.001). Similar observations were also seen with glycemic markers, which included HbA1c (r = 0.126, p < 0.001), fasting blood glucose (FBG) (r = 0.184, p < 0.001), fasting insulin (r = 0.326, p < 0.001), and HOMA-IR (r = 0.333, p < 0.001). Importantly, these associations remained significant even after adjusting for age, gender, and ethnicity. Furthermore, FABP4 levels were negatively associated with male gender (ß: -3.85, 95% CI: -4.92, -2.77, p < 0.001), and positively associated with age (ß: 0.14, 95% CI: 0.096, 0.183, p < 0.001), BMI (ß: 0.74, 95% CI: 0.644, 0.836, p < 0.001), and fasting insulin (ß: 0.115, 95% CI: 0.091, 0.138, p < 0.001). In this study, plasma FABP4 levels were significantly higher in diabetic and obese participants, and they were strongly influenced by age, gender, and ethnicity. These findings suggest that FABP4 may serve as a valuable prognostic and diagnostic marker for obesity and diabetes, particularly among female patients, individuals over 50 years old, and specific ethnic groups.

Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome.

INTRODUCTION: This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms. RESEARCH DESIGN AND METHODS: We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network. RESULTS: Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes. CONCLUSIONS: Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.

Diabetes mellitus, systemic inflammation and overactive bladder.

Background: Increasing evidence emphasizes the potential relationship between diabetes and OAB (overactive bladder). However, large population epidemiology is still lacking. Methods: This cross-sectional study included six cycle NHANES surveys, with a total of 23863 participants. Logistic regression models were constructed to analyze the association between diabetes mellitus, diabetes-related markers, and inflammatory biomarkers with OAB. Restricted cubic splines were used to analyze the non-linear associations. Mediating analysis was performed to test the effect of inflammatory biomarkers on the relationship between diabetes-related markers and OAB. Finally, machine learning models were applied to predict the relative importance and construct the best-fit model. Results: Diabetes mellitus participants' OAB prevalence increased by 77% compared with non-diabetes. As the quartiles of diabetes-related markers increased, the odds of OAB monotonically increased in three models (all p for trend < 0.001). Glycohemoglobin exhibited a linear association with OAB (p for nonlinearity > 0.05). White blood cells significantly mediated the associations between diabetes-related markers (glycohemoglobin, fasting glucose, and insulin) with OAB, and the proportions were 7.23%, 8.08%, and 17.74%, respectively (all p < 0.0001). Neutrophils partly mediated the correlation between (glycohemoglobin, fasting glucose, and insulin) and OAB at 6.58%, 9.64%, and 17.93%, respectively (all p < 0.0001). Machine learning of the XGBoost model constructs the best fit model, and XGBoost predicts glycohemoglobin is the most important indicator on OAB. Conclusion: Our research revealed diabetes mellitus and diabetes-related markers were remarkably associated with OAB, and systemic inflammation was an important mediator of this association.

Hematological Parameters and Comorbidities in COVID-19: Insights into Clinical Profiles and Outcome Predictors.

BACKGROUND: The global pandemic, known as the coronavirus disease 2019 (COVID-19) and caused by the severe acute respiratory syndrome, coronavirus 2 (SARS-CoV-2), poses a significant threat, particularly to individuals with comorbidities such as hypertension, chronic obstructive pulmonary disease (COPD), diabetes, HIV, cardiovascular disease (CVD), and cancer. METHODS: This descriptive retrospective study investigates the impact of comorbidities on COVID-19-positive patients. The study includes individuals that were tested positive for SARS-CoV-2 via polymerase chain reaction at the Security Forces Hospital, Makkah, KSA, between February, 2022, and June, 2022. A total of 208 patients (107 males, 101 females) were examined, and the laboratory results revealed normal parameters. RESULTS: An analysis indicates that 86.5% of the patients were discharged, 2.9% remained hospitalized, and 10.6% succumbed to the disease, indicating a 10.6% mortality rate among comorbid COVID-19-positive patients. Notably, the study identifies specific comorbidities (chronic kidney disease, diabetes mellitus, hypertension) and changes in laboratory parameters (red blood cells, hemoglobin, C-reactive protein, white blood cells, ferritin, D-dimer, ALT, troponin, LDH, neutrophils) associated with ICU admission during hospitalization. CONCLUSIONS: This study underscores the critical impact of comorbidities, such as chronic kidney disease, diabetes, and hypertension, on the clinical outcomes of COVID-19-positive patients. The identification of specific laboratory parameters linked with ICU admission provides valuable insights for risk stratification and tailored management strategies.

Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis.

OBJECTIVE: This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC). DESIGN: In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients. METHODS: The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes. RESULTS: Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups. CONCLUSIONS: These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.

The association between the triglyceride-glucose index and the risk of cardiovascular disease in US population aged ≤ 65 years with prediabetes or diabetes: a population-based study.

BACKGROUND: The relationship between the triglyceride-glucose (TyG) index and the risk of cardiovascular disease (CVD) in the U.S. population under 65 years of age with diabetes or prediabetes is unknown. The purpose of this study was to investigate the relationship between baseline TyG index and CVD risk in U.S. patients under 65 years of age with diabetes or prediabetes. METHODS: We used data from the 2003-2018 National Health and Nutrition Examination Survey (NHANES). Multivariate regression analysis models were constructed to explore the relationship between baseline TyG index and CVD risk. Nonlinear correlations were explored using restricted cubic splines. Subgroup analysis and interaction tests were also conducted. RESULTS: The study enrolled a total of 4340 participants with diabetes or pre-diabetes, with a mean TyG index of 9.02 ± 0.02. The overall average prevalence of CVD was 10.38%. Participants in the higher TyG quartiles showed high rates of CVD (Quartile 1: 7.35%; Quartile 2: 10.04%; Quartile 3: 10.71%; Quartile 4: 13.65%). For CVD, a possible association between the TyG index and the risk of CVD was observed. Our findings suggested a linear association between the TyG index and the risk of CVD. The results revealed a U-shaped relationship between the TyG index and both the risk of CVD (P nonlinear = 0.02583) and CHF (P nonlinear = 0.0208) in individuals with diabetes. Subgroup analysis and the interaction term indicated that there was no significant difference among different stratifications. Our study also revealed a positive association between the TyG index and comorbid MetS in the U.S. population under 65 years of age with prediabetes or diabetes. CONCLUSIONS: A higher TyG index was linked to an increased likelihood of CVD in the U.S. population aged ≤ 65 years with prediabetes and diabetes. Besides, TyG index assessment will contribute to more convenient and effective screening of high-risk individuals in patients with MetS. Future studies should explore whether interventions targeting the TyG index may improve clinical outcomes in these patients.

Nonenzymatic dual glucose sensing on boronic acid modified zeolitic imidazolate framework-67 nanoparticles for diabetes management.

For early diabetes identification and management, the progression of an uncomplicated and exceedingly responsive glucose testing technology is crucial. In this study, we present a new sensor incorporating a composite of metal organic framework (MOF) based on cobalt, coated with boronic acid to facilitate selective glucose binding. Additionally, we successfully employed a highly sensitive electro-optical immunosensor for the detection of subtle changes in concentration of the diabetes biomarker glycated haemoglobin (HbA1c), using zeolitic imidazolate framework-67 (ZIF-67) coated with polydopamine which further modified with boronic acid. Utilizing the polymerization characteristics of dopamine and the NH2 groups, a bonding structure is formed between ZIF-67 and 4-carboxyphenylboronic acid. ZIF-67 composite served as an effective substrate for immobilising 4-carboxyphenylboronic acid binding agent, ensuring precise and highly selective glucose identification. The sensing response was evaluated through both electrochemical and optical methods, confirming its efficacy. Under optimized experimental condition, the ZIF-67 based sensor demonstrated a broad detection range of 50-500 mg dL-1, a low limit of detection (LOD) of 9.87 mg dL-1 and a high correlation coefficient of 0.98. Furthermore, the 4-carboxyphenylboronic acid-conjugated ZIF-67-based sensor platform exhibited remarkable sensitivity and selectivity in optical-based detection for glycated haemoglobin within the clinical range of 4.7-11.3%, achieving a LOD of 3.7%. These findings highlight the potential of the 4-carboxyphenylboronic acid-conjugated ZIF-67-based electro-optical sensor as a highly sensitive platform for diabetes detection.

Emerging biosensor probes for glycated hemoglobin (HbA1c) detection.

Glycated hemoglobin (HbA1c), originating from the non-enzymatic glycosylation of ßVal1 residues in hemoglobin (Hb), is an essential biomarker indicating average blood glucose levels over a period of 2 to 3 months without external environmental disturbances, thereby serving as the gold standard in the management of diabetes instead of blood glucose testing. The emergence of HbA1c biosensors presents affordable, readily available options for glycemic monitoring, offering significant benefits to small-scale laboratories and clinics. Utilizing nanomaterials coupled with high-specificity probes as integral components for recognition, labeling, and signal transduction, these sensors demonstrate exceptional sensitivity and selectivity in HbA1c detection. This review mainly focuses on the emerging probes and strategies integral to HbA1c sensor development. We discussed the advantages and limitations of various probes in sensor construction as well as recent advances in diverse sensing strategies for HbA1c measurement and their potential clinical applications, highlighting the critical gaps in current technologies and future needs in this evolving field.

The reliability of using gingival crevicular blood to measure blood glucose and hba1c levels in the dental setting: a systematic review and meta-analysis.

OBJECTIVE: There are 500 million patients living with diabetes mellitus worldwide and 50% of them remain undiagnosed. Routine periodontal probing provides gingival crevicular blood in patients with gingivitis. Gingival blood may be useful for diabetes screening without the need for any expensive, painful or time-consuming method by using convenient glucometers. Therefore, the objective of this systematic review and meta-analysis is to answer the question to "is there a difference in glucose or HbA1c levels (O) in patients with positive gingival bleeding (P) measured on gingival crevicular blood (GCB) (I) compared to finger prick capillary blood (CB) (C). MATERIALS AND METHODS: The authors performed an electronic search of six databases using identical MeSH phrases. Only human clinical studies without limitations on the year of publication were considered. Data extraction was done by using standardized data collection sheets. Risk of bias assessment were conducted using QUADAS-2 and QUADAS-C. Meta-analyses were carried out with the random effects model to aggregate the correlation coefficients and the difference between the means between gingival and capillary blood reading, using 95% confidence intervals. RESULTS: The database and manual search yielded 268 articles, from which the selection procedure provided 36 articles for full-text screening, and the final pool of eligible articles composed of 23 studies with 1680 patients. Meta-analysis results on glycemic levels showed differences between the GCB and CB procedures in patients with and without diabetes with values of -6.80 [-17.35; 3.76] and - 4.36 [-9.89; 1.18], respectively. Statistically significant correlations were found (p = 0.001) between GCB and CB measurements in patients with (0.97 [0.927; 0.987]) and without diabetes (0.927 [0.873; 0.958]). CONCLUSION: Gingival blood could prove to be useful to identify patients with undiagnosed diabetes when the necessary amount of uncontaminated blood is present. However, this technique is limited by the possibility of contamination, prandial status and inaccuracies, so it is unsuited to address the patient's glycemic control accurately.

JMJD6 Autoantibodies as a Potential Biomarker for Inflammation-Related Diseases.

Inflammation is closely associated with cerebrovascular diseases, cardiovascular diseases, diabetes, and cancers, and it is accompanied by the development of autoantibodies in the early stage of inflammation-related diseases. Hence, it is meaningful to discover novel antibody biomarkers targeting inflammation-related diseases. In this study, Jumonji C-domain-containing 6 (JMJD6) was identified by the serological identification of antigens through recombinant cDNA expression cloning. In particular, JMJD6 is an antigen recognized in serum IgG from patients with unstable angina pectoris (a cardiovascular disease). Then, the serum antibody levels were examined using an amplified luminescent proximity homogeneous assay-linked immunosorbent assay and a purified recombinant JMJD6 protein as an antigen. We observed elevated levels of serum anti-JMJD6 antibodies (s-JMJD6-Abs) in patients with inflammation-related diseases such as ischemic stroke, acute myocardial infarction (AMI), diabetes mellitus (DM), and cancers (including esophageal cancer, EC; gastric cancer; lung cancer; and mammary cancer), compared with the levels in healthy donors. The s-JMJD6-Ab levels were closely associated with some inflammation indicators, such as C-reactive protein and intima-media thickness (an atherosclerosis index). A better postoperative survival status of patients with EC was observed in the JMJD6-Ab-positive group than in the negative group. An immunohistochemical analysis showed that JMJD6 was highly expressed in the inflamed mucosa of esophageal tissues, esophageal carcinoma tissues, and atherosclerotic plaques. Hence, JMJD6 autoantibodies may reflect inflammation, thereby serving as a potential biomarker for diagnosing specific inflammation-related diseases, including stroke, AMI, DM, and cancers, and for prediction of the prognosis in patients with EC.

Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit.

BACKGROUND: We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction. METHODS: Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed. RESULTS: In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good. CONCLUSION: This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

Very short sleep duration reveals a proteomic fingerprint that is selectively associated with incident diabetes mellitus but not with incident coronary heart disease: a cohort study.

BACKGROUND: The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease. METHODS: We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46-68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates. RESULTS: Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06-1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD. CONCLUSIONS: We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

Effect of glycotoxicity and lipotoxicity on carbohydrate antigen 19 - 9 in the patients with diabetes.

OBJECTIVES: In comparison to the subjects without diabetes, a greater concentration of serum carbohydrate antigen 19 - 9 (CA 19 - 9) was observed in the subjects with diabetes. Nevertheless, since the occurrence of abnormal CA 19 - 9 is not widespread among the whole diabetic population, this phenomenon has not attracted enough attention. The prevalence of abnormal CA 19 - 9 in hospitalized patients with diabetes was the focus of our research. METHOD: A total of 385 subjects with diabetes and 200 controls were enrolled and all had been tested the CA19-9 levels. Cases of cancers were excluded through examination and followup for 1 year. RESULTS: We found that the rate of patients with abnormal CA19-9 level was 8.3%. The rate of patients with abnormal CA19-9 level was 14.0% in the HbA1c ≥ 9% group, and 3.0% in the HbA1c < 9% group, 2.5% in the control group. There was no significant difference in the HbA1c < 9% group and the control group. A significant correlation between serum CA19-9 and both HbA1c and total cholesterol was observed, yet no difference in CRP level was observed between subjects with normal CA19-9 level and subjects with abnormal CA19-9 level. However, a significant difference in fasting C-peptide levels was observed between the two groups, p = 0.039. CONCLUSION: The percentage of patients with diabetes exhibiting elevated CA19-9 level is 14% in the HbA1c ≥ 9% diabetic patients, much higher than expected. The underlying mechanism may be related to islet injury caused by glycotoxicity and lipotoxicity. STRENGTHS AND LIMITATIONS OF THE STUDY: We studied the rate of hospitalized diabetic patients with elevated CA 19 - 9 which were characterized with poorly controlled blood glucose. We found that the elevation of CA 19 - 9 was unexpectedly high in diabetic inpatients without development to cancer. The limitation of this study is that the underlying mechanism is not sufficiently studied.

Changes in glucometric parameters in people living with diabetes users of the free-style libre 2 system before and after the update possibility to real-time glucose readings in real world practice.

In Spain, from October 10th, 2023, the FreeStyle Libre 2 system offers the possibility to automatically changed from isCGM to rtCGM with a system update. Our study aimed to evaluate the glucometric before and after that date. We didn't find significant changes in TIR, however time of use increased and TBR decreased.

Severity of COVID-19 infection in patients with COVID-19 combined with diabetes.

PURPOSE: This study aimed to analyse the correlation between blood glucose control and the severity of COVID-19 infection in patients with diabetes. METHODS: Clinical and imaging data of a total of 146 patients with diabetes combined with COVID-19 who visited our hospital between December 2022 and January 2023 were retrospectively collected. The patients were divided into the 'good blood glucose control' group and the 'poor blood glucose control' group based on an assessment of their blood glucose control. The clinical data, computed tomography (CT) appearance and score and the severity of COVID-19 infection of the two groups were compared, with the severity of COVID-19 infection being the dependent variable to analyse other influencing factors. RESULTS: The group with poor blood glucose control showed a higher lobar involvement degree and total CT severity score (CTSS) than the group with good blood glucose control (13.30 ± 5.25 vs. 10.38 ± 4.84, p < 0.05). The two groups exhibited no statistically significant differences in blood lymphocyte, leukocyte, C-reaction protein, pleural effusion, consolidation, ground glass opacity or crazy-paving signs. Logistic regression analysis showed that the total CTSS significantly influences the clinical severity of patients (odds ratio 1.585, p < 0.05), whereas fasting plasma glucose and blood glucose control are not independent factors influencing clinical severity (both p > 0.05). The area under the curve (AUC) of CTSS prediction of critical COVID-19 was 0.895 with sensitivity of 79.3% and specificity of 88.1% when the threshold value is 12. CONCLUSION: Blood glucose control is significantly correlated with the CTSS; the higher the blood glucose is, the more severe the lung manifestation. The CTSS can also be used to evaluate and predict the clinical severity of COVID-19.

Free triiodothyronine to free thyroxine ratio as a marker of poor prognosis in euthyroid patients with acute coronary syndrome and diabetes after percutaneous coronary intervention.

Objectives: In recent years, the free triiodothyronine/free thyroxine (FT3/FT4) ratio, a new comprehensive index for evaluating thyroid function, which could reflect thyroid function more stably and truly than serum thyroid hormone level, has been demonstrated to correlate with the risks of diabetes and cardiovascular disease in euthyroid adults. However, the correlation between thyroid hormone sensitivity and long-term prognosis in euthyroid patients with acute coronary syndrome (ACS) and diabetes after percutaneous coronary intervention (PCI) remains unclear. Methods: A total of 1,786 euthyroid patients with ACS who successfully underwent PCI at Beijing Anzhen Hospital from August 2021 to April 2022 were included in our study, which was divided into three groups according to tertiles of thyroid hormone sensitivity index. Cox regression, Kaplan-Meier, and receiver operating characteristic analyses were applied to analyze the associations between the FT3/FT4 ratio with ACS and diabetes after PCI. Results: Our analysis indicated that a lower level of FT3/FT4 ratio in euthyroid patients with acute coronary syndrome (ACS) and diabetes after PCI showed significantly higher incidences of major adverse cardiac and cerebrovascular events (MACCE) when compared with a higher level of FT3/FT4 ratio. After adjusting for other covariates, patients with a lower level of FT3/FT4 ratio were negatively associated with the risk of MACCE than those with a higher level of FT3/FT4 ratio (adjusted OR =1.61, 95% CI 1.05-2.47, P = 0.028). In subgroup analyses, individuals were stratified by age, sex, BMI, ACS type, hypertension, and dyslipidemia, showing that there were no significant interactions between the FT3/FT4 ratio and all subgroups for MACCE. In addition, the FT3/FT4 ratio performed better on ROC analyses for cardiac death prediction [area under the curve (AUC), 0.738]. Conclusion: A reduced level of FT3/FT4 ratio was a potential marker of poor prognosis in euthyroid patients with ACS and diabetes after PCI.

The impact of triglyceride glucose-body mass index on all-cause and cardiovascular mortality in elderly patients with diabetes mellitus: evidence from NHANES 2007-2016.

BACKGROUND: The relationship between triglyceride glucose-body mass index (TyG-BMI) index and mortality in elderly patients with diabetes mellitus (DM) are still unclear. This study aimed to investigate the association between TyG-BMI with all-cause and cardiovascular mortality among elderly DM patients in the United States (US). METHODS: Patients aged over 60 years with DM from the National Health and Nutrition Examination Survey (2007-2016) were included in this study. The study endpoints were all-cause and cardiovascular mortality and the morality data were extracted from the National Death Index (NDI) which records up to December 31, 2019. Multivariate Cox proportional hazards regression model was used to explore the association between TyG-BMI index with mortality. Restricted cubic spline was used to model nonlinear relationships. RESULTS: A total of 1363 elderly diabetic patients were included, and were categorized into four quartiles. The mean age was 70.0 ± 6.8 years, and 48.6% of them were female. Overall, there were 429 all-cause deaths and 123 cardiovascular deaths were recorded during a median follow-up of 77.3 months. Multivariate Cox regression analyses indicated that compared to the 1st quartile (used as the reference), the 3rd quartile demonstrated a significant association with all-cause mortality (model 2: HR = 0.64, 95% CI 0.46-0.89, P = 0.009; model 3: HR = 0.65, 95% CI 0.43-0.96, P = 0.030). Additionally, the 4th quartile was significantly associated with cardiovascular mortality (model 2: HR = 1.83, 95% CI 1.01-3.30, P = 0.047; model 3: HR = 2.45, 95% CI 1.07-5.57, P = 0.033). The restricted cubic spline revealed a U-shaped association between TyG-BMI index with all-cause mortality and a linear association with cardiovascular mortality, after adjustment for possible confounding factors. CONCLUSIONS: A U-shaped association was observed between the TyG-BMI index with all-cause mortality and a linear association was observed between the TyG-BMI index with cardiovascular mortality in elderly patients with DM in the US population.

Independent Correlates of Glycemic Control among Adults with Diabetes in South Africa.

BACKGROUND: Globally, the prevalence of diabetes is increasing, especially in low- and middle-income countries (LMICs), including those in the sub-Saharan African region. However, the independent socioeconomic correlates of glycemic control as measured by hemoglobin A1C have yet to be identified. Therefore, the aim of this analysis was to understand the independent correlates of glycemic control in South Africa. METHODS: Data from the 2016 South Africa Demographic and Health Survey on adults with diabetes were used for this analysis. The dependent variable, glycemic control, was defined using hemoglobin A1c (HbA1c). Independent variables included: age, gender, ethnicity, marital status, region, urban/rural residence, ability to read, education, insurance, wealth, occupation, and employment in the last year. Analysis of variance was used to test for differences in mean HbA1c for each category of all independent variables, and a fully adjusted linear regression model was used to identify independent correlates of glycemic control (HbA1c). RESULTS: Among the 772 people included in this analysis, there were significant differences in mean HbA1c by age (p < 0.001), ethnicity (p < 0.001), place of residence (p = 0.024), wealth index (p = 0.001), and employment in the last year (p = 0.008). Independent correlates of HbA1c included age, ethnicity, and wealth index. CONCLUSIONS: This study used data from a large diverse population with a high prevalence of diabetes in sub-Saharan Africa and provides new evidence on the correlates of glycemic control and potential targets for interventions designed to lower HbA1c and improve diabetes-related health outcomes of adults in South Africa.