HbA1c variability associated with dementia risk in people with type 2 diabetes.

INTRODUCTION: Although poor glycemic control is associated with dementia, it is unknown if variability in glycemic control, even in those with optimal glycosylated hemoglobin A1c (HbA1c) levels, increases dementia risk. METHODS: Among 171,964 people with type 2 diabetes, we evaluated the hazard of dementia association with long-term HbA1c variability using five operationalizations, including standard deviation (SD), adjusting for demographics and comorbidities. RESULTS: The mean baseline age was 61 years (48% women). Greater HbA1c SD was associated with greater dementia hazard (adjusted hazard ratio = 1.15 [95% confidence interval: 1.12, 1.17]). In stratified analyses, higher HbA1c SD quintiles were associated with greater dementia hazard among those with a mean HbA1c < 6% (P = 0.0004) or 6% to 8% (P < 0.0001) but not among those with mean HbA1c ≥ 8% (P = 0.42). DISCUSSION: Greater HbA1c variability is associated with greater dementia risk, even among those with HbA1c concentrations at ideal clinical targets. These findings add to the importance and clinical impact of recommendations to minimize glycemic variability. HIGHLIGHTS: We observed a cohort of 171,964 people with type 2 diabetes (mean age 61 years). This cohort was based in Northern California between 1996 and 2018. We examined the association between glycosylated hemoglobin A1c (HbA1c) variability and dementia risk. Greater HbA1c variability was associated with greater dementia hazard. This was most evident among those with normal-low mean HbA1c concentrations.

Comparison of admission glycemic variability and glycosylated hemoglobin in predicting major adverse cardiac events among type 2 diabetes patients with heart failure following acute ST-segment elevation myocardial infarction.

Background and Objectives: Hyperglycemia is associated with adverse outcomes in patients with acute myocardial infarction (AMI) as well as in patients with heart failure. However, the significance of admission glycemic variability (GV) in predicting outcomes among diabetes patients with heart failure (HF) following acute ST-segment elevation myocardial infarction (ASTEMI) remains unclear. This study aims to explore the prognostic value of admission GV and admission glycosylated hemoglobin (HbA1c) levels in individuals diagnosed with type 2 diabetes and HF following ASTEMI. Methods: We measured GV and HbA1c upon admission in 484 consecutive patients diagnosed with type 2 diabetes and HF following ASTEMI. GV, indicated as the mean amplitude of glycemic excursions (MAGE), was assessed utilizing a continuous glucose monitoring system (CGMS). admission MAGE values were categorized as < 3.9 or ≥ 3.9 mmol/L, while HbA1c levels were classified as < 6.5 or ≥ 6.5%. Participants were followed up prospectively for 12 months. The relationship of admission MAGE and HbA1c to the major adverse cardiac event (MACE) of patients with type 2 diabetes and HF following ASTEMI was analyzed. Results: Among the 484 enrolled patients, the occurrence of MACE differed significantly based on MAGE categories (< 3.9 vs. ≥ 3.9 mmol/L), with rates of 13.6% and 25.3%, respectively (P = 0.001). While MACE rates varied by HbA1c categories (< 6.5 vs. ≥ 6.5%) at 15.7% and 21.8%, respectively (P = 0.086). Patients with higher MAGE levels exhibited a notably elevated risk of cardiac mortality and an increased incidence of HF rehospitalization. The Kaplan-Meier curves analysis demonstrated a significantly lower event-free survival rate in the high MAGE level group compared to the low MAGE level group (log-rank test, P < 0.001), while HbA1c did not exhibit a similar distinction. In multivariate analysis, high MAGE level was significantly associated with incidence of MACE (hazard ratio 3.645, 95% CI 1.287-10.325, P = 0.015), whereas HbA1c did not demonstrate a comparable association (hazard ratio 1.075, 95% CI 0.907-1.274, P = 0.403). Conclusions: Elevated admission GV emerges as a more significant predictor of 1-year MACE in patients with type 2 diabetes and HF following ASTEMI, surpassing the predictive value of HbA1c.

Relationship of urinary glyphosate concentrations with glycosylated hemoglobin and diabetes in US adults: a cross-sectional study.

BACKGROUND: Glyphosate is a commonly used herbicide worldwide and is purportedly associated with multiple health effects. Research assessing the association of glyphosate concentrations with glycosylated hemoglobin (HbA1c) levels and the prevalence of diabetes is scarce. We sought to evaluate the association between urinary glyphosate levels and HbA1c levels and the prevalence of diabetes. METHODS: A total of 2,745 adults in the National Health and Nutrition Examination Survey from 2013 to 2016 were included in this study. Generalized linear models (GLM) were applied to evaluate the associations of glyphosate concentrations with HbA1c levels and the prevalence of diabetes. The dose-response relationship was examined using restricted cubic splines (RCS). RESULTS: Significantly positive correlations of urinary glyphosate concentrations with HbA1c levels (percentage change: 1.45; 95% CI: 0.95, 1.96; P < 0.001) and the prevalence of diabetes (OR: 1.45; 95% CI: 1.24, 1.68; P < 0.001) were found after adjustment. Compared with the lowest quartile of glyphosate levels, the highest quartile was positively associated with HbA1c levels (percentage change: 4.19; 95% CI: 2.54, 5.85; P < 0.001) and the prevalence of diabetes (OR: 1.89; 95% CI: 1.37, 2.63; P < 0.001). The RCS curves demonstrated a monotonically increasing dose-response relationship between urinary glyphosate levels and the prevalence of diabetes and HbA1c levels. CONCLUSIONS: Urinary glyphosate concentrations are positively associated with HBA1c levels and the prevalence of diabetes. To verify our findings, additional large-scale prospective investigations are required.

Efficacy of telemedicine intervention in the self-management of patients with type 2 diabetes: a systematic review and meta-analysis.

Purpose: We aimed to report the latest and largest pooled analyses and evidence updates to assess the effectiveness of telemedicine interventions for self-management (DSM) in patients with type 2 diabetes mellitus (T2DM). Methods: A systematic literature search was conducted using PubMed, Cochrane, Embase, and Web of Science in December 2023. We included randomized controlled trials (RCTs) of adults (≥18 years of age) diagnosed with T2DM where the intervention was the application of telemedicine. The Cochrane Risk of Bias Assessment was used to evaluate quality. The study's main outcome indicators were glycosylated hemoglobin (HbA1c) and diabetes self-management (DSM) capacity. Results: A total of 17 eligible articles, comprising 20 studies and 1,456 patients (734 in the intervention group and 722 in the control group), were included in the evidence synthesis. The baseline characteristics of both groups were similar in all outcomes. Comprehensive analyses showed post-intervention decreases in HbA1c, 2-h postprandial glucose, systolic and diastolic blood pressure, increases in Diabetes Self- Care activities, DSM competencies based on dietary and medication adherence, and improvements in overall DSM scores, all of which were statistically significant. While no statistically significant differences were observed in body mass index, lipids, and other DSM dimensions. Based on subgroup analyses, app-based experimental interventions targeting under 60 years old populations in Asia and North America were found to be more effective and less heterogeneity in the short term (<6 months of intervention). Conclusion: Telemedicine interventions may assist patients with T2DM in enhancing their DSM and improving their HbA1c levels. Clinician can use various telemedicine interventions to enhance DSM in T2DM patients, considering local circumstances. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42024508522.

Evaluation of Glycosylated Hemoglobin Levels and Effect of Tobacco Smoking in Periodontally Diseased Non-Diabetic Patients.

Background and Objective: Chronic diseases have progressively increased worldwide, impacting all areas and socioeconomic groups. Periodontal disease is an increasing global concern and contains risk factors similar to other chronic illnesses. The main risk factor for periodontitis is smoking. Smoking not only hastens periodontal disease but also complicates periodontal therapy. Serum glycosylated hemoglobin levels, which are derived from the average life span of an erythrocyte, are a good indicator of glycemic management during the preceding one to three months. This study was undertaken to assess the association between tobacco smoking and periodontal disease by evaluating plaque score, gingival score, extent and severity index (ESI), and glycemic status by estimating serum HbA1c in cigarette smoker patients compared to non-smokers. Methods: The study was conducted with 40 patients in the age range of 20-40 years. Patients were divided into two groups: non-smokers (Group I) and cigarette smokers (Group II). Periodontal clinical parameters such as the plaque index (PI), gingival index (GI), and ESI were recorded during the oral cavity examination. The biochemical marker, serum glycosylated hemoglobin, was measured in both groups. All parameters were measured at baseline and three months after periodontal therapy. The statistical tests used were the paired t-test, and Chi-square test for comparison between both groups. Results: The mean difference of PI of non-smokers was 0.33 ± 0.30, and smokers were 0.52 ± 0.32, which was statistically significant. The mean difference of GI of non-smokers was 0.34 ± 0.19 and smokers 0.36 ± 0.303, which was statistically significant. The mean difference of extent in non-smokers was 5.33 ± 1.59, 5.52 ± 2.43, and smokers were 0.18 ± 0.17. The mean difference in severity in non-smokers was 0.18 ± 0.17, and smokers were 0.31 ± 0.25, which was statistically significant. The mean difference of HbA1c in non-smokers and smokers was 0.43 ± 0.277 and 0.415 ± 0.230, which shows a higher mean difference in non-smokers, which was statistically non-significant. Conclusion and Global Health Implications: This study concluded that each of Group I and Group II showed substantial improvements in all clinical periodontal variables, which include plaque index (PI), gingival index (GI), extent and severity index (ESI), and biochemical marker serum glycosylated hemoglobin. Controlling inflammation with SRP can improve insulin resistance, lower glucose levels, and prevent non-enzymatic glycation of hemoglobin.

Impact of Lifestyle Modification: An Intervention on Newly Diagnosed Diabetics of the Urban Slum of Meerut.

Introduction Diabetes is a long-term condition that necessitates ongoing medical attention and self-care to prevent immediate complications and minimize the likelihood of long-term issues. Early diagnosis is one of the most important steps for people living with diabetes to take. Public awareness regarding the importance of lifestyle modification in managing type 2 diabetes mellitus is a crucial preventive measure. Despite continuous efforts to raise public awareness, the prevalence of type 2 diabetes continues to increase, with most people overlooking the importance of a healthy lifestyle. Our goal was to assess the impact of lifestyle modification on glycemic control in newly diagnosed diabetic patients. Materials and methods A total of 503 adults aged 30 years and above who were nondiabetic or were unaware of their diabetic status were assessed for their fasting blood glucose levels. Individuals identified as diabetic based on their fasting blood glucose levels were subjected to lifestyle modification for a period of three months. Glycemic levels were measured at the beginning and the end of the study period for comparison. Results Of the study participants, 7.6% were undiagnosed diabetics with increased blood sugar levels who were unaware of their diabetic status. Mean anthropometric measurements from pre- to postintervention values improved overall. Overall reduction was observed in weight (66.21±12.97 to 63.18±11.48), waist circumference (96.21±13.01 to 91.77±11.82), hip circumference (105.16±11.91 to 103.58±10.88), waist-hip ratio (0.91±0.09 to 0.88±0.08) and body mass index (27.48±6.04 to 26.18±5.30). Significant reductions were observed in the mean glycemic values, including fasting blood sugar (180.19±55.81 to 152.56±45.74) and glycosylated hemoglobin levels (8.61±1.97 to 6.68±1.67). Conclusion Lifestyle modification plays a crucial role in managing diabetes, both in preventing its onset and controlling its progression. The present study highlights the importance of early diagnosis and lifestyle interventions in the management of diabetes, thereby stressing the necessity of comprehensive strategies to combat this situation.

Poor Prestroke Glycemic Control Increases the Rate of Symptomatic Intracranial Hemorrhage after Mechanical Thrombectomy.

(1) Background: Diabetes is a well-established risk factor for acute ischemic stroke (AIS). This study evaluated the impact of prestroke glycemic control in diabetic patients on their 3-month clinical outcome after mechanical thrombectomy (MT). (2) Methods: AIS patients with a premorbid modified Rankin scale (mRS) score of 0-2 who were admitted within 6 h after stroke onset and treated with MT between January 2020 and August 2023 were retrospectively analyzed. The study evaluated the effect of prestroke glycemic control on the stroke severity, reperfusion rate, symptomatic intracranial hemorrhage (sICH) and favorable clinical outcome (modified Rankin scale score 0-2) at 3 months after endovascular treatment. (3) Results: A total of 364 patients were analyzed, with 275 cases of non-diabetes (ND), 66 of well-controlled diabetes (WCD) and 23 of poorly controlled diabetes (PCD). There was no significant difference in the baseline neurological deficit expressed according to the National Institutes of Health Stroke Scale among the three groups. The time from stroke onset to groin puncture was similar in the ND, WCD and PCD groups (median 215 min, 194.5 min and 222.5 min, respectively). There was no significant difference in the favorable 3-month clinical outcomes among these three groups (35.2% of ND patients, 42.4% of WCD patients and 39.1% of PCD patients) or full recovery (12.4% of ND patients, 11.0% of WCD patients and 17.4% of PCD patients). The rate of sICH was significantly higher in the PCD group as compared to the ND and WDP groups (21.7% of PCD patients versus 7.6% of ND patients, p = 0.038, and 6.0% of WCD patients, p = 0.046), but the 3-month mortality did not differ between the three groups (21.8% of ND group, 19.7% of WCD group and 26.1% of PCD group). (4) Conclusions: This study shows that poor prestroke glycemic control in AIS diabetic patients does not change the chance of a good clinical functional outcome after endovascular treatment. However, the increased risk of hemorrhagic complications in this group of patients should be considered.

Glycemic control and clinical outcomes in diabetic patients with heart failure and reduced ejection fraction: insight from ventricular remodeling using cardiac MRI.

BACKGROUND: Glycemic control, as measured by glycosylated hemoglobin (HbA1c), is an important biomarker to evaluate diabetes severity and is believed to be associated with heart failure development. Type 2 diabetes mellitus (T2DM) and heart failure with reduced ejection fraction (HFrEF) commonly coexist, and the combination of these two diseases indicates a considerably poorer outcome than either disease alone. Therefore, glycemic control should be carefully managed. The present study aimed to explore the association between glycemic control and clinical outcomes, and to determine the optimal glycemic target in this specific population. METHODS: A total of 262 patients who underwent cardiac MRI were included and were split by HbA1c levels [HbA1c < 6.5% (intensive control), HbA1c 6.5-7.5% (modest control), and HbA1c > 7.5% (poor control)]. The biventricular volume and function, as well as left ventricular (LV) systolic strains in patients in different HbA1c categories, were measured and compared. The primary and secondary outcomes were recorded. The association of different HbA1c levels with adverse outcomes was assessed. RESULTS: Despite similar biventricular ejection fractions, both patients with intensive and poor glycemic control exhibited prominent deterioration of LV systolic strain in the longitudinal component (P = 0.004). After a median follow-up of 35.0 months, 55 patients (21.0%) experienced at least one confirmed endpoint event. Cox multivariable analysis indicated that both patients in the lowest and highest HbA1c categories exhibited a more than 2-fold increase in the risk for primary outcomes [HbA1c < 6.5%: hazard ratio (HR) = 2.42, 95% confidence interval (CI) = 1.07-5.45; P = 0.033; HbA1c > 7.5%: HR = 2.24, 95% CI = 1.01-4.99; P = 0.038] and secondary outcomes (HbA1c < 6.5%: HR = 2.84, 95% CI = 1.16-6.96; P = 0.022; HbA1c > 7.5%: HR = 2.65, 95% CI = 1.08-6.50; P = 0.038) compared with those in the middle HbA1c category. CONCLUSIONS: We showed a U-shaped association of glycemic control with clinical outcomes in patients with T2DM and HFrEF, with the lowest risk of adverse outcomes among patients with modest glycemic control. HbA1c between 6.5% and 7.5% may be served as the optimal hypoglycemic target in this specific population.

The Impact of Resistance Exercise Training on Glycemic Control Among Adults with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: The prevalence of type 2 diabetes mellitus (T2DM) presents a challenge for health organizations because of its high likelihood of morbidity and mortality. There is an increasing body of evidence exploring the efficacy of resistance training (RT) alone on glycemic control. Objective: To update the effectiveness of RT on glycosylated hemoglobin (HbA1c) and fasting glucose in adults diagnosed with T2DM. Methods: CINAHL (EBSDCO), PubMed, MEDLINE (Ovid), and EMBASE (Ovid) databases were searched from inception to 30 January 2024. Published randomized controlled trials (RCTs) of adult humans with T2DM assessing the impact of RT on HbA1c and fasting glucose compared with control condition were included. Data were pooled by the inverse-variance method and reported as mean differences (MDs) with 95% confidence intervals (CIs). Results: Forty-six RCTs totaling 2130 participants met the inclusion criteria. Meta-analysis demonstrated RT significantly reduced HbA1c (MD -0.50% [95% CI, -0.67, -0.34 %], p < .00,001) and fasting glucose (MD -12.03 mg/dl [95% CI, -19.36, -4.69 mg/dl], p = .001). Subgroup analyses found that exercise training durations, gender, and risk of bias had statistically significant effects on HbA1c levels and fasting glucose concentrations after resistance training. However, meta-regression analyses revealed that variables including year of publication, number of sessions per week, mean sample age, sample size, and study quality scores did not significantly affect the change in either HbA1c or glucose. Conclusion: Our meta-analysis with meta-regression delivers further evidence that RT programs are effective approach in attenuation of HbA1c and fasting glucose in individuals with T2DM.

Gestational Diabetes and Subsequent Metabolic Dysfunction: An National Health and Nutrition Examination Survey Analysis (2011-2018).

Background: Gestational diabetes mellitus (GDM) complicates ∼10% of pregnancies, with the highest rates among Asian women. Evidence suggests that GDM is associated with an increased risk for future chronic health conditions, yet data for Asian women are sparse. We explored the association between prior GDM and metabolic dysfunction with nationally representative data to obtain Asian-specific estimates. Methods: For this cross-sectional study, data were drawn from the National Health and Nutrition Examination Survey for 7195 women with a prior pregnancy. GDM (yes/no) was defined using the question "During pregnancy, were you ever told by a doctor or other health professional that you had diabetes, sugar diabetes, or gestational diabetes?." Current metabolic dysfunction (yes/no) was based on having at least one of four indicators: systolic blood pressure (SBP, ≥130 mmHg), waist circumference (≥88 cm), high-density lipoprotein (HDL) cholesterol (<50 mg/dL), and glycosylated hemoglobin (HbA1c) (≥6.5%). Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between prior GDM and metabolic outcomes, overall and by race. Models included sampling weights and demographic and behavioral factors. Results: Overall, women with prior GDM had 46% greater odds of high waist circumference (OR: 1.5; 95% CI: 1.1-2.0) and 200% greater odds (OR: 3.0; 95% CI: 2.1-4.2) of high HbA1c. Prior GDM was not associated with high blood pressure or low HDL cholesterol. In race-specific analyses, prior GDM was associated with increased risk of elevated HbA1c among Asian (OR: 6.6; 95% CI: 2.5-17.2), Mexican American (OR: 3.0; 95% CI: 1.5-5.8), Black (OR: 3.0; 95% CI: 1.7-5.5), and White (OR: 2.6; 95% CI: 1.5-4.6) women. Prior GDM was associated with elevated SBP among Mexican American women and low HDL among Black women. Discussion: Prior GDM is associated with elevated HbA1c among all women, yet is a stronger predictor of elevated HbA1c among Asian women than other women. Race-specific associations between prior GDM and metabolic dysfunction were observed among Mexican American and Black women. Further research is warranted to understand the observed race/ethnic-specific associations.

Prediction of glycosylated hemoglobin level in patients with cardiovascular diseases and type 2 diabetes mellitus with respect to anti-diabetic medication.

Blood glycosylated hemoglobin level can be affected by various factors in patients with type 2 diabetes and cardiovascular diseases. Frequent measurements are expensive, and a suitable estimation method could improve treatment outcomes. Patients and methods: 93 patients were recruited in this research. We analyzed a number of parameters such as age, glucose level, blood pressure, Body Mass Index, cholesterol level, echocardiography et al. Patients were prescribed metformin. One group (n=60) additionally was taking sitagliptin. We applied eight machine learning methods (k nearest neighbors, Random Forest, Support Vector Machine, Extra Trees, XGBoost, Linear Regression including Lasso, and ElasticNet) to predict exact values of glycosylated hemoglobin in two years. Results: We applied a feature selection approach using step-by-step removal of them, Linear Regression on remaining features, and Pearson's correlation coefficient on the validation set. As a result, we got four different subsets for each group. We compared all eight Machine Learning methods using different hyperparameters on validation sets and chose the best models. We tested the best models on the external testing set and got R2 = 0.88, C Index = 0.857, Accuracy = 0.846, and MAE (Mean Absolute Error) = 0.65 for the first group, R2 = 0.86, C Index = 0.80, Accuracy = 0.75, and MAE = 0.41 for the second group. Conclusion: The resulting algorithms could be used to assist clinical decision-making on prescribing anti-diabetic medications in pursuit of achieving glycemic control.

Gender effect of glucose, insulin/glucagon ratio, lipids, and nitrogen-metabolites on serum HGF and EGF levels in patients with diabetes type 2.

Hepatocyte growth factor (HGF) exhibits potent growth-inducing properties across various tissues, while epidermal growth factor (EGF) acts as a molecular integration point for diverse stimuli. HGF plays a crucial role in hepatic metabolism, tissue repair, and offers protective effects on epithelial and non-epithelial organs, in addition to its involvement in reducing apoptosis and inflammation, underscoring its anti-inflammatory capabilities. The HGF-Met system is instrumental in hepatic metabolism and enhancing insulin sensitivity in animal diabetes models. Similarly, the EGF and its receptor tyrosine kinase family (EGFR) are critical in regulating cell growth, proliferation, migration, and differentiation in both healthy and diseased states, with EGF also contributing to insulin sensitivity. In this observational study, we aimed to identify correlations between serum levels of HGF and EGF, insulin, glucagon, glucose, and primary serum lipids in patients with type 2 diabetes mellitus (DM), taking into account the impact of gender. We noted differences in the management of glucose, insulin, and glucagon between healthy men and women, potentially due to the distinct influences of sexual hormones on the development of type 2 DM. Additionally, metabolites such as glucose, albumin, direct bilirubin, nitrites, and ammonia might influence serum levels of growth factors and hormones. In summary, our results highlight the regulatory role of insulin and glucagon in serum glucose and lipids, along with variations in HGF and EGF levels, which are affected by gender. This link is especially significant in DM, where impaired cell proliferation or repair mechanisms lead to metabolic changes. The gender-based differences in growth factors point to their involvement in the pathophysiology of the disease.

Can artificial intelligence detect type 2 diabetes in women by evaluating the pectoral muscle on tomosynthesis: diagnostic study.

OBJECTIVES: This retrospective single-center analysis aimed to evaluate whether artificial intelligence can detect type 2 diabetes mellitus by evaluating the pectoral muscle on digital breast tomosynthesis (DBT). MATERIAL METHOD: An analysis of 11,594 DBT images of 287 consecutive female patients (mean age 60, range 40-77 years) was conducted using convolutional neural networks (EfficientNetB5). The inclusion criterion was left-sided screening images with unsuspicious interpretation who also had a current glycosylated hemoglobin A1c (HBA1c) % value. The exclusion criteria were inadequate imaging, history of breast cancer, and/or diabetes mellitus. HbA1c values between 5.6 and 6.4% were categorized as prediabetic, and those with values ≥ 6.5% were categorized as diabetic. A recorded HbA1c ≤ 5.5% served as the control group. Each group was divided into 3 subgroups according to age. Images were subjected to pattern analysis parameters then cropped and resized in a format to contain only pectoral muscle. The dataset was split into 85% for training and 15% for testing the model's performance. The accuracy rate and F1-score were selected as performance indicators. RESULTS: The training process was concluded in the 15th epoch, each comprising 1000 steps, with an accuracy rate of 92% and a loss of only 0.22. The average specificity and sensitivity for all 3 groups were 95%. The F1-score was 0.95. AUC-ROC was 0.995. PPV was 94%, and NPV was 98%. CONCLUSION: Our study presented a pioneering approach, applying deep learning for the detection of diabetes mellitus status in women using pectoral muscle images and was found to function with an accuracy rate of 92%. CRITICAL RELEVANCE STATEMENT: AI can differentiate pathological changes within pectoral muscle tissue by assessing radiological images and maybe a potential diagnostic tool for detecting diabetes mellitus and other diseases that affect muscle tissues. KEY POINTS: • AI may have an opportunistic use as a screening exam for diabetes during digital breast tomosynthesis. • This technique allows for early and non-invasive detection of diabetes mellitus by AI. • AI may have broad applications in detecting pathological changes within muscle tissue.

Management of intervenable factors to reduce vascular complications in patients with internal carotid artery occlusion treated by non-emergency endovascular treatment.

Objective: This study aims to identify risk factors for vascular complications during non-emergency endovascular treatment in patients with internal carotid artery occlusion (ICAO) and to propose potential interventions. Method: A retrospective analysis of 92 patients with ICAO who received non-emergency endovascular treatment in our center from 1 January 2018 to 31 June 2023, was conducted. The correlation between intraoperative vascular complications and potential risk factors was studied, and interaction analysis was performed. Results: Our findings revealed that the use of non-neurology guide wires to open vessels (adjusted OR: 4.1, 95%CI: 1.3-12.8; p = 0.014) and glycosylated hemoglobin (HbA1c) ≥ 6.5 mmol/L (adjusted OR: 3.2, 95%CI: 1.2-8.9; p = 0.023) was significantly associated with vascular complications in non-emergency endovascular treatment of ICAO patients. The restricted cubic spline (RCS) showed that the higher the HbA1c level, the higher the risk of vascular complications. Conclusion: The use of non-neurology guide wires for vessel opening during non-emergency endovascular treatment in patients with ICAO increases the risk of vascular complications. Preoperative assessment and management of HbA1c levels can reduce the incidence of intraoperative vascular complications.

Mathematical model for assessing glycemic control in type 2 diabetes mellitus.

Glycated hemoglobin (HbA1c) and glycated albumin (GA) are vital markers for assessing glucose control in diabetes. This cross-sectional study involving 901 diagnosed type 2 diabetics aimed to compare calculated HbA1c, using the formula HbA1c = 2.6 + 0.03 x FBS (mg/dL), with directly measured HbA1c. Simultaneously, the study assessed the agreement between the two methods through regression analysis and explored correlations with various measures of glycemic control. The non-parametric Kolmogorov-Smirnov test indicated a non-normal data distribution, prompting appropriate statistical tests. Spearman's correlation coefficient revealed a strong correlation of calculated HbA1c, calculated GA, and estimated average glucose with measured parameters. Wilcoxon rank sum test indicated a significant difference between directly measured and calculated HbA1c (Z -9.487033, p < 0.0001). Passing Bablok regression analysis showed a significant deviation from linearity. Despite the potential cost benefits in resource-poor settings, caution is advised regarding interchangeable use of calculated and directly measured HbA1c in clinical decision-making. Data shows the importance of robust analytical methods in glycemic control assessment, offering insights for managing type 2 diabetes mellitus.

The glycosylated hemoglobin level and the severity of cardiovascular involvement in patients with the first episode of acute coronary syndrome.

Background: The current study was carried out aiming at investigating the relationship between glycosylated hemoglobin level and coronary atherosclerosis in patients with the first episode of acute coronary syndrome. Methods: This case-control study evaluated 450 patients with the first episode of acute coronary syndrome in Ayatollah Rouhani Hospital in Babol (Iran) from 2011 to 2018. Based on glycosylated hemoglobin, patients were divided into three groups of non-diabetic, pre-diabetic, and diabetic (n=150 in each group). Since SYNTAX score and Gensini score are employed to evaluate the extent of cardiovascular disease and predict CVD in patients with CAD over long-term follow-up, we calculated SYNTAX score and Gensini score based on angiographic results. Results: Concerning the factors related to the severity of cardiovascular involvement, the results revealed no significant difference between the diabetic and pre-diabetic groups in terms of the frequency of patients in terms of SYNTAX score, Gensini score, and the number of vessels involved (0.142 and 87, respectively, and P=0.102). However, this difference between the diabetic and non-diabetic groups, as well as between the pre-diabetic and non-diabetic groups was statistically significant (respectively for SYNTAX score, p< 0.001 and P=0.001; for Gensini score, P=0.013 and P=0.019; and for the number of vessels involved P=0.001and p<0.001). Conclusion: According to the findings of the current study, since there was no significant difference between diabetic and pre-diabetic patients in terms of the components indicating the severity of cardiovascular involvement, pre-diabetes itself may be associated with the severity of cardiovascular involvement as a predisposing factor.

Serum tumor markers expression (CA199, CA242, and CEA) and its clinical implications in type 2 diabetes mellitus.

BACKGROUND: Glucose and lipid metabolic disorder in patients with type 2 diabetes mellitus (T2DM) is associated with the levels of serum tumor markers of the digestive tract, such as cancer antigen (CA)199. Therefore, tumor markers in T2DM are important. AIM: To evaluate the expression of serum tumor markers [CA199, CA242, and car-cinoembryonic antigen (CEA)] and the clinical implications of the expression in T2DM. METHODS: For this observational study conducted at Hefei BOE Hospital, China, we enrolled 82 patients with first-onset T2DM and 51 controls between April 2019 and December 2020. Levels of fasting blood glucose (FBG), tumor markers (CA199, CEA, and CA242), glycosylated hemoglobin (HbA1c), etc. were measured and group index levels were compared. Moreover, FBG and HbA1c levels were correlated with tumor marker levels. Tumor markers were tested for diagnostic accuracy in patients with > 9% HbA1c using the receiver operating curve (ROC) curve. RESULTS: The T2DM group had high serum FBG, HbA1c, CA199, and CEA levels (P < 0.05). A comparative analysis of the two groups based on HbA1c levels (Group A: HbA1c ≤ 9%; Group B: HbA1c > 9%) revealed significant differences in CEA and CA199 levels (P < 0.05). The areas under the ROC curve for CEA and CA199 were 0.853 and 0.809, respectively. CA199, CEA, and CA242 levels positively correlated with HbA1c (r = 0.308, 0.426, and 0.551, respectively) and FBG levels (r = 0.236, 0.231, and 0.298, respectively). CONCLUSION: As compared to controls, serum CEA and CA199 levels were higher in patients with T2DM. HbA1c and FBG levels correlated with CA199, CEA, and CA242 levels. Patients with poorly controlled blood sugar must be screened for tumor markers.

Association between glycated hemoglobin and risk of all-cause mortality in community patients with type 2 diabetes: A prospective cohort study.

AIMS/INTRODUCTION: To analyze the association between HbA1c level and the risk of all-cause mortality in community patients with type 2 diabetes mellitus, and to provide a scientific basis for the management of type 2 diabetes mellitus in the community. MATERIALS AND METHODS: Based on a Zhejiang rural community type 2 diabetes mellitus cohort, a total of 10,310 patients with type 2 diabetes mellitus with complete baseline and follow-up data were selected. The Cox proportional hazards regression model and the restricted cubic spline model were used to evaluate the relationship between the HbA1c level and the risk of all-cause mortality. RESULTS: During a mean follow-up of 5.5 years, 971 patients died. With HbA1c levels of 6.5-7.0% as the reference, after adjusting for relevant confounding factors, the HR(95%CI) of all-cause mortality with HbA1c levels of <5.5%, 5.5-6.5%, 7.0-8.0%, 8.0-9.0%, and ≥9.0% were 1.53 (1.08-2.15), 0.97 (0.79-1.21), 1.14 (0.92-1.41), 1.44 (1.14-1.83), and 2.08 (1.68-2.58), respectively. The HbA1c level was associated with the risk of all-cause mortality in a "J-shaped" manner. The risk of all-cause mortality was lowest when the HbA1c was 6.5-7.0%, and increased significantly when the HbA1c was ≥ 8.0% and the HbA1c was < 5.5% (P < 0.05). The risk of all-cause death in the HbA1c 5.5-6.5% group and the 7.0-8.0% group was not significant compared with the reference group (P > 0.05). CONCLUSIONS: The HbA1c levels were associated with the risk of all-cause mortality in type 2 diabetes mellitus in a "J-shaped" manner, a too high or a too low HbA1c level could increase the risk of death. Attention should be paid to the individual evaluation of patients and the setting of appropriate glycemic control goals.

Correlation analysis of diabetes based on Copula.

Introduction: The ratio of Triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) is a crucial indicator for diabetes diagnosis. Methods: This study utilizes the Copula function to model and fit the non-linear correlation among fasting blood glucose (Glu), glycosylated hemoglobin (HbA1C), and TG/HDL-C in patients with diabetes. The Copula function chosen for this study includes the two-dimensional Archimedes and Elliptical distribution family, as well as the multidimensional Vine Copula function, for fitting the data. The evaluation of the fitting effect is performed using the mean absolute error (MAE) and mean square error (MSE). Results: The results indicate that the Clayton Copula exhibits the highest effectiveness in fitting the pairwise relationship between Glu and TG/HDL-C, as well as HbA1C and TG/HDL-C, displaying the smallest fitting error. Additionally, the Vine Copula function produces a satisfactory fit for the relationship among all three indicators. Compared to linear analysis methods, the Copula function more accurately depicts the correlation among these three types of indicators. Discussion: Moreover, our findings indicate a stronger correlation in the lower tail between Glu and HbA1C, as well as TG/HDL-C, suggesting that the Copula function provides greater accuracy and applicability in depicting the relationship among these indicators. As a result, it can offer a more precise auxiliary diagnosis and serve as a valuable reference in clinical judgment.

Associations of glycosylated hemoglobin, pre-diabetes, and type 2 diabetes with incident lung cancer: A large prospective cohort study.

BACKGROUND: The association of pre-diabetes and type 2 diabetes (T2D) with incident lung cancer is uncertain, and the incident risk across the glycemic spectrum is unclear. We aimed to explore the associations of glycosylated hemoglobin (HbA1c), pre-diabetes, and T2D with incident lung cancer in a large prospective cohort. METHODS: Leveraging a total of 210,779 cancer-free adults recruited in the UK Biobank between 2006 and 2010. We performed multivariable Cox proportional hazards models and restricted cubic spline methods to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations of HbA1c, pre-diabetes, and T2D with incident lung cancer. RESULTS: During a median follow-up of 11.06 years, 1738 incident lung cancer cases were ascertained. The incidence of lung cancer was 20% higher among people with diabetes (HR: 1.20, 95% CI: 1.02 to 1.42) and 38% higher among people with pre-diabetes (HR: 1.38, 95% CI: 1.15 to 1.65). After dividing people with diabetes by whether taking antidiabetic medications, the incidence was 28% higher among people with diabetes without medications (HR: 1.28, 95% CI: 1.02 to 1.61) and 15% higher among people with diabetes with medications (HR: 1.15, 95% CI: 0.93 to 1.41). The increased risk of incident lung cancer for each standard deviation (6.45 mmol/mol) increase in HbA1c was more pronounced across HbA1c values of 32-42 mmol/mol (HR: 1.37, 95% CI: 1.18 to 1.59). The risk was more pronounced among participants <60 years. CONCLUSIONS: Pre-diabetes and T2D are associated with an increased incidence of lung cancer. The increased risk of incident lung cancer is more pronounced across HbA1c values of 32-42 mmol/mol, which are currently considered normal values.