Search Results (19)

Cancer risk increases by 25 to 250% not only in dysmetabolic obese or overweight people with overt type 2 diabetes but also in individuals with intermediate hyperglycemia (pre-diabetes), with especially pronounced risk of pancreatic or hepatocellular cancer and obesity-related cancers, e.g., colorectal and kidney cancers, bladder cancer in men, and endometrial and breast cancers in women. Cancer may often be present before or upon the diagnosis of diabetes, as there is a common pathogenetic dysmetabolic–inflammatory background with insulin resistance for developing diabetes, cardiorenal disease, and cancer in parallel. The mechanisms involved relate to hyperinsulinemia as a potential carcinogenic priming event with ectopic visceral, hepatic, pancreatic, or renal fat accumulation that subsequently fuel inflammation and lipo-oncogenic signals, causing mitochondrial oxidative stress and deregulation. Moreover, hyperinsulinemia may foster mitogenic MAP kinase-related signaling, which can also occur via IGF1 receptors due to increased free IGF1 levels in obesity. Weight reduction of 10% or more in obese people with diabetes or pre-diabetes, e.g., through intensive lifestyle intervention or bariatric (=metabolic) surgery or through treatment with GLP-1 receptor agonists or metformin, is associated with significantly lower incidence of “diabesity”-associated cancers. In conclusion, there seems to be huge utility in adopting the new “Cardio-Renal-Metabolic-Cancer Syndrome” approach, also looking for cancer at the time of diabetes diagnosis in addition to proactively screening for undiagnosed dysglycemia. Full article

Objective: This study aimed to investigate the utilization of patterns derived from physical activity monitoring (PAM) for the identification of individuals at risk of type 2 diabetes mellitus (T2DM) through an at-home screening approach employing machine learning techniques. Methods: Data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES) were scrutinized, focusing on the PAM component. The primary objective involved the identification of diabetes, characterized by an HbA1c ≥ 6.5% (48 mmol/mol), while the secondary objective included individuals with prediabetes, defined by an HbA1c ≥ 5.7% (39 mmol/mol). Features derived from PAM, along with age, were utilized as inputs for an XGBoost classification model. SHapley Additive exPlanations (SHAP) was employed to enhance the interpretability of the models. Results: The study included 7532 subjects with both PAM and HbA1c data. The model, which solely included PAM features, had a test dataset ROC-AUC of 0.74 (95% CI = 0.72–0.76). When integrating the PAM features with age, the model’s ROC-AUC increased to 0.79 (95% CI = 0.78–0.80) in the test dataset. When addressing the secondary target of prediabetes, the XGBoost model exhibited a test dataset ROC-AUC of 0.80 [95% CI; 0.79–0.81]. Conclusions: The objective quantification of physical activity through PAM yields valuable information that can be employed in the identification of individuals with undiagnosed diabetes and prediabetes. Full article

Introduction: Undiagnosed diabetes poses significant public health challenges in Ghana. Numerous factors may influence the prevalence of undiagnosed diabetes among adults, and therefore, using a model that takes into account the intricate network of these relationships should be considered. Our goal was to evaluate fasting plasma levels, a critical indicator of diabetes, and the associated direct and indirect associated or protective factors. Methods: This research employed a cross-sectional survey to sample 1200 adults aged 25–70 years who perceived themselves as healthy and had not been previously diagnosed with diabetes from 13 indigenous communities within the Cape Coast Metropolis, Ghana. Diabetes was diagnosed based on the American Diabetes Association (ADA) criteria for fasting plasma glucose, and lipid profiles were determined using Mindray equipment (August 2022, China). A stepwise WHO questionnaire was used to collect data on sociodemographic and lifestyle variables. We analyzed the associations among the exogenous, mediating, and endogenous variables using a generalized structural equation model (GSEM). Results: Overall, the prevalence of prediabetes and diabetes in the Cape Coast Metropolis was found to be 14.2% and 3.84%, respectively. In the sex domain, females had a higher prevalence of prediabetes (15.33%) and diabetes (5.15%) than males (12.62% and 1.24%, respectively). Rural areas had the highest prevalence, followed by peri-urban areas, whereas urban areas had the lowest prevalence. In the GSEM results, we found that body mass index (BMI), triglycerides (TG), systolic blood pressure (SBP), gamma-glutamyl transferase (GGT), and female sex were direct predictive factors for prediabetes and diabetes, based on fasting plasma glucose (FPG) levels. Indirect factors influencing diabetes and prediabetes through waist circumference (WC) included childhood overweight status, family history, age 35–55 and 56–70, and moderate and high socioeconomic status. High density lipoprotein (HDL) cholesterol, childhood overweight, low physical activity, female sex, moderate and high socioeconomic status, and market trading were also associated with high BMI, indirectly influencing prediabetes and diabetes. Total cholesterol, increased TG levels, WC, age, low physical activity, and rural dwellers were identified as indirectly associated factors with prediabetes and diabetes through SBP. Religion, male sex, and alcohol consumption were identified as predictive factors for GGT, indirectly influencing prediabetes and diabetes. Conclusions: Diabetes in indigenous communities is directly influenced by blood lipid, BMI, SBP, and alcohol levels. Childhood obesity, physical inactivity, sex, socioeconomic status, and family history could indirectly influence diabetes development. These findings offer valuable insights for policymakers and health-sector stakeholders, enabling them to understand the factors associated with diabetes development and implement necessary public health interventions and personalized care strategies for prevention and management in Ghana. Full article

Maturity-onset diabetes of the young (MODY) is part of the heterogeneous group of monogenic diabetes (MD) characterized by the non-immune dysfunction of pancreatic β-cells. The diagnosis of MODY still remains a challenge for clinicians, with many cases being misdiagnosed as type 1 or type 2 diabetes mellitus (T1DM/T2DM), and over 80% of cases remaining undiagnosed. With the introduction of modern technologies, important progress has been made in deciphering the molecular mechanisms and heterogeneous etiology of MD, including MODY. The aim of our study was to identify genetic variants associated with MODY in a group of patients with early-onset diabetes/prediabetes in whom a form of MD was clinically suspected. Genetic testing, based on next-generation sequencing (NGS) technology, was carried out either in a targeted manner, using gene panels for monogenic diabetes, or by analyzing the entire exome (whole-exome sequencing). GKC-MODY 2 was the most frequently detected variant, but rare forms of KCNJ11-MODY 13, specifically, HNF4A-MODY 1, were also identified. We have emphasized the importance of genetic testing for early diagnosis, MODY subtype differentiation, and genetic counseling. We presented the genotype–phenotype correlations, especially related to the clinical evolution and personalized therapy, also emphasizing the particularities of each patient in the family context. Full article

More than 25% of older adults in Europe have diabetes mellitus. It is estimated that 45% of patients with diabetes are currently undiagnosed, which is a known risk factor for perioperative morbidity. We investigated whether routine HbA1c screening in older adult patients undergoing surgery would identify patients with undiagnosed diabetes. We included patients aged ≥65 years without a diagnosis of diabetes who visited the preoperative assessment clinic at the Amsterdam University Medical Center and underwent HbA1c screening within three months before surgery. Patients undergoing cardiac surgery were excluded. We assessed the prevalence of undiagnosed diabetes (defined as HbA1c ≥ 48 mmol·mol⁻¹) and prediabetes (HbA1c 39–47 mmol·mol⁻¹). Using a multivariate regression model, we analysed the ability of HbA1c to predict days alive and at home within 30 days after surgery. From January to December 2019, we screened 2015 patients ≥65 years at our clinic. Of these, 697 patients without a diagnosis of diabetes underwent HbA1c screening. The prevalence of undiagnosed diabetes and prediabetes was 3.7% (95%CI 2.5–5.4%) and 42.9% (95%CI 39.2–46.7%), respectively. Preoperative HbA1c was not associated with days alive and at home within 30 days after surgery. In conclusion, we identified a small number of patients with undiagnosed diabetes and a high prevalence of prediabetes based on preoperative HbA1c screening in a cohort of older adults undergoing non-cardiac surgery. The relevance of prediabetes in the perioperative setting is unclear. Screening for HbA1c in older adult patients undergoing non-cardiac surgery does not appear to help predict postoperative outcome. Full article

Background: To identify people at risk of type 2 diabetes. Primary health care needs efficient and noninvasive screening tools to detect individuals in need of follow-up to promote health and well-being. Previous research has shown people with lower levels of health literacy and/or well-being scores are vulnerable but may benefit from intervention and follow-up care. Aims: This cross-sectional study, aimed to identify people at risk for type 2 diabetes by comparing the Finnish Diabetes Risk instrument with the waist-to-height ratio. Further, the difference was examined in health literacy and well-being scale scores in the countryside versus town areas, respectively. Results: In total, 220, aged 18–75 years, participated. Thereof, 13.2% displayed biomarkers at prediabetes level of HbA1c (39–47 mmol/mol); none had undiagnosed diabetes. Of the participants, 73% were overweight or obese. Waist-to-height ratio demonstrated 93.1% of the prediabetes group at moderate to high health risk and 64.4% of the normal group, with an area under the curve of 0.759, sensitivity of 93.3%, and specificity of 63.1%. Residency did not influence prediabetes prevalence, health literacy, or well-being. Conclusion: Waist-to-height ratio and the Finnish Diabetes Risk instrument may be suitable for identifying who need further tests and follow-up care for health promotion in primary care. Full article

Early detection of pre-diabetes (pre-DM) can prevent DM and related complications. This review examined studies on non-laboratory-based pre-DM risk prediction tools to identify important predictors and evaluate their performance. PubMed, Embase, MEDLINE, CINAHL were searched in February 2023. Studies that developed tools with: (1) pre-DM as a prediction outcome, (2) fasting/post-prandial blood glucose/HbA1c as outcome measures, and (3) non-laboratory predictors only were included. The studies’ quality was assessed using the CASP Clinical Prediction Rule Checklist. Data on pre-DM definitions, predictors, validation methods, performances of the tools were extracted for narrative synthesis. A total of 6398 titles were identified and screened. Twenty-four studies were included with satisfactory quality. Eight studies (33.3%) developed pre-DM risk tools and sixteen studies (66.7%) focused on pre-DM and DM risks. Age, family history of DM, diagnosed hypertension and obesity measured by BMI and/or WC were the most common non-laboratory predictors. Existing tools showed satisfactory internal discrimination (AUROC: 0.68–0.82), sensitivity (0.60–0.89), and specificity (0.50–0.74). Only twelve studies (50.0%) had validated their tools externally, with a variance in the external discrimination (AUROC: 0.31–0.79) and sensitivity (0.31–0.92). Most non-laboratory-based risk tools for pre-DM detection showed satisfactory performance in their study populations. The generalisability of these tools was unclear since most lacked external validation. Full article

Gestational diabetes mellitus (GDM) is currently the most common complication of pregnancy and is defined as a glucose intolerance disorder with recognition during pregnancy. GDM is considered a uniform group of patients in conventional guidelines. In recent years, evidence of the disease’s heterogeneity has led to a growing understanding of the value of dividing patients into different subpopulations. Furthermore, in view of the increasing incidence of hyperglycemia outside pregnancy, it is likely that many cases diagnosed as GDM are in fact patients with undiagnosed pre-pregnancy impaired glucose tolerance (IGT). Experimental models contribute significantly to the understanding of the pathogenesis of GDM and numerous animal models have been described in the literature. The aim of this review is to provide an overview of the existing mouse models of GDM, in particular those that have been obtained by genetic manipulation. However, these commonly used models have certain limitations in the study of the pathogenesis of GDM and cannot fully describe the heterogeneous spectrum of this polygenic disease. The polygenic New Zealand obese (NZO) mouse is introduced as a recently emerged model of a subpopulation of GDM. Although this strain lacks conventional GDM, it exhibits prediabetes and an IGT both preconceptionally and during gestation. In addition, it should be emphasized that the choice of an appropriate control strain is of great importance in metabolic studies. The commonly used control strain C57BL/6N, which exhibits IGT during gestation, is discussed in this review as a potential model of GDM. Full article

Obstructive sleep apnea (OSA) is a common but largely undiagnosed clinical condition, which is turning into a serious public health issue. Of note is that its prevalence is gradually increasing in parallel with the obesity and type 2 diabetes mellitus (T2DM) epidemics. The aim of this article is to comprehensively review the literature in order to evaluate the cardiovascular (CV) risk among patients with OSA and prediabetes or T2DM. OSA seems to be an independent risk factor for the development as well as the progression of T2DM, whereas it is associated with T2DM-related macrovascular and microvascular complications. OSA may also act as a potential risk factor for the presentation and development of CV disease, such as hypertension, coronary artery disease, heart failure, pulmonary hypertension, atrial fibrillation and other cardiac arrythmias, as well as stroke. OSA and T2DM also share common pathophysiological mechanisms leading to atherosclerosis. Considering that the coexistence of OSA and T2DM is an independent and cumulative risk factor for CV mortality, more so than the two diseases separately, clinicians and healthcare professionals should be aware of and screen for OSA in patients with T2DM. Notably, targeted therapy for both conditions seems to substantially improve CV prognosis. Full article

Type 2 diabetes mellitus (T2DM) is a major global health issue. The development of T2DM is gradual and preceded by the pre-diabetes mellitus (pre-DM) stage, which often remains undiagnosed. This study aimed to identify novel pre-DM biomarkers in a high-fat diet (HFD)-induced pre-DM mouse model. Male C57BL/6J mice were fed either a chow diet or HFD for 12 weeks. Serum and liver samples were isolated in a time-dependent manner. Semi-quantitative assessment of secretory cytokines was performed by cytokine array analysis, and 13 cytokines were selected for further analysis based on the changes in expression levels in the pre-DM and T2DM stages. HFD-fed mice gained body weight and exhibited high serum lipid, liver enzyme, glucose, and insulin levels during the progression of pre-DM to T2DM. The mRNA expression of inflammatory and lipogenic genes was elevated in HFD-fed mice The mRNA expression of Fc receptor, IgG, low affinity Iib, lectin, galactose binding, soluble 1, vascular cell adhesion molecule 1, insulin-like growth factor binding protein 5, and growth arrest specific 6 was elevated in the pre-DM, which was confirmed by measuring protein levels. Our study identified novel pre-DM biomarkers that may help to delay or prevent the progression of T2DM. Full article

Background: Diagnostic concordance between HbA1c and other glucose-based tests is imperfect, and data on this problem in acute coronary syndrome (ACS) are still lacking. The aim of this study was to identify undiagnosed glucose abnormalities in ACS patients, and to compare the effectiveness and consistency of the diagnostic screening based on HbA1c to the oral glucose tolerance test (OGTT). Methods: The study group consisted of 121 ACS patients, mean age 62.3 ± 11.6 years, without known glucose abnormalities. HbA1c, admission and fasting plasma glucose in the first days of hospitalization were assessed and referred to the results of OGTT performed two weeks after discharge. Results: OGTT identified normoglycemia in 45%, pre-diabetes in 39.4%, and diabetes in 15.6%, while HbA1c revealed these categories in 39.7%, 51.2%, and 9.1%, respectively. With an HbA1c cut-off ≥6.5% (48 mmol/mol) diagnostic for diabetes, the sensitivity of the method was 41%, while specificity was 98%, compared to the OGTT. The optimal HbA1c cut-off value at the crossing of sensitivity and specificity curves was 5.9%. The HbA1c value recommended for the diagnosis of pre-diabetes and optimal cut-off point were the same (5.7%). Conclusions: Using HbA1c without OGTT in an early but stable phase of ACS may result in a significant underdiagnosis of diabetes. Full article

Dysglycemia is a public health challenge for the coming decades, especially in patients with chronic coronary syndromes (CCS). We want to assess the prevalence of undiagnosed diabetes mellitus (DM) and prediabetes, as well as identify factors associated with the development of dysglycaemia in patients with CCS. In total, 1233 study participants (mean age 69 ± 9 years), who, between 6 and 18 months earlier were hospitalized for acute coronary syndrome or elective revascularization, were examined (71.4% men). The diagnosis of DM, impaired fasting glucose (IFG), impaired glucose tolerance (IGT) have been made according to World Health Organization (WHO) criteria. Based on the oral glucose tolerance test (OGTT) results, DM has been newly diagnosed in 28 (5.1%, mean age 69.9 ± 8.4 years) patients, 75% were male (n = 21). Prediabetes has been observed in 395 (72.3%) cases. IFG was found in 234 (42.9%) subjects, 161 (29.5%) individuals had IGT. According to multinomial logistic regression, body mass index (BMI) and high-density lipoprotein cholesterol (HDL-C) should be considered when assessing risk of development of dysglycaemia after discharge from the hospital. Among people with previously diagnosed DM, a significantly higher percentage were willing to change their lifestyles after the index event compared to other patients. Patients with chronic coronary syndromes suffer a very high frequency of dysglycaemia. Most patients with chronic coronary syndromes, especially those with high BMI or low HDL-C, should be considered for screening for dysglycemia using OGTT within the first year after hospitalization. A higher percentage of patients who were aware of their diabetic status changed their lifestyles, which added the benefit of timely diagnosis and treatment of diabetes. Full article

Background and objectives. In forensic medicine, the postmortem determination of glycated hemoglobin (HbA1c) helps identify undiagnosed cases of diabetes or cases with uncontrolled glycemic status. In order to contribute to the solidification of thanatochemistry, both globally and especially nationally, we aimed to determine this biomarker postmortem, for the first time in our institution, in order to identify undiagnosed pre-mortem diabetics, as well as those with inadequate glycemic control. Materials and Methods. Our research consisted of analyzing a total number of 180 HbA1c values, 90 determinations from the peripheral blood and 90 from the central blood. The determination of HbA1c was performed by means of a fully automatic analyzer (HemoCue HbA1c 501), certified by the National Glycohemoglobin Standardization Program (NGSP)/Diabetes Control and Complications Trial (DCCT) and calibrated according to the standards developed by the International Federation of Clinical Chemistry (IFCC). According to ADA criteria, HbA1c values can provide us with the following information about the diagnosis of diabetes: normal 4.8–5.6%; prediabetes 5.7–6.4%; diabetes ≥ 6.5%. Results. A considerable number of cases with an altered glycemic status (cases that had HbA1c values equal to or greater than 5.7%) were identified—51% demonstrable by peripheral blood determinations and 41% by central blood determinations. Notably, 23 people with diabetes (25%) were identified by analyzing the peripheral blood; 18 other people with diabetes (20%) were identified by analyzing the central blood. Conclusions. Our study managed to confirm the antemortem diagnosis of DM using a simple point-of-care analyzer and applying standardized and certified criteria on HbA1c levels measured postmortem. We also identified a considerable number of cases with DM in patients with no antemortem history of glucose imbalance—at least 20% more cases. Although the two different sites used for blood collection showed a strong statistical correlation, it seems that the peripheral site could have a higher sensibility in detecting postmortem altered glycemic status. Full article

This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis. Full article

Over a third of adults in the United States have prediabetes, and many of those with prediabetes will progress to type 2 diabetes within 3–5 years. Health insurance status may factor into a proper diagnosis of prediabetes and diabetes. This study sought to determine the associations between health insurance and undiagnosed prediabetes and diabetes in a national sample of American adults. Publicly available data from 13,029 adults aged 18–64 years from the 2005–2016 waves of the National Health and Nutrition Examination Survey were analyzed. Health insurance type (Medicaid, Private, Other, None) was self-reported. Prediabetes and diabetes status were assessed with measures of self-report, glycohemoglobin, fasting plasma glucose, and two-hour glucose. Covariate-adjusted logistic models were used for the analyses. Overall, 5976 (45.8%) participants had undiagnosed prediabetes, while 897 (6.8%) had undiagnosed diabetes. Having health insurance was associated with decreased odds ratios for undiagnosed prediabetes: 0.87 (95% confidence interval (CI: 0.79, 0.95)) for private insurance, 0.84 (CI: 0.73, 0.95) for other insurance, and 0.78 (CI: 0.67, 0.90) for Medicaid. Moreover, having private health insurance was associated with 0.82 (CI: 0.67, 0.99) decreased odds for undiagnosed diabetes. Health insurance coverage and screening opportunities for uninsured individuals may reduce prediabetes and diabetes misclassifications. Full article