Risk factors for Charcot foot development in individuals with diabetes mellitus.

AIMS/HYPOTHESIS: Charcot foot is a complication of diabetes mellitus that has potentially disastrous consequences. Although it was first described in 1868 and found to be associated with diabetes in 1936, there is still uncertainty about the risk factors affecting the development of the condition. Here, we aim to identify risk factors for Charcot foot in a nationwide cohort study. METHODS: A retrospective register-based cohort study was performed for the period 2001-2016, using nationwide registries. Individuals with diabetes and Charcot foot were identified and matched by diabetes type and with similar diabetes duration with individuals with diabetes but not Charcot foot. Logistic regression analyses were used to identify risk factors. RESULTS: A total of 3397 participants with diabetes mellitus and Charcot foot and 27,662 control participants with diabetes but without Charcot foot were included. HbA1c, duration of diabetes, micro- and macroalbuminuria, retinopathy and atherosclerosis (general and peripheral) were identified as risk factors for Charcot foot in participants with type 1 diabetes and participants with type 2 diabetes. CONCLUSIONS/INTERPRETATION: In the most extensive study on Charcot foot to date, we identified distinctive and common risk factors associated with the development of Charcot foot in individuals with type 1 diabetes and type 2 diabetes.

Metabolic health in people living with type 1 diabetes in Belgium: a repeated cross-sectional study.

AIMS/HYPOTHESIS: Metabolic abnormalities such as central obesity, insulin resistance, dyslipidaemia and hypertension, often referred to as 'the metabolic syndrome' (or 'combined metabolic abnormalities'), are increasingly being identified in people living with type 1 diabetes, accelerating the risk for CVD. As a result, in recent years, treatment in people living with type 1 diabetes has shifted to improving overall metabolic health rather than glucose control alone. In Belgium, diabetes care for people living with type 1 diabetes is centrally organised. The Initiative for Quality Improvement and Epidemiology in Diabetes, imposed by the Belgian health insurance system, has systematically collected data from patients on intensive insulin therapy treated in all 101 diabetes clinics in Belgium since 2001. The aim of this real-world study is to describe the evolution of treatment and metabolic health, including the prevalence of obesity and combined metabolic abnormalities, in people living with type 1 diabetes over the past 20 years, and to compare the treatment and prevalence of complications between those with and without combined metabolic abnormalities. METHODS: We analysed data on adults (≥16 years old) living with type 1 diabetes, who were diagnosed at age ≤45 years and who had a diabetes duration ≥1 year, collected between 2001 and 2022. The evolution of HbA1c, BMI, LDL-cholesterol, systolic BP, lipid-lowering therapy and antihypertensive therapy over time was analysed. The prevalence of individual and multiple metabolic abnormalities according to various definitions of the metabolic syndrome/combined metabolic abnormalities was analysed, and the association between combined metabolic abnormalities and metabolic health indicators, complications and treatment was investigated in the 2022 data. RESULTS: The final dataset consisted of 26,791 registrations of adults living with type 1 diabetes collected between 2001 and 2022. Although glycaemic and lipid control generally improved over time, the prevalence of obesity strongly increased (12.1% in 2001 vs 21.7% in 2022, p<0.0001), as did the presence of combined metabolic abnormalities (WHO criteria: 26.9% in 2001 vs 42.9% in 2022 in women, p<0.0001; 30.4% in 2001 vs 52.1% in 2022 in men, p<0.0001; WHO criteria without albuminuria: 22.3% in 2001 vs 40.6% in 2022 in women, p<0.0001; 25.1% in 2001 vs 49.2% in 2022 in men, p<0.0001; NCEP-ATPIII criteria: 39.9% in 2005 vs 57.2% in 2022 in women, p<0.0001; 40.8% in 2005 vs 60.9% in 2022 in men, p<0.0001; IDF criteria: 43.9% in 2005 vs 59.3% in 2022 in women, p<0.001; 33.7% in 2005 vs 50.0% in 2022 in men, p<0.0001). People with combined metabolic abnormalities had higher glucose levels compared to those without combined metabolic abnormalities (HbA1c >58 mmol in men: 48.9% vs 36.9%; HbA1c >58 mmol in women: 53.3% vs 41.1%, p<0.0001). People with combined metabolic abnormalities were more often treated with adjunct therapies such as metformin, sodium-glucose transport protein 2 inhibitors and glucagon-like peptide-1 receptor agonists. In both men and women, the presence of combined metabolic abnormalities was strongly related to the presence of eye complications, peripheral neuropathy, chronic kidney disease and CVD, corrected for age, diabetes duration and HbA1c. CONCLUSIONS/INTERPRETATION: Overweight, obesity and combined metabolic abnormalities are increasingly being identified in people living with type 1 diabetes, further accelerating the risk of microvascular and macrovascular complications. Early identification of the presence of combined metabolic abnormalities should enable therapeutic interventions to be modified towards multifactorial approaches, with attention to education on avoidance of overweight (e.g. dietary counselling) in addition to strict glycaemic control and intensification of use of antihypertensive agents and statins. Use of adjunct therapies in this population as a tool should be explored more thoroughly to reduce risk of complications.

Heterogeneity of glycaemic phenotypes in type 1 diabetes.

AIMS/HYPOTHESIS: Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS: In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS: We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION: Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

Enhanced lung endothelial glycolysis is implicated in the development of severe pulmonary hypertension in type 2 diabetes.

Metabolic abnormalities in pulmonary endothelial cells are implicated in pulmonary hypertension (PH) while increasing evidence shows the influence of diabetes on progressing PH. In this study, we examined the effect of type 2 diabetes on hypoxia-induced PH and investigated its molecular mechanisms using hypoxia-induced diabetic male mice. Chronic hypoxia led to a more severe PH in type 2 diabetic mice than in control mice. Next, we compared gene expression patterns in isolated pulmonary endothelial cells (MPECs) from control mice in normoxia (CN), diabetic mice in normoxia (DN), control mice exposed to hypoxia (CH), and diabetic mice exposed to hypoxia (DH). The results showed that expression levels of 27 mRNAs, out of 92 mRNAs, were significantly different among the four groups. Two glycolysis-related proteins, GAPDH and HK2, were increased in MPECs of DH mice compared to those in DN or CH mice. In addition, the levels of pyruvate and lactate (glycolysis end products) were significantly increased in MPECs of DH mice, but not in CH mice, compared to MPECs of CN mice. Augmentation of glycolysis by terazosin exacerbated hypoxia-induced PH in CH mice but not in DH mice. On the contrary, inhibiting GAPDH (a key enzyme of the glycolytic pathway) by koningic acid ameliorated hypoxia-induced PH in DH mice but had no effect in CH mice. These data suggest that enhanced glycolysis in diabetic mice is involved in severe hypoxia-induced PH, and glycolysis inhibition is a potential target to reduce the severe progression of PH in diabetic patients.

Pancreas Β-Cells in Type 1 and Type 2 Diabetes: Cell Death, Oxidative Stress and Immune Regulation. Recently Appearing Changes in Diabetes Consequences.

Diabetes mellitus type 1 (T1D) and type 2 (T2D) develop due to dysfunction of the Langerhans islet ß-cells in the pancreas, and this dysfunction is mediated by oxidative, endoplasmic reticulum (ER), and mitochondrial stresses. Although the two types of diabetes are significantly different, ß-cell failure and death play a key role in the pathogenesis of both diseases, resulting in hyperglycemia due to a reduced ability to produce insulin. In T1D, ß-cell apoptosis is the main event leading to hyperglycemia, while in T2D, insulin resistance results in an inability to meet insulin requirements. It has been suggested that autophagy promotes ß-cell survival by delaying apoptosis and providing adaptive responses to mitigate the detrimental effects of ER stress and DNA damage, which is directly related to oxidative stress. As people with diabetes are now living longer, they are more susceptible to a different set of complications. There has been a diversification in causes of death, whereby a larger proportion of deaths among individuals with diabetes is attributable to nonvascular conditions; on the other hand, the proportion of cancer-related deaths has remained stable or even increased in some countries. Due to the increasing cases of both T1D and T2D, these diseases become even more socially significant. Hence, we believe that search for any opportunities for control of this disease is an overwhelmingly important target for the modern science. We focus on two differences that are characteristic of the development of diabetes's last periods. One of them shows that all-cause death rates have declined in several diabetes populations, driven in part by large declines in vascular disease mortality but large increases in oncological diseases. Another hypothesis is that some T2D medications could be repurposed to control glycemia in patients with T1D.

Evaluation of the Steno Type 1 Risk Engine in predicting cardiovascular events in an ethnic mixed population of type 1 diabetes mellitus and its association with chronic microangiopathy complications.

BACKGROUND: The Steno Type 1 Risk Engine (ST1RE) was developed to aid clinical decisions in primary prevention for individuals with type 1 diabetes (T1D), as existing cardiovascular (CV) risk models for the general population and type 2 diabetes tend to underestimate CV risk in T1D. However, the applicability of ST1RE in different populations remains uncertain, as prediction models developed for one population may not accurately estimate risk in another. This study aimed to evaluate the performance of the ST1RE in predicting CV events among ethnically mixed T1D individuals and its association with the progression of microangiopathy complications. METHODS: A retrospective survey of 435 adults with T1D who were free of CV events at baseline was assessed by ST1RE and chronic diabetes complications at 5 and 10 years of follow-up. The estimated CV risk rates were compared with the observed rates at 5 and 10 years using statistical analyses, including Receiver Operating Characteristic (ROC) curve analysis, Hosmer-Lemeshow test, Kaplan-Meier curves analysis and Cox-regression models. RESULTS: Among 435 patients (aged 25 years; interquartile range [IQR]: 21-32) with a median T1D duration of 13 years (IQR: 9-18), only 5% were categorized into the high ST1RE group. Within a median follow-up of 9.2 years (IQR 6.0-10.7), 5.5% of patients experienced a CV event (1.6%, 14.9%, and 50% from the low, moderate, and high-risk groups, respectively). The hazard ratios (HRs) for CV events were greater in the high-risk group (HR 52.02; 95% CI 18.60-145.51, p < 0.001) and in the moderate-risk group (HR 8.66; 95% CI 2.90-25.80, p < 0.001) compared to the low-risk group. The ST1RE estimated CV events were similar to the observed at 5 years (3.4% vs. 3.5%; χ2 = 10.12, p = 0.899) and 10 years (6.8% vs. 9.9%; χ2 = 14.80, p = 0.676) of follow-up. The progression of microangiopathies was greater in the high vs. low for retinopathy (p = 0.008), diabetic kidney disease (p < 0.001), peripheral neuropathy (p = 0.021), and autonomic neuropathy (p = 0.008). CONCLUSIONS: ST1RE performed well in predicting CV events at 5 and 10 years of follow-up. Moreover, higher ST1RE scores were associated with the progression of microangiopathy complications in this genetically heterogeneous T1D population.

Pathogenic mechanisms, diagnostic, and therapeutic potential of microvesicles in diabetes and its complications.

Extracellular vesicles (EVs), particularly microvesicles (MVs), have gained significant attention for their role as mediators of intercellular communication in both physiological and pathological contexts, including diabetes mellitus (DM) and its complications. This review provides a comprehensive analysis of the emerging roles of MVs in the pathogenesis of diabetes and associated complications such as nephropathy, retinopathy, cardiomyopathy, and neuropathy. MVs, through their cargo of proteins, lipids, mRNAs, and miRNAs, regulate critical processes like inflammation, oxidative stress, immune responses, and tissue remodeling, all of which contribute to the progression of diabetes and its complications. We examine the molecular mechanisms underlying MVs' involvement in these pathological processes and discuss their potential as biomarkers and therapeutic tools, particularly for drug delivery. Despite promising evidence, challenges remain in isolating and characterizing MVs, understanding their molecular mechanisms, and validating them for clinical use. Advanced techniques such as single-cell RNA sequencing and proteomics are required to gain deeper insights. Improved isolation and purification methods are essential for translating MVs into clinical applications, with potential to develop novel diagnostic and therapeutic strategies to improve patient outcomes in diabetes.

Causes of death among Australians with type 1 or type 2 diabetes, 2002-2019.

AIMS: This population-based study sought to explore in detail the conditions driving the diversification in causes of death among people with diabetes. METHODS: We linked Australians with type 1 or type 2 diabetes of all ages on the National Diabetes Services Scheme to the National Death Index for 2002-2019. We investigated the proportional contributions of different causes of death to total deaths over time across eight categories of causes of death, stratified by sex and diabetes type. The underlying causes of death were classified according to the International Classification of Diseases, Tenth Revision codes. RESULTS: Between 2002 and 2019, there was a shift in the causes of death among Australians with diabetes away from cardiovascular disease. The proportion of deaths attributed to cardiovascular disease declined in both sexes (ptrend <0.001), most substantially among women with type 2 diabetes from 48.2% in 2002 to 30.7% in 2019. Among men with type 2 diabetes, cancer replaced cardiovascular disease as the leading cause of death. The proportion of deaths due to dementia increased overall, from 2% in 2002 to over 7% in 2019, and across all age groups, notably from 1% to 4% in those aged 70-79. The proportion of deaths due to falls and Parkinson's disease also increased. CONCLUSIONS: There has been a shift of causes of death among those with diabetes away from cardiovascular disease. The proportion of deaths due to conditions such as dementia and falls is increasing among those with diabetes, which will require consideration when planning future resource allocation.

Estimation of the direct health and indirect societal costs of diabetes in the UK using a cost of illness model.

AIMS: The direct cost of diabetes to the UK health system was estimated at around £10 billion in 2012. This analysis updates that estimate using more recent and accurate data sources. METHODS: A pragmatic review of relevant data sources for UK nations was conducted, including population-level data sets and published literature, to generate estimates of costs separately for Type 1, Type 2 and gestational diabetes. A comprehensive cost framework, developed in collaboration with experts, was used to create a population-based cost of illness model. The key driver of the analysis was prevalence of diabetes and its complications. Estimates were made of the excess costs of diagnosis, treatment and diabetes-related complications compared with the general UK population. Estimates of the indirect costs of diabetes focused on productivity losses due to absenteeism and premature mortality. RESULTS: The direct costs of diabetes in 2021/22 for the UK were estimated at £10.7 billion, of which just over 40% related to diagnosis and treatment, with the rest relating to the excess costs of complications. Indirect costs were estimated at £3.3 billion. CONCLUSIONS: Diabetes remains a considerable cost burden in the UK, and the majority of those costs are still spent on potentially preventable complications. Although rates of some complications are reducing, prevalence continues to increase and effective approaches to primary and secondary prevention continue to be needed. Improvements in data capture, data quality and reporting, and further research on the human and financial implications of increasing incidence of Type 2 diabetes in younger people are recommended.

Evaluating the incidence of complications among people with diabetes according to age of onset: Findings from the UK Biobank.

AIMS: To examine the impact of current age, age at diagnosis, and duration of diabetes on the incidence rate of complications among people with type 2 diabetes. METHODS: Baseline data from 19,327 individuals with type 2 diabetes in the UK Biobank were analysed. Poisson regression was used to model incidence rates by current age, age at diagnosis, and duration of diabetes for the following outcomes: myocardial infarction (MI), heart failure (HF), stroke, end-stage kidney diseases (ESKD), chronic kidney diseases (CKD), liver diseases, depression, and anxiety. RESULTS: The mean age at baseline was 60.2 years, and median follow-up was 13.9 years. Diabetes duration was significantly longer among those with younger-onset type 2 diabetes (diagnosed at <40 years) compared to later-onset type 2 diabetes (diagnosed at ≥40 years), 16.2 and 5.3 years, respectively. Incidence rates of MI, HF, stroke, and CKD had strong positive associations with age and duration of diabetes, whereas incidence rates of ESKD liver diseases, and anxiety mainly depended on duration of diabetes. The incidence rates of depression showed minor variation by age and duration of diabetes and were highest among those diagnosed at earlier ages. No clear evidence of an effect of age of onset of diabetes on risk of complications was apparent after accounting for current age and duration of diabetes. CONCLUSIONS: Our study indicates age at diagnosis of diabetes does not significantly impact the incidence of complications, independently of the duration of diabetes. Instead, complications are primarily influenced by current age and diabetes duration.

Beneficial effect of oral semaglutide for type 2 diabetes mellitus in patients with metabolic dysfunction-associated steatotic liver disease: A prospective, multicentre, observational study.

AIMS: To evaluate the efficacy and safety of oral semaglutide for type 2 diabetes mellitus (T2DM) in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). MATERIALS AND METHODS: This was a single-arm, multicentre, prospective study. Among 80 consecutive patients with MASLD and T2DM who newly received oral semaglutide, 70 completed 48-week oral semaglutide treatment as scheduled and were included in an efficacy analysis. Dose adjustments of oral semaglutide were determined by each physician while monitoring efficacy and adverse events. RESULTS: Significant improvements in body weight, liver enzymes, lipid profile, and glycaemic control were found at 48 weeks compared with baseline values (all p < 0.01). Controlled attenuation parameter values significantly decreased from baseline to 48 weeks (p < 0.01). Changes in alanine aminotransferase concentrations (r = 0.37, p < 0.01) and controlled attenuation parameter values (r = 0.44, p < 0.01) were significantly correlated with changes in body weight. Liver fibrosis markers, such as type IV collagen 7S, Wisteria floribunda agglutinin-positive Mac-2-binding protein, fibrosis-4 index, and liver stiffness measurement, significantly decreased from baseline to 48 weeks (all p < 0.01). The most common adverse events were Grades 1-2 transient gastrointestinal symptoms, such as nausea (23 patients, 28.8%), dyspepsia (12, 15.0%) and appetite loss (4, 5.0%). CONCLUSIONS: Oral semaglutide treatment for T2DM in patients with MASLD leads to an improvement in liver steatosis and injury, surrogate markers of fibrosis, diabetic status, and lipid profile, and reduces body weight.

Prognostic value of the stress-hyperglycaemia ratio in patients with moderate-to-severe coronary artery calcification: Insights from a large cohort study.

AIM: To evaluate the relationship between the stress-hyperglycaemia ratio (SHR) and the clinical prognosis of patients with moderate-to-severe coronary artery calcification (MSCAC). METHODS: We consecutively enrolled 3841 patients with angiography-detected MSCAC. The individuals were categorized into three groups based on SHR tertiles: T1 (SHR ≤ 0.77), T2 (0.77 < SHR ≤ 0.89) and T3 (SHR > 0.89). The SHR value was calculated using the formula SHR = [admission glucose (mmol/L)]/[1.59 × HbA1c (%) - 2.59]. The primary outcomes were major adverse cardiovascular and cerebrovascular events (MACCEs), including all-cause death, non-fatal myocardial infarction and non-fatal stroke. RESULTS: During a median follow-up of 3.11 years, 241 MACCEs were recorded. Kaplan-Meier survival analysis showed that the SHR T3 group had the highest incidence of MACCEs (P < .001). Moreover, findings from the restricted cubic spline analysis showed a significant and positive association between the SHR and MACCEs. This correlation remained consistent even after considering other variables that could potentially impact the results (Pnon-linear = .794). When comparing SHR T1 with SHR T3, it was found that SHR T3 was significantly associated with an increased risk of the primary outcome (adjusted hazard ratio = 1.50; 95% confidence interval: 1.10-2.03). CONCLUSIONS: Patients with MSCAC showed a positive correlation between the SHR and MACCE rate over a 3-year follow-up period. The study showed that an SHR value of 0.83 is the key threshold, indicating a poor prognosis. Future large-scale multicentre investigations should be conducted to determine the predictive value of the SHR in patients with MSCAC.

Detection of hypoglycaemia in type 1 diabetes through breath volatile organic compound profiling using gas chromatography-ion mobility spectrometry.

AIM: To evaluate the relationship between breath volatile organic compounds (VOCs) and glycaemic states in individuals with type 1 diabetes (T1D), focusing on identifying specific VOCs as biomarkers for hypoglycaemia to offer a non-invasive diabetes-monitoring method. MATERIALS AND METHODS: Ten individuals with T1D underwent induced hypoglycaemia in a clinical setting. Breath samples, collected every 10-15 minutes, were analysed using gas chromatography-ion mobility spectrometry (GC-IMS). Correlation analysis and machine learning models, including Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine classifiers, were used to classify glycaemic states based on VOC profiles. RESULTS: Statistical analysis revealed moderate correlations between specific VOCs (e.g. isoprene, acetone) and venous blood glucose levels. Machine learning models showed high accuracy in classifying glycaemic states, with the best performance achieved by a two-class PLS-DA model showing an accuracy of 93%, sensitivity of 92% and specificity of 94%. Key biomarkers identified included isoprene, acetone, 2-butanone, methanol, ethanol, 2-propanol and 2-pentanone. CONCLUSIONS: This study shows the potential of breath VOCs to accurately classify glycaemic states in individuals with T1D. While key biomarkers such as isoprene, acetone and 2-butanone were identified, the analysis emphasizes the importance of using overall VOC patterns rather than individual compounds, which can be markers for multiple conditions. Machine learning models leveraging these patterns achieved high accuracy, sensitivity and specificity. These findings suggest that breath analysis using GC-IMS could be a viable non-invasive method for monitoring glycaemic states and managing diabetes.

Cardiovascular risk reduction in type 2 diabetes: What the non-specialist needs to know about current guidelines.

In the US, approximately 11% of the population have diagnosed diabetes and nearly 40% have prediabetes. In addition, chronic kidney disease (CKD) affects 14% of the US population including up to 40% of those with diabetes. Cardiovascular disease (CVD) remains the leading cause of death worldwide where it affects approximately half of adults. The presence of CKD or diabetes doubles the risk of cardiovascular events. When both CKD and diabetes occur in the same patient the risks are further increased. The clinical problems of hypertension, hyperglycemia, and hyperlipidemia are all closely related with obesity, metabolic syndrome, Type 2 diabetes, CKD, atherosclerotic cardiovascular disease, heart failure and non-alcoholic fatty liver disease and metabolic dysfunction-associated steatohepatitis. The increasing frequency of obesity has driven increases in all of these medical comorbidities. These conditions frequently cluster together in the same patient exacerbating the risk of morbidity and mortality. They are also associated with cognitive dysfunction/dementia, pulmonary diseases, cancers, gastrointestinal diseases, immune system abnormalities, and inflammatory disorders. Only 6.8% of adults in US meet all targets for cardiovascular risk management with significant disparities based on race and ethnicity. Given the complexity of these multisystem problems in people with diabetes and obesity, it would seem reasonable to attempt to diagnose and treat many of the comorbidities earlier in the course of disease rather than wait for substantial end organ dysfunction to occur. The American Diabetes Association (ADA) has recently published a consensus statement recommending early screening for the diagnosis of heart failure, CKD and diabetes, recognizing both the frequency and gravity of this combination. Likewise, there are recommendations in the guidelines to facilitate screening for microalbuminuria, blood pressure, glycemic control and lipids earlier in patients at risk rather than wait and treat as a secondary prevention program. Thus, the general principle is to facilitate earlier recognition and diagnosis and provide treatment before downstream target organ complications occur. This review will focus on CVD and risk management based on newest recommendations and standards of care in people with diabetes by the ADA. The main considerations in the treatment of people with diabetes are glycemic control, blood pressure, lipids, and the use of medications with proven cardiorenal disease progression capability to prevent or delay.

Fracture risk revisited: Bone mineral density T-score and fracture risk in type 2 diabetes.

AIM: To study the association between femoral neck (FN) bone mineral density (BMD) T-score and fracture risk in individuals with and without type 2 diabetes (T2D). MATERIALS AND METHODS: We performed a single-centre retrospective cohort study using the Danish National Health Service. BMD of the FN was measured by dual-energy X-ray absorptiometry. Cox proportional hazards regression models were used to study the association between FN BMD T-score and fractures in individuals with and without T2D separately, adjusted for age, comorbidities and comedication. The results from this analysis were used to estimate the 10-year absolute fracture risk. RESULTS: In total, there were 35,129 women (2362 with T2D) and 7069 men (758 with T2D). The FN BMD T-score was significantly associated with risk of any, hip and major osteoporotic fracture in men and women with [adjusted hazard risk ratios (aHR) women, hip: 1.57; 95% confidence interval (CI) 1.24-2.00, incidence rate (IR) 8.7; aHR men, hip: 1.55; 95% CI 1.01-2.36, IR 4.6] and without T2D (aHR women, hip: 1.75; 95% CI 1.64-1.87, IR 7.0; aHR men, hip: 1.97, 95% CI 1.73-2.25, IR 6.3), and its ability to predict fracture risk was similar. Fracture IRs were not significantly different for individuals with or without T2D, nor was the estimated cumulative 10-year fracture risk. CONCLUSIONS: The FN BMD T-score was significantly associated with hip, non-spine and major osteoporotic fracture risk in men and women with and without T2D. Fracture risk for a given T-score and age was equal in individuals with and without T2D, as was the ability of the FN BMD T-score to predict fracture risk.

Periodontal tissue susceptibility to glycaemic control in type 2 diabetes.

AIM: To assess the direct effect of intensive glycaemic control on periodontal tissues in patients with diabetes mellitus. MATERIALS AND METHODS: Twenty-nine patients with type 2 diabetes were enrolled and hospitalized to receive a 2-week intensive glycaemic control regimen. We observed and analysed the systemic and oral disease indicators before and after treatment and clarified the indicators related to periodontal inflammation. RESULTS: A significant reduction in glycaemic and periodontal parameters, including glycated albumin levels and periodontal inflamed surface area (PISA), was observed after treatment. The changes in PISA per tooth, indicative of periodontal healing, exhibited a bimodal distribution; the patients were divided into two groups on this basis. Correlations were observed between the changes in PISA per tooth and fasting plasma glucose, acetoacetic acid, and beta-hydroxybutyrate levels in the PISA-improved group. Significantly lower levels of C-peptide, coefficient of variation of R-R interval, and ankle-brachial pressure index were observed before treatment in the PISA non-improved group. CONCLUSIONS: Glycaemic control treatment can effectively improve periodontitis in patients with type 2 diabetes, even in the absence of specific periodontal treatments. However, the periodontal responsiveness to glycaemic control treatment depends on the systemic condition of the patient.

Association of single-point insulin sensitivity estimator index (SPISE) with future cardiovascular outcomes in patients with type 2 diabetes.

AIMS: To investigate the association of single-point insulin sensitivity estimator (SPISE) index with future cardiovascular outcomes in patients with type 2 diabetes. MATERIALS AND METHODS: SPISE index (= 600 × high-density lipoprotein cholesterol [mg/dL]0.185/triglycerides [mg/dL]0.2 × body mass index [kg/m2]1.338) was calculated in 10 190 participants. Cox proportional hazard regression models were applied to evaluate the association between SPISE index and future cardiovascular outcomes. Restricted cubic spline analyses and two-piecewise linear regression models were employed to explore the nonlinear association and to determine the threshold value. Subgroup and interaction analyses were conducted to test the robustness of the results. RESULTS: After fully adjusting for well-established metabolic confounders, higher SPISE index was significantly associated with lower risk of future cardiovascular outcomes in patients with type 2 diabetes (major adverse cardiovascular event [MACE]): hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.90-0.98, p = 0.0026; overall mortality: HR 0.90, 95% CI 0.86-0.93, p < 0.0001; cardiovascular disease [CVD] mortality: HR 0.85, 95% CI 0.79-0.92, p < 0.0001; congestive heart failure (CHF): HR 0.72, 95% CI 0.67-0.78, p < 0.0001; major coronary events: HR 0.91, 95% CI 0.87-0.95, p < 0.0001. There was a nonlinear association between SPISE index and future cardiovascular outcomes (the threshold value was 5.68 for MACE, 5.71 for overall mortality, 4.64 for CVD mortality, 4.48 for CHF, and 6.09 for major coronary events, respectively). CONCLUSIONS: Higher SPISE index was independently associated with lower risk of future cardiovascular outcomes in type 2 diabetes patients after full adjustment for well-established metabolic confounders.

Association of gestational diabetes with long-term risk of premature mortality, and cardiovascular outcomes and risk factors: A retrospective cohort analysis in the UK Biobank.

AIM: To investigate the association of gestational diabetes mellitus (GDM) with premature mortality and cardiovascular (CVD) outcomes and risk factors. MATERIALS AND METHODS: Parous women recruited to the UK Biobank cohort during 2006-2010 were followed up from their first delivery until 31 October 2021. The data were linked to Hospital Episode Statistics and mortality registries. Multivariate Cox proportional hazard models investigated associations of GDM with all-cause mortality, CVD, diabetes, hypertension and dyslipidaemia. RESULTS: The maximum total analysis time at risk and under observation was 9 694 090 person-years. Among 220 726 women, 1225 self-reported or had a recorded diagnosis of GDM. After adjusting for confounders and behavioural factors, GDM was associated with increased risk for premature mortality [hazard ratio (HR): 1.44, 95% confidence interval (CI): 1.12-1.86], particularly CVD-related death (HR: 2.38, 95% CI: 1.63-3.48), as well as incident total CVD (HR: 1.50, 95% CI: 1.30-1.74), non-fatal CVD (HR: 1.41, 95% CI: 1.20-1.65), diabetes (HR: 14.37, 95% CI: 13.51-15.27), hypertension (HR: 1.49, 95% CI: 1.38-1.60), and dyslipidaemia (HR: 1.30, 95% CI: 1.22-1.39). The total CVD risk was greater in women with GDM who did not later develop diabetes than in those with GDM and diabetes. CONCLUSIONS: Women with GDM are at increased risk of premature death and have increased CV risk, emphasizing the importance of interventions to prevent GDM. If GDM develops, the diagnosis represents an opportunity for future surveillance and intervention to reduce CVD risk factors, prevent CVD and improve long-term health.

Lifetime and 10-year cardiovascular risk prediction in individuals with type 1 diabetes: The LIFE-T1D model.

AIMS: To develop and externally validate the LIFE-T1D model for the estimation of lifetime and 10-year risk of cardiovascular disease (CVD) in individuals with type 1 diabetes. MATERIALS AND METHODS: A sex-specific competing risk-adjusted Cox proportional hazards model was derived in individuals with type 1 diabetes without prior CVD from the Swedish National Diabetes Register (NDR), using age as the time axis. Predictors included age at diabetes onset, smoking status, body mass index, systolic blood pressure, glycated haemoglobin level, estimated glomerular filtration rate, non-high-density lipoprotein cholesterol, albuminuria and retinopathy. The model was externally validated in the Danish Funen Diabetes Database (FDDB) and the UK Biobank. RESULTS: During a median follow-up of 11.8 years (interquartile interval 6.1-17.1 years), 4608 CVD events and 1316 non-CVD deaths were observed in the NDR (n = 39 756). The internal validation c-statistic was 0.85 (95% confidence interval [CI] 0.84-0.85) and the external validation c-statistics were 0.77 (95% CI 0.74-0.81) for the FDDB (n = 2709) and 0.73 (95% CI 0.70-0.77) for the UK Biobank (n = 1022). Predicted risks were consistent with the observed incidence in the derivation and both validation cohorts. CONCLUSIONS: The LIFE-T1D model can estimate lifetime risk of CVD and CVD-free life expectancy in individuals with type 1 diabetes without previous CVD. This model can facilitate individualized CVD prevention among individuals with type 1 diabetes. Validation in additional cohorts will improve future clinical implementation.

What every clinician needs to know about chronic kidney disease: Detection, classification and epidemiology.

Chronic kidney disease (CKD) is a major healthcare challenge, affecting >800 million people worldwide. Implications for population health result from the strong associations of CKD with increased rates of cardiovascular disease, heart failure, progressive CKD leading to kidney failure, acute kidney injury (AKI), and mortality. In addition to a single disease perspective, CKD commonly coexists alongside other long-term conditions, in particular type 2 diabetes and cardiovascular disease. CKD is therefore an important component of multimorbidity that influences individual management and impacts prognosis. CKD is defined by abnormalities of kidney structure or function of any cause with implications for health that are present for longer than 3 months. The diagnosis is usually made on the basis of an abnormal glomerular filtration rate (GFR < 60 mL/min/1.73 m2) and/or the presence of proteinuria (urine albumin to creatinine ratio > 30 mg/g or >3 mg/mmol). GFR is usually estimated from serum creatinine concentration using a variety of validated equations. However, serum creatinine is closely related to muscle mass and may therefore not be an accurate marker of GFR in people with high or low muscle mass (sarcopaenia). Cystatin C is an alternative endogenous marker of GFR that is increasingly being used but also has limitations. An estimate of GFR based on both creatinine and cystatin C is the most accurate. Diagnosis should be followed by classification and risk stratification to guide the development of a risk-based, personalized care plan. Improved detection and widespread implementation of optimal CKD management has the potential to bring major benefits to population health.