Risk factors for myocardial infarction case fatality and stroke case fatality in type 2 diabetes: UKPDS 66

Risk of Stroke in Real-World US Individuals with Type 2 Diabetes Receiving Semaglutide or a Dipeptidyl Peptidase 4 Inhibitor

INTRODUCTION

People with type 2 diabetes (T2D) have a higher risk of stroke and worse outcomes than those without T2D. Pooled data from randomized controlled trials indicate that the glucagon-like peptide 1 receptor agonist semaglutide is associated with stroke risk reduction in people with T2D at high cardiovascular risk. We compared real-world stroke risk in people with T2D or T2D plus atherosclerotic cardiovascular disease (ASCVD) initiating either semaglutide or a dipeptidyl peptidase 4 inhibitor (DPP4i).

METHODS

Adults (≥ 18 years old) in a US claims database with a claim indicating initiation of either semaglutide or a DPP4i (index date) during the index period (1 January 2018-30 September 2020), a diagnosis code for T2D on or before the index date and at least 12 months' continuous enrolment in the database pre-index were included and propensity score matched 1:1 on baseline demographic and clinical characteristics. The primary outcome was time to first stroke event during follow-up. Healthcare resource utilization was also compared between groups.

RESULTS

The analysis included 17,920 matched pairs with T2D and 4234 matched pairs with T2D and ASCVD. The groups were well matched on baseline characteristics. People initiating semaglutide had a lower risk of stroke over short-term follow-up than those initiating a DPP4i (T2D: hazard ratio 0.63 [95% confidence interval 0.41-0.95], p = 0.029; T2D plus ASCVD: 0.45 [0.24-0.86], p = 0.015). Semaglutide was also associated with a lower rate of inpatient, outpatient and emergency room visits compared with a DPP4i.

CONCLUSION

This proof-of-concept analysis indicates that semaglutide has the potential to reduce the risk of stroke in people with T2D when prescribed in clinical practice.

Cardiovascular Outcomes Among Patients with Acute Coronary Syndromes and Diabetes: Results from ACS QUIK Trial in India

Background

Despite cardiovascular disease being the leading cause of death in India, limited data exist regarding the factors associated with outcomes in patients with diabetes who suffer acute myocardial infarction (AMI).

Methods

We examined 21,374 patients with AMI enrolled in the ACS QUIK trial. We compared in-hospital and 30-day major adverse cardiac events including death, re-infarction, stroke, or major bleeding in those with and without diabetes. The associations between diabetes and cardiac outcomes were adjusted for presentation and in-hospital management using logistic regression.

Results

Mean ± SD age was 60.1 ± 12.0 years, 24.3% were females, and 44.4% had diabetes. Those with diabetes were more likely to be older, female, hypertensive, and have higher Killip class but less likely to present with STEMI. Patients with diabetes had longer symptoms onset-to-arrival (median 225 vs 290 min; P < 0.001) and, in case of STEMI, longer door-to-balloon times (median, 75 vs 91 min; P < 0.001). Diabetes was independently associated with higher in-hospital death (adjusted odds ratio [aOR], 1.46; 95% CI, 1.12-1.89), in-hospital reinfarction (aOR, 1.52; 95% CI, 1.15-2.02), 30-day MACE (aOR, 1.33; 95% CI, 1.14-1.55) and 30-day death (aOR, 1.40; 95%CI, 1.16-1.69) but not 30-day stroke or 30-day major bleeding.

Conclusion

Among patients presenting with AMI in Kerala, India, a considerable proportion has diabetes and are at increased risk for in-hospital and 30-day adverse cardiovascular outcomes. Increased awareness of the increased cardiovascular risk and attention to the implementation of established cardiovascular therapies are indicated for patients with diabetes in lower-middle-income countries who develop AMI.

Clinical Trial registration

ClinicalTrials.gov Unique identifier: NCT02256658.

Skin autofluorescence of advanced glycation end-products relates to new cardiovascular events in type 2 diabetes: A longitudinal observational study

BACKGROUND

Cardiovascular disease is frequent in type 2 diabetes mellitus (T2DM). We investigated the relationship between skin autofluorescence (SAF) of advanced glycation end-products and later cardiovascular events (CVEs) in patients with T2DM.

RESEARCH DESIGN AND METHODS

We conducted a retrospective analysis of 504 patients hospitalized for uncontrolled and/or complicated T2DM between 2009 and 2017. SAF was measured using an AGE-Reader. Participants were followed up from admission to December 2020, for the onset of a CVE (myocardial infarction, stroke, revascularization procedures or cardiovascular death). The relationship between SAF and CVE was analyzed by multivariable Cox regression. Log-rank curves were used to compare CVE-free survival in patients whose SAF at admission was above versus below the whole-population median. The analysis was repeated in subjects without/with macroangiopathy (defined as myocardial infarction, stroke, peripheral revascularization) at baseline.

FINDINGS

During 54 months of follow-up, 69 (13.7%) patients had a CVE. Baseline SAF was significantly higher in patients with T2DM who later experienced a CVE (2.89 ± 0.70 arbitrary units versus 2.64 ± 0.62 in others, P = 0.002). This relationship was significant after adjusting for age, sex, conventional risk factors (diabetes duration, HbA1c, arterial hypertension, dyslipidemia, smoking, body mass index), vascular complications, C-reactive protein, and treatments for diabetes. The CVE-free survival curves differed between subjects whose SAF was above the whole-population median (log-rank: P = 0.002) and those whose SAF was above the macroangiopathy-free sub-population median (log-rank: P = 0.016).

CONCLUSION

SAF of advanced glycation end-products was related to a higher incidence of later CVE in patients with T2DM.

Mesenchymal Stem Cell-Derived Exosomes: A Novel Approach to Diabetes-Associated Cognitive Impairment

The progression of diabetes frequently results in a myriad of neurological disorders, including ischemic stroke, depression, blood-brain barrier impairment, and cognitive dysfunction. Notably, diabetes-associated cognitive impairment, a prevalent comorbidity during the course of diabetes, progressively affects patients' cognitive abilities and may reciprocally influence diabetes management, thereby severely impacting patients' quality of life. Extracellular vesicles, particularly nanoscale exosomes, have garnered considerable attention in recent years. These exosomes carry and transfer various functional molecules, such as proteins, lipids, and diverse non-coding RNAs, serving as novel regulators and communicators in intercellular interactions. Of particular interest, mesenchymal stem cell-derived exosomes (MSC-Exos) have been reported to traverse the blood-brain barrier and ameliorate intracerebral pathologies. This review elucidates the role of MSC-Exos in diabetes-related cognitive impairment, with a focus on their applications as biomarkers, modulation of neuronal regeneration and synaptic plasticity, anti-inflammatory properties, antioxidative effects, and their involvement in regulating the functionality of β-amyloid proteins during the course of cognitive impairment. The immense therapeutic potential of MSC-Exos in the treatment of diabetes-induced cognitive dysfunction is emphasized.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used

AIM

Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions.

METHODS

PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated.

RESULTS

The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly.

CONCLUSIONS

The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

Long-term increase in fasting blood glucose is associated with increased risk of sudden cardiac arrest

BACKGROUND

Diabetes mellitus (DM) is associated with various cardiovascular complications, including sudden cardiac arrest (SCA). Furthermore, the severity of DM, as assessed by fasting blood glucose (FBG), is associated with the risk of SCA. However, whether long-term changes in FBG influence on SCA risk remains to be determined.

METHODS

This study used sequential nationwide health screening data from 2009 and 2011. FBG was measured at each health screening, and ΔFBG was calculated as FBG in 2011-FBG in 2009.

RESULTS

Overall, 2,801,153 people were analyzed, and the mean follow-up duration was 6.33 years. Compared with the euglycemic group (- 20 ≤ ΔFBG < 20), the 20 ≤ ΔFBG < 40, 40 ≤ ΔFBG < 100, and ΔFBG ≥ 100 groups had increased SCA risks of 25% (adjusted hazard ratio [HR] = 1.25; 95% confidence interval [CI] 1.16-1.35; p < 0.001), 66% (adjusted HR = 1.66; 95% CI 1.49-1.86; p < 0.001), and 2.9-fold (adjusted HR = 2.85; 95% CI 2.37-3.44; p < 0.001), respectively. The association between ΔFBG and SCA was maintained in people with DM but not in people without DM. However, sex, age, blood pressure, and presence of heart failure did not affect the association between ΔFBG and SCA. A decrease in ΔFBG over time was not associated with reduced risk of SCA: the adjusted HR was 1.11 (95% CI 0.98-1.27; p = 0.113) for the ΔFBG < -40 group and 1.12 (95% CI 1.03-1.22; p = 0.009) for the - 40 ≤ ∆FBG < - 20 group.

CONCLUSIONS

A long-term increase in ΔFBG can be associated with increased risk of SCA in people with DM. However, a long-term decrease in ΔFBG was not associated with reduced risk of SCA. Actions to prevent increase in FBG can have significant effects on public health in terms of SCA prevention.

Women and Ischemic Stroke

Although men are at higher risk of stroke throughout most of their lifespan, the incidence of stroke in women climbs with age, increasing after menopause and rising sharply after 85 years. This, combined with women's longer life expectancy, results in most of the stroke deaths occurring in women. In addition to accounting for a larger proportion of strokes, women may also suffer a survival disadvantage, which may be due to several factors. In many families, women are the primary caretakers. When they become disabled, there may be limited options to care for them. Others suggest that some of the disparities in stroke outcomes in women may be related to age, pre-stroke functional status, and comorbidities. Regardless of the cause, the increased disability and post-stroke care requirements of women, particularly in our aging population, highlight the importance of determining successful strategies for stroke prevention, acute stroke treatments, optimization of stroke rehabilitation, and effective secondary prevention measures in women.

Cardioprotective effects of neuropeptide galanin: Focusing on its roles against diabetic heart

Following an unprecedented rise in the number of the aged, the incidence of age-related diseases, such as diabetes and cardiovascular disease, is consequently increasing in the world. Type 2 diabetes mellitus (T2DM) is associated with excess cardiovascular morbidity and mortality. The diabetic heart is characterized by increased cardiomyocyte stiffness and fibrotic changes. Despite many factors resulting in cardiomyocyte injury and dysfunction in diabetes, insulin resistance is still a critical etiology of diabetic cardiomyopathy. Preclinical and clinical studies have revealed an intriguing role for galanin in the pathogenesis of insulin resistance and diabetic heart disease. A significant change in plasma galanin levels occurred in patients suffering from type 2 diabetes or cardiomyocyte injury. In turn, galanin may also distinctly mitigate hyperglycemia and insulin resistance in diabetes as well as increase glucose metabolism and mitochondrial biogenesis in cardiac muscle. Here, we critically review current data about the multivariate relationship among galanin, insulin resistance, and cardiac muscle to comprehensively evaluate the protective role of galanin and its receptors for the diabetic heart and to determine whether galanin receptor 2 agonists potentially represent a feasible way to treat diabetic cardiomyopathy in the future.

A doctor-nurse-patient mobile health management system effectively controls blood glucose in chinese patients with type 2 diabetes mellitus: a prospective study

BACKGROUND

Coronavirus-2019 pandemic in China aroused increasing interest in telemedicine-supported glycaemic control. We hypothesize that age might influence usage and efficacy of telemedicine-supported glycaemic control. This study aims to measure the effects of a doctor-nurse-patient Mobile Health Management System (MHMS) for fasting plasma glucose (FPG) control in patients with type 2 diabetes mellitus (T2DM).

METHODS

Four hundred sixty four patients with T2DM were recruited. A one-hour diabetes education provided to each patient and subsequent follow-ups arranged in the 1st, 2nd, 4th, 8th, and 12th week after enrollment were recorded in MHMS. The effectiveness of MHMS was defined as the proportion of patients achieving FPG target (below 126 mg/dL or 7.0mml/L).

RESULTS

Among the enrolled 464 patients (age: 55.0 ± 13.7 years) who were divided into three groups: young (18-40 years), middle-aged (41-65 years) and elderly (> 65 years), 424 ones completed all follow-ups of 12 weeks. FPG decreased from 178.38 ± 95.04 to 117.90 ± 14.22 mg/dL in the young group, from 180.00 ± 91.08 to 122.94 ± 37.95 mg/dL in the middle-aged group, and from 174.24 ± 80.64 to 128.88 ± 23.4 mg/dL in the elderly group. The proportion of FPG-target-achieved patients increased from 46.2 to 90.4% in the young group, from 32.6 to 82.8% in the middle-aged group, and from 29.5 to 73.3% in the elderly group. The proportion of FPG-target-achieved patients between three age groups were statistically significant (P < 0.001). And the changes of proportion of FPG-target-achieved patients at different follow-up times were statistically significant (P = 0.037). Compared with the young group, the elderly group achieved poorer FPG level (P = 0.032).

CONCLUSION

MHMS can help patients with T2DM lower FPG and improve proportion of FPG-target-achieved patients. Younger patients may achieve better glycaemic control than older patients. MHMS may serve multitudinous patients with T2DM to achieve adequate FPG self-management.

Atrial fibrillation is an independent risk factor for new-onset myocardial infarction: a prospective study

BACKGROUND

Atrial fibrillation (AF) and myocardial infarction (MI) share common cardiovascular risk factors, therefore coexistence of AF and MI is very common, in addition, both AF and MI aggravate and exacerbate each other through multiple pathological processes. The aim of this study is to investigate whether AF increases the risk of new-onset MI.

METHODS

In total 171,086 participants from an industrial city in North China were selected and enrolled in this prospective cohort study, participants were divided into the AF group or the non-AF group according to their medical history. 1542 participants from the AF group were propensity-matched with 4626 participants from the non-AF group. All the participants were followed up every 2 years from June 2006 to December 2020, the median follow-up was 14.25 years and the endpoint of this study was new-onset MI. The association between AF and new-onset MI was analysed by using both univariate and multivariate Cox proportional hazards regression analysis.

RESULTS

New-onset MI was documented in 56 cases from the AF group and 98 cases from the non-AF group, respectively, the cumulative incidence of new-onset MI in the AF group (3.73%) was significantly higher than that in the non-AF group (2.23%) (p < 0.01). In a univariate analysis, AF was associated with an increased risk of new-onset MI (hazard ratio: 1.73, 95% confidence interval: 1.24-2.40), in two multivariable-adjusted analyses, AF was still associated with an increased risk of new-onset MI (hazard ratio: 1.78, 95% confidence interval, 1.28-2.47).

CONCLUSIONS

AF is an independent risk factor for new-onset MI in an industrial population of North China.

Sex differences in neurovascular disorders

Neurovascular disorders is a heterogenous group of diseases, including one of the most time critical disorders in emergency medicine; stroke. Sex differences are extensively described in neurovascular disorders, ranging from differences in symptom presentation, risk factors, treatment and outcomes. For example, women with stroke, more often present with generalized weakness, reduced consciousness and headache than men. Furthermore, there are differences in risk factors, outcomes and in the effect of secondary prevention. Women have a higher risk of cerebral venous thrombosis and developing cerebral aneurysms. In general, women have been underrepresented in trials on neurovascular disorders. This chapter provides an extensive overview of sex differences in stroke in general and in the differences specially seen in ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage and in cerebral venous thrombosis.

Machine Learning-Based Prediction of Subsequent Vascular Events After 6 Months in Chinese Patients with Minor Ischemic Stroke

Background

To develop and validate a machine learning model for predicting subsequent vascular events (SVE) 6 months after mild ischemic stroke (MIS) in Chinese patients.

Methods

A retrospective analysis was performed on 495 newly diagnosed MIS patients by collecting their basic information, past medical history, initial NIHSS score, symptoms, obstruction sites of MIS, and MRI results. According to the ratio of 7:3, the dataset was divided into a training set (n=346) and a testing set (n=149) through stratified random sampling. In the training set, the recursive feature elimination (RFE) was used to select the optimal combination of features, and two machine learning algorithms, including the logistic regression (LR) and support vector machines (SVM), were used to build the prediction model, which was further validated by using 5-fold cross-validation. The receiver operating characteristic (ROC) curve was used on the testing set to evaluate the model’s performance, and the area under the curve (AUC), sensitivity, specificity, and accuracy were calculated. The calibration curve and decision curve of the two models were further compared.

Results

SVE occurred in 56 cases (11.3%) of 495 patients with MIS during the 6-month follow-up. Finally, the best 15 predictive features were selected, and the top three predictive features were diabetes, posterior cerebral artery lesion, and fasting blood glucose in order. In the testing set, the AUC of the LR model was 0.929 (95% CI: 0.875–0.964), and its accuracy, sensitivity, and specificity were 0.832, 0.765, and 0.841, respectively. The AUC of the SVM model was 0.992 (95% CI: 0.962–1.000), and its accuracy, sensitivity, and specificity were 0.966, 0.824, and 0.985, respectively. The SVM model’s discrimination, calibration, and clinical validity are better than those of the LR model.

Conclusion

The predictive models developed using machine learning methods can predict the risk of SVE after 6 months following MIS in Chinese patients.

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study

OBJECTIVE

Improved identification of individuals with type 2 diabetes at high cardiovascular (CV) risk could help in selection of newer CV risk-reducing therapies. The aim of this study was to determine whether retinal vascular parameters, derived from retinal screening photographs, alone and in combination with a genome-wide polygenic risk score for coronary heart disease (CHD PRS) would have independent prognostic value over traditional CV risk assessment in patients without prior CV disease.

RESEARCH DESIGN AND METHODS

Patients in the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study were linked to retinal photographs, prescriptions, and outcomes. Retinal photographs were analyzed using VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina) software, a semiautomated artificial intelligence platform, to compute arterial and venous fractal dimension, tortuosity, and diameter. CHD PRS was derived from previously published data. Multivariable Cox regression was used to evaluate the association between retinal vascular parameters and major adverse CV events (MACE) at 10 years compared with the pooled cohort equations (PCE) risk score.

RESULTS

Among 5,152 individuals included in the study, a MACE occurred in 1,017 individuals. Reduced arterial fractal dimension and diameter and increased venous tortuosity each independently predicted MACE. A risk score combining these parameters significantly predicted MACE after adjustment for age, sex, PCE, and the CHD PRS (hazard ratio 1.11 per SD increase, 95% CI 1.04-1.18, P = 0.002) with similar accuracy to PCE (area under the curve [AUC] 0.663 vs. 0.658, P = 0.33). A model incorporating retinal parameters and PRS improved MACE prediction compared with PCE (AUC 0.686 vs. 0.658, P < 0.001).

CONCLUSIONS

Retinal parameters alone and in combination with genome-wide CHD PRS have independent and incremental prognostic value compared with traditional CV risk assessment in type 2 diabetes.

Resolving inflammatory links between myocardial infarction and vascular dementia

Myocardial infarction is associated with increased risk for vascular dementia. In both myocardial infarction and vascular dementia, there is evidence that elevated inflammatory biomarkers are associated with worsened clinical outcomes. Myocardial infarction leads to a systemic inflammatory response, which may contribute to recruitment or activation of myeloid cells, including monocytes, microglia, and perivascular macrophages, within the central nervous system. However, our understanding of the causative roles for these cells linking cardiac injury to the development and progression of dementia is incomplete. Herein, we provide an overview of inflammatory cellular and molecular links between myocardial infarction and vascular dementia and discuss strategies to resolve inflammation after myocardial infarction to limit neurovascular injury.

Gut Microbiota and Complications of Type-2 Diabetes

The gut microbiota has been linked to the emergence of obesity, metabolic syndrome and the onset of type 2 diabetes through decreased glucose tolerance and insulin resistance. Uncontrolled diabetes can lead to serious health consequences such as impaired kidney function, blindness, stroke, myocardial infarction and lower limb amputation. Despite a variety of treatments currently available, cases of diabetes and resulting complications are on the rise. One promising new approach to diabetes focuses on modulating the gut microbiota with probiotics, prebiotics, synbiotics and fecal microbial transplantation. Differences in gut microbiota composition have been observed in preclinical animal models as well as patients with type 2 diabetes and complications such as diabetic nephropathy, diabetic retinopathy, diabetic neuropathy, cerebrovascular disease, coronary heart disease and peripheral artery disease compared to healthy controls. Severity of gut microbiota dysbiosis was associated with disease severity and restoration with probiotic administration in animal models and human patients has been associated with improvement of symptoms and disease progression. Characterizing the gut microbiota dysbiosis in different diseases and determining a causal relationship between the gut microbiota and disease can be beneficial in formulating therapeutic interventions for type 2 diabetes and associated complications. In this review, we present the most important findings regarding the role of the gut microbiota in type 2 diabetes and chronic complications as well as their underlying mechanisms.

Time to Development of Overt Diabetes and Macrovascular and Microvascular Complications Among Patients With Prediabetes: A Retrospective Cohort Study

Objective In this study, we aimed to determine the effect of age, gender, race, and obesity on the development of overt diabetes and macro/microvascular events among patients with prediabetes. Methods This was a retrospective cohort study of patient records available through a national electronic health record (EHR) database from 2012 to 2017. Patients with prediabetes in the baseline year of 2012 were identified. Macro/microvascular events were defined as the diagnosis of myocardial infarction (MI), stroke, or chronic kidney disease (CKD). The effects of age, gender, race, and obesity on the incidence of diabetes and macro/microvascular events between 2013-2017 were assessed using the multivariate Cox proportional-hazards model. Results Among the total 5,230 patients with prediabetes in 2012, 16.7% developed overt diabetes, and 19.7% developed a macro/microvascular event. Elderly patients (HR: 2.96, 95% CI: 2.12-4.13), males (HR: 1.38, 95% CI: 1.20-1.59), and African-Americans (HR: 1.47, 95% CI: 1.26-1.73) were at a higher risk of experiencing a macro/microvascular event. Additionally, male gender (HR: 1.27, 95% CI: 1.11-1.46) and obesity (HR: 1.24, 95% CI: 1.08-1.43) were significant factors associated with the development of overt diabetes. Furthermore, when diabetes status was added as an interaction term to the Cox proportional-hazards model, no statistical difference was found with respect to any of the other independent variables. It can therefore be inferred that those with prediabetes and overt diabetes had a similar risk of developing macro/microvascular events. Conclusions Based on our findings, factors including advanced age, obesity, male gender, and African race significantly impact the progression to diabetes and associated macro/microvascular events.

Leucine imparts cardioprotective effects by enhancing mTOR activity and mitochondrial fusion in a myocardial ischemia/reperfusion injury murine model

BACKGROUND

Coronary artery disease is a leading cause of morbidity and mortality among patients with diabetes. Previously, we demonstrated that branched-chain amino acids (BCAAs) showed cardioprotective effects against cardiac ischemia/reperfusion (I/R) injury. A recent study suggested that leucine (Leu), a BCAA, is a key amino acid involved in mammalian target of rapamycin (mTOR) activity and mitochondrial function. However, whether Leu has cardioprotective effects on diabetic hearts is unclear. In this study, we examined the preconditioning effect of Leu treatment on high-fat diet (HFD)-induced obese mouse which simulate prediabetic heart.

METHODS

In vivo mice models of I/R injury were divided into the following groups: control, mTOR^+/-, and high-fat diet (HFD)-induced obese groups. Mice were randomly administered with Leu, the mTOR inhibitor rapamycin (Rap), or Leu with Rap. Isolated rat cardiomyocytes were subjected to simulated I/R injury. Biochemical and mitochondrial functional assays were performed to evaluate the changes in mTOR activity and mitochondrial dynamics caused by Leu treatment.

RESULTS

Leu-treated mice showed a significant reduction in infarct size when compared with the control group (34.8% ± 3.8% vs. 43.1% ± 2.4%, n = 7, p < 0.05), whereas Rap-treated mice did not show the protective effects of Leu. This preconditioning effect of Leu was attenuated in mTOR^+/- mice. Additionally, Leu increased the percentage of fused mitochondria and the mitochondrial volume, and decreased the number of mitochondria per cell in isolated cardiomyocytes. In HFD-induced obese mice, Leu treatment significantly reduced infarct size (41.0% ± 1.1% vs. 51.0% ± 1.4%, n = 7, p < 0.05), which was not induced by ischemic preconditioning, and this effect was inhibited by Rap. Furthermore, we observed enhanced mTOR protein expression and mitochondrial fusion with decreased reactive oxygen species production with Leu treatment in HFD-induced obese mice, but not in mTOR^+/- mice.

CONCLUSIONS

Leu treatment improved the damage caused by myocardial I/R injury by promoting mTOR activity and mitochondrial fusion on prediabetic hearts in mice.

COVID-19 and Diabetes: A Comprehensive Review of Angiotensin Converting Enzyme 2, Mutual Effects and Pharmacotherapy

The potential relationship between diabetes and COVID-19 has been evaluated. However, new knowledge is rapidly emerging. In this study, we systematically reviewed the relationship between viral cell surface receptors (ACE2, AXL, CD147, DC-SIGN, L-SIGN and DPP4) and SARS-CoV-2 infection risk, and emphasized the implications of ACE2 on SARS-CoV-2 infection and COVID-19 pathogenesis. Besides, we updated on the two-way interactions between diabetes and COVID-19, as well as the treatment options for COVID-19 comorbid patients from the perspective of ACE2. The efficacies of various clinical chemotherapeutic options, including anti-diabetic drugs, renin-angiotensin-aldosterone system inhibitors, lipid-lowering drugs, anticoagulants, and glucocorticoids for COVID-19 positive diabetic patients were discussed. Moreover, we reviewed the significance of two different forms of ACE2 (mACE2 and sACE2) and gender on COVID-19 susceptibility and severity. This review summarizes COVID-19 pathophysiology and the best strategies for clinical management of diabetes patients with COVID-19.

Long-term effects of the mean hemoglobin A1c levels after percutaneous coronary intervention in patients with diabetes

BACKGROUND/AIMS

The clinical benefit of strict blood glucose-lowering therapy for patients with coronary artery disease (CAD) is still debated. We aimed to evaluate the long-term outcomes of patients with diabetes who underwent percutaneous coronary intervention (PCI), according to the mean hemoglobin A1c (HbA1c) level after PCI.

METHODS

We evaluated 675 diabetes patients with CAD treated with PCI. We categorized the study population into three groups based on the mean observed HbA1c levels during the follow-up duration, as follows: aggressive control (AC) group (HbA1c level < 6.5%, n = 148), moderate control (MC) group (HbA1c level ≥ 6.5% and < 7.0%, n = 138), and uncontrolled (UC) group (HbA1c level ≥ 7.0%, n = 389). The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCEs), defined as cardiac death, myocardial infarction, repeat target vessel revascularization, and stroke.

RESULTS

The mean HbA1c level of the AC group was significantly lower than that of the MC and UC groups (6.04% ± 0.36% vs. 6.74% ± 0.14% vs. 8.39% ± 1.20%, p < 0.001). The incidence of MACCEs was significantly lower in the AC group than in the MC and UC groups (16.0% vs. 24.3% vs. 26.3%, p = 0.010), mostly driven by the incidence of stroke (4.4% vs. 14.0% vs. 11.4%, p = 0.013). Multivariate Cox regression analysis showed that only the AC group was associated with a reduced rate of MACCEs (hazard ratio, 0.499; 95% confidence interval, 0.316 to 0.786; p = 0.004) compared with the UC group.

CONCLUSION

Our study showed that intensive glycemic control (HbA1c level < 6.5%) is associated with improved clinical outcomes after PCI in patients with diabetes.

Modification of the Association Between Severe Hypoglycemia and Ischemic Heart Disease by Surrogates of Vascular Damage Severity in Type 1 Diabetes During ∼30 Years of Follow-up in the DCCT/EDIC Study

OBJECTIVE

Literature suggests that severe hypoglycemia (SH) may be linked to cardiovascular events only in older individuals with high cardiovascular risk score (CV-score). Whether a potential relationship between any-SH and cardiovascular disease exists and whether it is conditional on vascular damage severity in a young cohort with type 1 diabetes (T1D) without apparent macrovascular and no or mild-to-moderate microvascular complications at baseline is unknown.

RESEARCH DESIGN AND METHODS

We evaluated data of 1,441 Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications study volunteers (diabetes duration 1-15 years) followed for ∼30 years. Time-dependent associations between any-SH and ischemic heart disease (IHD: death, silent/nonfatal myocardial infarct, revascularization, or confirmed angina) and associations between interactions of any-SH with surrogates of baseline micro-/macrovascular damage severity and IHD were analyzed. Diabetes duration, steps on DCCT Early Treatment Diabetic Retinopathy Study severity scale (DCCT-ETDRS), Diabetes Complications Severity Index (DCSI), and CV-scores were considered as surrogates of baseline micro-/macrovascular damage severity.

RESULTS

Without interactions, in the minimally adjusted model controlling for confounding bias by age and HbA_1c, SH was a significant IHD factor (P = 0.003). SH remained a significant factor for IHD in fully adjusted models (P < 0.05). In models with interactions, interactions between SH and surrogates of microvascular complications severity, but not between SH and CV-score, were significant. Hazard ratios for IHD based on SH increased 1.19-fold, 1.32-fold, and 2.21-fold for each additional year of diabetes duration, DCCT-ETDRS unit, and DCSI unit, respectively. At time of IHD event, ∼15% of 110 participants with SH had high CV-scores.

CONCLUSIONS

In a young cohort with T1D with no baseline macrovascular complications, surrogates of baseline microvascular damage severity impact the effect of SH on IHD. Older age with high CV-score per se is not mandatory for an association of SH with IHD. However, the association is multifactorial.

Cardiovascular disease in diabetes, beyond glucose

Despite the decades-old knowledge that diabetes mellitus is a major risk factor for cardiovascular disease, the reasons for this association are only partially understood. While this association is true for both type 1 and type 2 diabetes, different pathophysiological processes may be responsible. Lipids and other risk factors are indeed important, whereas the role of glucose is less clear. This lack of clarity stems from clinical trials that do not unambiguously show that intensive glycemic control reduces cardiovascular events. Animal models have provided mechanisms that link diabetes to increased atherosclerosis, and evidence consistent with the importance of factors beyond hyperglycemia has emerged. We review clinical, pathological, and animal studies exploring the pathogenesis of atherosclerosis in humans living with diabetes and in mouse models of diabetes. An increased effort to identify risk factors beyond glucose is now needed to prevent the increased cardiovascular disease risk associated with diabetes.

Sex-related disparities in the incidence and outcomes of hemorrhagic stroke among type 2 diabetes patients: a propensity score matching analysis using the Spanish National Hospital Discharge Database for the period 2016-18

Background

To analyze incidence, use of therapeutic procedures, use of oral anticoagulants (OACs) and antiplatelet agents prior to hospitalization, and in-hospital outcomes among patients who were hospitalized with hemorrhagic stroke (HS) according to the presence of type 2 diabetes mellitus (T2DM) in Spain (2016–2018) and to assess the role of sex differences among those with T2DM.

Methods

Using the Spanish National Hospital Discharge Database we estimated the incidence of HS hospitalizations in men and women aged ≥ 35 years with and without T2DM. Propensity score matching (PSM) was used to compare population subgroups according to sex and the presence of T2DM.

Results

HS was coded in 31,425 men and 24,975 women, of whom 11,915 (21.12%) had T2DM. The adjusted incidence of HS was significantly higher in patients with T2DM (both sexes) than in non-T2DM individuals (IRR 1.15; 95% CI 1.12–1.17). The incidence of HS was higher in men with T2DM than in T2DM women (adjusted IRR 1.60; 95% CI 1.57–1.63). After PSM, men and women with T2DM have significantly less frequently received decompressive craniectomy than those without T2DM. In-hospital mortality (IHM) was higher among T2DM women than matched non-T2DM women (32.89% vs 30.83%; p = 0.037), with no differences among men. Decompressive craniectomy was significantly more common in men than in matched women with T2DM (5.81% vs. 3.33%; p < 0.001). IHM was higher among T2DM women than T2DM men (32.89% vs. 28.28%; p < 0.001). After adjusting for confounders with multivariable logistic regression, women with T2DM had a 18% higher mortality risk than T2DM men (OR 1.18; 95% CI 1.07–1.29). Use of OACs and antiplatelet agents prior to hospitalization were associated to higher IHM in men and women with and without T2DM.

Conclusions

T2DM is associated with a higher incidence of HS and with less frequent use of decompressive craniectomy in both sexes, but with higher IHM only among women. Sex differences were detected in T2DM patients who had experienced HS, with higher incidence rates, more frequent decompressive craniectomy, and lower IHM in men than in women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01334-2.

Prediction of transient ischemic attack and minor stroke in people with type 2 diabetes mellitus

AIMS

People with type 2 diabetes (T2DM) have an increased risk of transient ischemic attack and minor stroke (TIA) which are frequently followed by an ischemic stroke. We aimed to develop a predictive model for incident TIA in people with T2DM.

METHODS

We pooled data from two longitudinal cohort studies, Atherosclerosis Risk in Communities (ARIC) and the Cardiovascular Health Study (CHS), using a two-stage approach. First, we used a random effects model to interpolate risk factors of individuals between follow-up exams. Second, we used forward selection to develop a proportional hazards model for time to incident TIA. We internally validated our model using 10-fold cross-validation.

RESULTS

Among 3575 participants with T2DM, mean (SD) age was 60 (10) years and body mass index was 30 (6) kg/m2. Sixty-nine incident TIAs occurred during 38,364 person-years of follow-up. The multivariable model included age at diagnosis of diabetes (hazard ratio 1.13 (95% confidence interval: 1.05,1.21) per year), systolic blood pressure (1.25 (1.04,1.49) per 10 mmHg), a quadratic function of diastolic blood pressure, and history of congestive heart failure (2.08 (1.26, 3.42)). The median cross-validated Harrell's C-index was 0.80.

CONCLUSION

Blood pressure and heart failure are risk factors for the earliest stages of cerebrovascular disease.

Sex-Related Disparities in the Incidence and Outcomes of Ischemic Stroke among Type 2 Diabetes Patients. A Matched-Pair Analysis Using the Spanish National Hospital Discharge Database for Years 2016-2018

Background: To analyze the incidence, use of therapeutic procedures, and in-hospital outcomes among patients suffering an ischemic stroke (IS) according to the presence of type 2 diabetes mellitus (T2DM) in Spain (2016–2018) and to assess the existence of sex differences. Methods: Matched-pair analysis using the Spanish National Hospital discharge. Results: IS was coded in 92,524 men and 79,731 women (29.53% with T2DM). The adjusted incidence of IS (IRR 2.02; 95% CI 1.99–2.04) was higher in T2DM than non-T2DM subjects, with higher IRRs in both sexes. Men with T2DM had a higher incidence of IS than T2DM women (IRR 1.54; 95% CI 1.51–1.57). After matching patients with T2DM, those with other comorbid conditions, however, significantly less frequently received endovascular thrombectomy and thrombolytic therapy. In-hospital mortality (IHM) was lower among T2DM men than matched non-T2DM men (8.23% vs. 8.71%; p < 0.001). Women with T2DM had a higher IHM rate than T2DM men (11.5% vs. 10.20%; p = 0.004). After adjusting for confounders, women with T2DM had a 12% higher mortality risk than T2DM men (OR 1.12; 95% CI 1.04–1.21). Conclusions: T2DM is associated with higher incidence of IS in both sexes. Men with T2DM have a higher incidence rates of IS than T2DM women. Women with T2DM have a higher risk of dying in the hospital.

Diabetes, stroke, and neuroresilience: looking beyond hyperglycemia

Ischemic stroke is a leading cause of morbidity and mortality among type 2 diabetic patients. Preclinical and translational studies have identified critical pathophysiological mediators of stroke risk, recurrence, and poor outcome in diabetic patients, including endothelial dysfunction and inflammation. Most clinical trials of diabetes and stroke have focused on treating hyperglycemia alone. Pioglitazone has shown promise in secondary stroke prevention for insulin-resistant patients; however, its use is not yet widespread. Additional research into clinical therapies directed at diabetic pathophysiological processes to prevent stroke and improve outcome for diabetic stroke survivors is necessary. Resilience is the process of active adaptation to a stressor. In patients with diabetes, stroke recovery is impaired by insulin resistance, endothelial dysfunction, and inflammation, which impair key neuroresilience pathways maintaining cerebrovascular integrity, resolving poststroke inflammation, stimulating neural plasticity, and preventing neurodegeneration. Our review summarizes the underpinnings of stroke risk in diabetes, the clinical consequences of stroke in diabetic patients, and proposes hypotheses and new avenues of research for therapeutics to stimulate neuroresilience pathways and improve stroke outcome in diabetic patients.

Pharmacotherapeutic considerations for the management of diabetes mellitus among hospitalized COVID-19 patients

INTRODUCTION

Diabetes mellitus is one of the most prevalent comorbidities identified in patients with coronavirus disease 2019 (COVID-19). This article aims to discuss the pharmacotherapeutic considerations for the management of diabetes in hospitalized patients with COVID-19.

AREAS COVERED

We discussed various aspects of pharmacotherapeutic management in hospitalized patients with COVID-19: (i) susceptibility and severity of COVID-19 among individuals with diabetes, (ii) glycemic goals for hospitalized patients with COVID-19 and concurrent diabetes, (iii) pharmacological treatment considerations for hospitalized patients with COVID-19 and concurrent diabetes.

EXPERT OPINION

The glycemic goals in patients with COVID-19 and concurrent type 1 (T1DM) or type 2 diabetes (T2DM) are to avoid disruption of stable metabolic state, maintain optimal glycemic control, and prevent adverse glycemic events. Patients with T1DM require insulin therapy at all times to prevent ketosis. The management strategies for patients with T2DM include temporary discontinuation of certain oral antidiabetic agents and consideration for insulin therapy. Patients with T2DM who are relatively stable and able to eat regularly may continue with oral antidiabetic agents if glycemic control is satisfactory. Hyperglycemia may develop in patients with systemic corticosteroid treatment and should be managed upon accordingly.

Established and novel gender dimorphisms in type 2 diabetes mellitus: Insights from a multiethnic cohort

BACKGROUND AND AIMS

In type 2 diabetes mellitus (T2DM), sexual dimorphisms modulate the natural histories of hyperglycemia, anthropophysical/cardiometabolic phenotype, and susceptibility to chronic micro and macrovascular complications. The purpose of this work was to revisit known or new dimorphisms within a multiethnic cohort.

METHODS

Among 1238 T2DM patients, men (63%) were compared to women (37%), including leading ethnicities: Whites (67.4%; 542 men; 293 women); Maghrebians (9.4%; 62 men; 54 women); and Blacks (12.5%; 92 men; 63 women).

RESULTS

Age, BMI, diabetes duration, insulin sensitivity, B-cell function loss, HbA1c, and hyperglycemia index were similar in both genders. All-cause microangiopathy and cerebrovascular disease did not differ between sexes. Women had significantly more retinopathy (27% vs. 21%) and men more microalbuminuria (25% vs. 19%), all-cause macroangiopathy (40% vs. 26%), CAD (29% vs. 17%) and PAD (11% vs. 6%). Among Blacks, sexual dimorphism in terms of retinopathy was more pronounced (24% in women vs. 11%), while there was no sexual dimorphism in all-cause macroangiopathy, CAD or PAD. B-cell function loss was faster among North African men (+15%), who also had more hepatic steatosis (+27%) than women.

CONCLUSIONS

T2DM abolishes the CV protection provided by the female gender in Blacks. In White women, the loss of CV protection in diabetes is limited to cerebrovascular disease. In Black women, a markedly increased risk of retinopathy is present, despite glycemic exposure similat to men. Sexual dimorphisms do not affect glucose homeostasis and metabolic control in all ethnicities, except for lesser B-cell function loss in Maghrebian women.

Toxicity of Metformin and Hypoglycemic Therapies

Metformin along with other antidiabetic medications provide benefit to patients in the treatment of type 2 diabetes mellitus, but caution is advised in certain scenarios to avoid toxicity in kidney disease. Renal dosing, monitoring of kidney function, and evaluating the risk of developing serious side effects are warranted with some agents. The available literature with regard to incidence of adverse events and toxicity of hypoglycemic therapies is reviewed.

Non-Communicable Diseases on the Rise in Sub-Saharan Africa, the Underappreciated Threat of a Dual Disease Burden

In sub-Saharan Africa, the burden of non-communicable diseases (NCDs) remains under appreciated, but emerging evidence suggests it to be substantial. NCDs such as arterial hypertension, heart diseases, diabetes mellitus and chronic kidney diseases are especially relevant, and put additional strain on the already challenged health systems in this region. Moreover, NCDs appear to be associated with higher mortality and morbidity rates and are more common in younger population groups, in people from sub-Saharan Africa when compared to more developed countries. In this review, we summarize the current literature on the burden of NCDs in sub-Saharan Africa, and highlight the clinical implications of the most relevant etiologies, i.e. arterial hypertension, heart diseases, diabetes mellitus and chronic kidney diseases.

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

OBJECTIVE

Stroke is a major cause of disability and death worldwide. People with diabetes are at a twofold to fivefold increased risk for stroke compared with people without diabetes. This study systematically reviews the literature on available stroke prediction models specifically developed or validated in patients with diabetes and assesses their predictive performance through meta-analysis.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

A detailed search was performed in MEDLINE, PubMed and EMBASE (from inception to 22 April 2019) to identify studies describing stroke prediction models.

ELIGIBILITY CRITERIA

All studies that developed stroke prediction models in populations with diabetes were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently identified eligible articles and extracted data. Random effects meta-analysis was used to obtain a pooled C-statistic.

RESULTS

Our search retrieved 26 202 relevant papers and finally yielded 38 stroke prediction models, of which 34 were specifically developed for patients with diabetes and 4 were developed in general populations but validated in patients with diabetes. Among the models developed in those with diabetes, 9 reported their outcome as stroke, 23 reported their outcome as composite cardiovascular disease (CVD) where stroke was a component of the outcome and 2 did not report stroke initially as their outcome but later were validated for stroke as the outcome in other studies. C-statistics varied from 0.60 to 0.92 with a median C-statistic of 0.71 (for stroke as the outcome) and 0.70 (for stroke as part of a composite CVD outcome). Seventeen models were externally validated in diabetes populations with a pooled C-statistic of 0.68.

CONCLUSIONS

Overall, the performance of these diabetes-specific stroke prediction models was not satisfactory. Research is needed to identify and incorporate new risk factors into the model to improve models' predictive ability and further external validation of the existing models in diverse population to improve generalisability.

Development and Validation of PREDICT-DM: A New Microsimulation Model to Project and Evaluate Complications and Treatments of Type 2 Diabetes Mellitus

Background: Type 2 diabetes mellitus (T2DM) affects ∼30 million people in the United States and ∼400 million people worldwide, numbers likely to increase due to the rising prevalence of obesity. We sought to design, develop, and validate PREDICT-DM (PRojection and Evaluation of Disease Interventions, Complications, and Treatments-Diabetes Mellitus), a state-transition microsimulation model of T2DM, incorporating recent data. Methods: PREDICT-DM is populated with natural history, risk factor, and outcome data from large-scale cohort studies and randomized clinical trials. The model projects diabetes-relevant outcomes, including cardiovascular and renal disease outcomes, and 5/10-year survival. We assessed the model validity against 62 endpoints from ACCORD (Action to Control Cardiovascular Risk in Diabetes), VADT (Veterans Affairs Diabetes Trial), and Look AHEAD trials via several comparative statistical methods, including mean absolute percentage error (MAPE), Bland-Altman graphs, and Kaplan-Meier curves. Results: For the comparison between simulated and observed outcomes of the intervention/control arms of the trial, the MAPE was 19%/25% (ACCORD), 29%/20% (VADT), and 42%/10% (Look AHEAD). The Bland-Altman's 95% limit of agreement was 0.02 (ACCORD), 0.03 (VADT), and 0.01 (Look AHEAD), and the mean difference (95% confidence interval) for the comparison between PREDICT-DM and trial endpoints was 0.0025 (-0.0018 to 0.0070) for ACCORD, -0.0067 (-0.0137 to 0.0002) for VADT, and -0.0033 (-0.0067 to 0.00002) for Look AHEAD, indicating an adequate model fit to the data. The model-driven Kaplan-Meier curves were similarly close to those previously published. Conclusions: PREDICT-DM can reasonably predict clinical outcomes from ACCORD and other clinical trials of U.S. patients with T2DM. This model may be leveraged to inform clinical strategy questions related to the management and care of T2DM in the United States.

A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography

PURPOSE OF REVIEW

Cardiovascular disease (CVD) and stroke risk assessment have been largely based on the success of traditional statistically derived risk calculators such as Pooled Cohort Risk Score or Framingham Risk Score. However, over the last decade, automated computational paradigms such as machine learning (ML) and deep learning (DL) techniques have penetrated into a variety of medical domains including CVD/stroke risk assessment. This review is mainly focused on the changing trends in CVD/stroke risk assessment and its stratification from statistical-based models to ML-based paradigms using non-invasive carotid ultrasonography.

RECENT FINDINGS

In this review, ML-based strategies are categorized into two types: non-image (or conventional ML-based) and image-based (or integrated ML-based). The success of conventional (non-image-based) ML-based algorithms lies in the different data-driven patterns or features which are used to train the ML systems. Typically these features are the patients' demographics, serum biomarkers, and multiple clinical parameters. The integrated (image-based) ML-based algorithms integrate the features derived from the ultrasound scans of the arterial walls (such as morphological measurements) with conventional risk factors in ML frameworks. Even though the review covers ML-based system designs for carotid and coronary ultrasonography, the main focus of the review is on CVD/stroke risk scores based on carotid ultrasound. There are two key conclusions from this review: (i) fusion of image-based features with conventional cardiovascular risk factors can lead to more accurate CVD/stroke risk stratification; (ii) the ability to handle multiple sources of information in big data framework using artificial intelligence-based paradigms (such as ML and DL) is likely to be the future in preventive CVD/stroke risk assessment.

Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach

PURPOSE

Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of a combination of CCVRFs and CUSIP together were ranked. Further, an optimal risk calculator using AtheroEdge composite risk score (AECRS1.0) was designed and benchmarked against seven conventional CV risk (CVR) calculators.

METHODS

Two types of ranking were performed: (i) ranking of 26 CVR factors and (ii) ranking of eight types of 10-year risk calculators. In the first case, multivariate logistic regression was used to compute the odds ratio (OR) and in the second, receiver operating characteristic curves were used to evaluate the performance of eight types of CVR calculators using SPSS23.0 and MEDCALC12.0 with validation against STATA15.0.

RESULTS

The left and right common carotid arteries (CCA) of 202 Japanese patients were examined to obtain 404 ultrasound scans. CUSIP ranked in the top 50% of the 26 covariates. Intima-media thickness variability (IMTV) and IMTV_10yr were the most influential carotid phenotypes for left CCA (OR = 250, P < 0.0001 and OR = 207, P < 0.0001 respectively) and right CCA (OR = 1614, P < 0.0001 and OR = 626, P < 0.0001 respectively). However, for the mean CCA, AECRS1.0 and AECRS1.0_10yr reported the most highly significant OR among all the CVR factors (OR = 1.073, P < 0.0001 and OR = 1.104, P < 0.0001). AECRS1.0_10yr also reported highest area-under-the-curve (AUC = 0.904, P < 0.0001) compared to seven types of conventional calculators. Age and glycated haemoglobin reported highest OR (1.96, P < 0.0001 and 1.05, P = 0.012) among all other CCVRFs.

CONCLUSION

AECRS1.0_10yr demonstrated the best performance due to presence of CUSIP and ranked at the first place with highest AUC.

Assessing the Effect of Clinical Inertia on Diabetes Outcomes: a Modeling Approach

BACKGROUND

There are an increasing number of newer and better therapeutic options in the management of diabetes. However, a large proportion of diabetes patients still experience delays in intensification of treatment to achieve appropriate blood glucose targets-a phenomenon called clinical inertia. Despite the high prevalence of clinical inertia, previous research has not examined its long-term effects on diabetes-related health outcomes and mortality.

OBJECTIVE

We sought to examine the impact of clinical inertia on the incidence of diabetes-related complications and death. We also examined how the impact of clinical inertia would vary by the length of treatment delay and population characteristics.

DESIGN

We developed an agent-based model of diabetes and its complications. The model was parameterized and validated by data from health surveys, cohort studies, and trials.

SUBJECTS

We studied a simulated cohort of patients with diabetes in San Antonio, TX.

MAIN MEASURES

We examined 25-year incidences of diabetes-related complications, including retinopathy, neuropathy, nephropathy, and cardiovascular disease.

KEY RESULTS

One-year clinical inertia could increase the cumulative incidences of retinopathy, neuropathy, and nephropathy by 7%, 8%, and 18%, respectively. The effects of clinical inertia could be worse for populations who have a longer treatment delay, are aged 65 years or older, or are non-Hispanic whites.

CONCLUSION

Clinical inertia could result in a substantial increase in the incidence of diabetes-related complications and mortality. A validated agent-based model can be used to study the long-term effect of clinical inertia and, thus, inform clinicians and policymakers to design effective interventions.

Comparison of Recommendations and Use of Cardiovascular Risk Equations by Health Technology Assessment Agencies and Clinical Guidelines

OBJECTIVES

To identify risk equations for cardiovascular diseases (CVDs) in primary and secondary prevention settings that are used or recommended by health technology assessment (HTA) organizations and in clinical guidelines (CGs).

METHODS

A targeted literature review was conducted using a two-stage search strategy. First, HTA reviews of manufacturers' drug submissions, reports from established HTA organizations (Europe, Canada, and Australia), and CGs from countries with and without HTA organizations, including the United States, were identified. Documents published between September 30, 2006 and September 30, 2016, were examined for cardiovascular risk equations, recommendations, and commentaries. Next, publications associated with risk equations and cited by HTA and CG documents were retrieved. This literature was examined to extract commentaries and risk equation study characteristics.

RESULTS

The review identified 47 risk equations, 25 in the primary CVD prevention setting (i.e., patients with no CVD history), including 5 for CVD prevention in diabetes and 22 solely in secondary prevention settings; 11 were identified for heart failure, 3 for stroke or transient ischemic attack, 2 for stable angina, and 11 for acute coronary syndrome or related conditions. A small set of primary prevention equations was found to be commonly used by HTAs, whereas secondary prevention equations were less common in HTA documents. CGs provided more risk equations as options than HTA documents.

CONCLUSIONS

Although there is an abundance of risk equations developed for primary and secondary prevention, there remains a need for additional research to provide sufficient clinical and HTA guidance for risk estimation, particularly in high-risk or secondary prevention settings.

Effects of Severe Hypoglycemia on Cardiovascular Outcomes and Death in the Veterans Affairs Diabetes Trial

OBJECTIVE

To determine the risk factors for severe hypoglycemia and the association between severe hypoglycemia and serious cardiovascular adverse events and cardiovascular and all-cause mortality in the Veterans Affairs Diabetes Trial (VADT).

RESEARCH DESIGN AND METHODS

This post hoc analysis of data from the VADT included 1,791 military veterans (age 60.5 ± 9.0 years) with suboptimally controlled type 2 diabetes (HbA1c 9.4 ± 2.0%) of 11.5 ± 7.5 years disease duration with or without known cardiovascular disease and additional cardiovascular risk factors. Participants were randomized to intensive (HbA1c <7.0%) versus standard (HbA1c <8.5%) glucose control.

RESULTS

The rate of severe hypoglycemia in the intensive treatment group was 10.3 per 100 patient-years compared with 3.7 per 100 patient-years in the standard treatment group (P < 0.001). In multivariable analysis, insulin use at baseline (P = 0.02), proteinuria (P = 0.009), and autonomic neuropathy (P = 0.01) were independent risk factors for severe hypoglycemia, and higher BMI was protective (P = 0.017). Severe hypoglycemia within the past 3 months was associated with an increased risk of serious cardiovascular events (P = 0.032), cardiovascular mortality (P = 0.012), and total mortality (P = 0.024). However, there was a relatively greater increased risk for total mortality in the standard group compared with the intensive group (P = 0.019). The association between severe hypoglycemia and cardiovascular events increased significantly as overall cardiovascular risk increased (P = 0.012).

CONCLUSIONS

Severe hypoglycemic episodes within the previous 3 months were associated with increased risk for major cardiovascular events and cardiovascular and all-cause mortality regardless of glycemic treatment group assignment. Standard therapy further increased the risk for all-cause mortality after severe hypoglycemia.

Healthcare Cost Development in a Type 2 Diabetes Patient Population on Glucose-Lowering Drug Treatment: A Nationwide Observational Study 2006-2014

OBJECTIVE

The objective of this study was to describe healthcare resource use and cost development in Sweden during 2006-2014 in a type 2 diabetes (T2D) population receiving glucose-lowering drugs (GLDs).

METHODS

In- and outpatient healthcare resource use and costs were extracted from mandatory national registries: the Cause of Death Register; the National Patient Register; and the Prescribed Drug Register. Primary care data were estimated based on an observational study including patients from 84 primary care centers in Sweden. Numbers of any cause inpatient, outpatient, and primary care contacts were extracted and direct healthcare costs were estimated.

RESULTS

During 2006-2014, the number of inpatient and primary care contacts increased by approximately 70% (from 45,559 to 78,245 and from 4.9 to 8.8 million, respectively) and outpatient care contacts almost doubled (from 105,653 to 209,417). Mean annual per patient costs increased by 13%, reaching €4594. Total healthcare costs increased from €835 million to €1.684 billion. Inpatient care costs constituted 47% of total costs in 2014 (€783 million), primary care accounted for 24% (€405 million), outpatient care 18% (€303 million), non-GLD medications 6% (€109 million), and GLDs 5% (€84 million). Cardiovascular diseases (CVDs) were the most costly disease group in inpatient care (26%), whereas managing unspecified factors influencing health and T2D-associated diseases were the most costly in outpatient care (16 and 11%, respectively).

CONCLUSIONS

The healthcare costs of the GLD-treated T2D population doubled during 2006-2014, mostly driven by the increasing size of this population, of which inpatient care accounted for 47%. GLDs constituted the smallest share of costs. CVD was the most resource-requiring disease group.

Stroke Outcome and Determinants among Patients with and without Diabetes in a Tertiary Hospital in Ghana

BACKGROUND

Diabetes mellitus, a well-established independent risk factor for stroke, has varied association with stroke outcome from previous studies. This study investigated stroke outcome and determinants among patients with and without diabetes in a tertiary hospital in Ghana.

METHODS

A prospective study conducted among stroke patients with and without diabetes admitted in a Ghanaian tertiary hospital. Baseline clinical and biochemical data were documented. Functional stroke outcome was evaluated at 1, 3, and 6 months after stroke using the modified Rankin Scale.

RESULTS

Number of participants enrolled were 326 and 105 (32.20%) had diabetes. Higher proportions of diabetes patients had poor functional stroke outcome at 1, 3, and 6 months (79%, 75.23%, 73.33%) compared with those without diabetes (70.13%, 65.16, 61.99) (p>0.05). Stroke patients with diabetes had lower survival compared with those without diabetes (p=0.0745). Mortality at 6 months was more likely among ischaemic stroke patients with diabetes compared with those without diabetes (Odds Ratio 2.037; CI: 1.058-3.923). Determinants of poor functional stroke outcome for diabetes patients were older age (Adjusted Odds Ratio (AOR)-1.07; CI-1.03-1.12), female gender (AOR-3.74; CI-1.26-12.65), and pneumonia (AOR-11.32; CI-1.93-220.05) whereas the determinants for those without diabetes were unemployment (AOR-4.19; CI-1.24-19.50), speech abnormalities (AOR-1.99; CI1.08-3.73), and pneumonia (AOR-4.05; CI-1.83-9.77). High fasting plasma glucose (HR-1.15; CI-1.07-1.23), elevated temperature (HR-1.41; CI-1.11-1.79), and pneumonia (HR-2.25; CI-1.44-3.50) were determinants of low survival among all stroke patients.

CONCLUSION

Trends towards poorer functional outcome and reduced survival were found among Ghanaian stroke patients with diabetes compared with those without diabetes. Older age, female gender, pneumonia, elevated temperature, and fasting plasma glucose were determinants of adverse outcome in stroke patients with diabetes.

Streptozotocin‑induced diabetic mice exhibit reduced experimental choroidal neovascularization but not corneal neovascularization

The present study aimed to investigate the effects of diabetes mellitus (DM) on the generation of experimental corneal neovascularization (CrNV) and choroidal neovascularization (ChNV). Diabetes was induced in mice by intraperitoneal injection of streptozotocin (STZ). Experimental CrNV and ChNV were induced by alkali injury and laser photocoagulation, respectively. CrNV and ChNV were compared between the STZ‑induced diabetic mice and control mice two weeks after injury. Relative expression of angiogenic factors was quantified by reverse transcription‑quantitative polymerase chain reaction, and progenitor cell or macrophage accumulation in the early phase following injury was examined by flow cytometric analysis. Compared with the alkali‑injured normal mice, the alkali‑injured diabetic mice (STZ‑induced) exhibited no significant difference in CrNV occurrence, whereas the laser‑injured diabetic mice exhibited significantly reduced levels of ChNV compared with those of the laser‑injured control animals. The laser‑induced intrachoroidal mRNA expression levels of angiogenic factors, including vascular endothelial growth factor, hypoxia‑induced factor‑1α, chemokine (C‑C motif) ligand 3, and stromal cell‑derived factor‑1α, were reduced in the laser‑injured diabetic mice when compared with laser‑injured control mice. Furthermore, the laser‑induced intrachoroidal infiltration of c‑Kit+ progenitor cells was impaired in the laser‑injured diabetic mice compared with the laser‑injured control mice. Overall, diabetes did not exert a significant effect on the generation of experimental CrNV. However, diabetes reduced laser‑induced ChNV through downregulation of intrachoroidal progenitor cell infiltration and angiogenic factor expression.

Development of predictive risk models for major adverse cardiovascular events among patients with type 2 diabetes mellitus using health insurance claims data

Background

There exist several predictive risk models for cardiovascular disease (CVD), including some developed specifically for patients with type 2 diabetes mellitus (T2DM). However, the models developed for a diabetic population are based on information derived from medical records or laboratory results, which are not typically available to entities like payers or quality of care organizations. The objective of this study is to develop and validate models predicting the risk of cardiovascular events in patients with T2DM based on medical insurance claims data.

Methods

Patients with T2DM aged 50 years or older were identified from the Optum™ Integrated Real World Evidence Electronic Health Records and Claims de-identified database (10/01/2006–09/30/2016). Risk factors were assessed over a 12-month baseline period and cardiovascular events were monitored from the end of the baseline period until end of data availability, continuous enrollment, or death. Risk models were developed using logistic regressions separately for patients with and without prior CVD, and for each outcome: (1) major adverse cardiovascular events (MACE; i.e., non-fatal myocardial infarction, non-fatal stroke, CVD-related death); (2) any MACE, hospitalization for unstable angina, or hospitalization for congestive heart failure; (3) CVD-related death. Models were developed and validated on 70% and 30% of the sample, respectively. Model performance was assessed using C-statistics.

Results

A total of 181,619 patients were identified, including 136,544 (75.2%) without prior CVD and 45,075 (24.8%) with a history of CVD. Age, diabetes-related hospitalizations, prior CVD diagnoses and chronic pulmonary disease were the most important predictors across all models. C-statistics ranged from 0.70 to 0.81, indicating that the models performed well. The additional inclusion of risk factors derived from pharmacy claims (e.g., use of antihypertensive, and use of antihyperglycemic) or from medical records and laboratory measures (e.g., hemoglobin A1c, urine albumin to creatinine ratio) only marginally improved the performance of the models.

Conclusion

The claims-based models developed could reliably predict the risk of cardiovascular events in T2DM patients, without requiring pharmacy claims or laboratory measures. These models could be relevant for providers and payers and help implement approaches to prevent cardiovascular events in high-risk diabetic patients.

Electronic supplementary material

The online version of this article (10.1186/s12933-018-0759-z) contains supplementary material, which is available to authorized users.

Age and Sex Are Critical Factors in Ischemic Stroke Pathology

Ischemic stroke is a devastating brain injury resulting in high mortality and substantial loss of function. Understanding the pathophysiology of ischemic stroke risk, mortality, and functional loss is critical to the development of new therapies. Age and sex have a complex and interactive effect on ischemic stroke risk and pathophysiology. Aging is the strongest nonmodifiable risk factor for ischemic stroke, and aged stroke patients have higher mortality and morbidity and poorer functional recovery than their young counterparts. Importantly, patient age modifies the influence of patient sex in ischemic stroke. Early in life, the burden of ischemic stroke is higher in men, but stroke becomes more common and debilitating for women in elderly populations. The profound effects of sex and age on clinical ischemic stroke are mirrored in the results of experimental in vivo and in vitro studies. Here, we review current knowledge on the influence of age and sex in the incidence, mortality, and functional outcome of ischemic stroke in clinical populations. We also discuss the experimental evidence for sex and age differences in stroke pathophysiology and how a better understanding of these biological variables can improve clinical care and enhance development of novel therapies.

Relationship Between Glycated Hemoglobin and Stroke Risk: A Systematic Review and Meta-Analysis

BACKGROUND

Diabetes mellitus is a major risk factor for ischemic stroke. Rising hemoglobin A_1c (HbA_1c) levels are associated with microvascular diabetes mellitus complication development; however, this relationship has not been established for stroke risk, a macrovascular complication.

METHODS AND RESULTS

We conducted a systematic review and meta-analysis of observational cohort and nested case-control cohort studies assessing the association between rising HbA_1c levels and stroke risk in adults (≥18 years old) with and without type 1 or type 2 diabetes mellitus. Random-effects model meta-analyses were used to calculate pooled adjusted hazard ratios (HRs) and their precision. The systematic review yielded 36 articles, of which 29 articles (comprising n=532 779 participants) were included in our meta-analysis. Compared to non-diabetes mellitus range HbA_1c (<5.7%), diabetes mellitus range HbA_1c (≥6.5%) was associated with an increased risk of first-ever stroke with average HR (95% confidence interval) of 2.15 (1.76, 2.63), whereas pre-diabetes mellitus range HbA_1c (5.7-6.5%) was not (average HR [95% confidence interval], 1.19 [0.87, 1.62]). For every 1% HbA_1c increment (or equivalent), the average HR (95% confidence interval) for first-ever stroke was 1.12 (0.91, 1.39) in non-diabetes mellitus cohorts and 1.17 (1.09, 1.25) in diabetes mellitus cohorts. For every 1% HbA_1c increment, both non-diabetes mellitus and diabetes mellitus cohorts had a higher associated risk of first-ever ischemic stroke with average HR (95% confidence interval) of 1.49 (1.32, 1.69) and 1.24 (1.11, 1.39), respectively.

CONCLUSIONS

A rising HbA_1c level is associated with increased first-ever stroke risk in cohorts with a diabetes mellitus diagnosis and increased risk of first-ever ischemic stroke in non-diabetes mellitus cohorts. These findings suggest that more intensive HbA_1c glycemic control targets may be required for optimal ischemic stroke prevention.

Establishment and validation of a prediction model for ischemic stroke risks in patients with type 2 diabetes

AIMS

A risk scoring system for predicting ischemic stroke incidence may identify type 2 diabetes patients at high risk for ischemic stroke who can benefit from preventive intervention programs. Such a risk scoring system can serve as a benchmark to test novel putative risk factors.

METHODS

The study adopted a retrospective cohort, including 28,124 Chinese patients with type 2 diabetes aged 30-84 years during 2001-2004. Participants were randomly assigned to the derivation and validation sets at a 2:1 ratio. Cox's proportional hazard regression model was used to identify risk factors of ischemic stroke incidence in the derivation set. And then the steps proposed by the Framingham Heart Study for establishing an ischemic stroke prediction model with a scoring system was used.

RESULTS

Among 9374 patients in the validation set, 1076 subjects (11.48%) developed ischemic stroke with a mean follow up period of 8.0 years. We identified the following risk factors: age, gender, smoking habit, duration of type 2 diabetes, blood pressure, HbA1c level, total cholesterol to high-density lipoprotein ratio, creatinine, fasting plasma glucose variation (FPG-CV), arterial embolism and thrombosis, diabetes retinopathy, hypoglycemia, anti-diabetes medication use, and cardiovascular medication. The area under receiver operating characteristic curve of the 3-year, 5-year, and 8-year ischemic stroke incidence risks were 0.72, 0.71, and 0.68 for the validation set, respectively.

CONCLUSIONS

This proposed ischemic stroke incidence risk prediction model is the first model established for Chinese patients with type 2 diabetes recruited from nationwide clinical settings.

STOP-Bang questionnaire screening for obstructive sleep apnea among Chinese patients with type 2 diabetes mellitus

Introduction

The aim of the current study was to evaluate the efficiency of the STOP-Bang questionnaire for obstructive sleep apnea (OSA) screening among Chinese patients with type 2 diabetes mellitus (T2DM).

Material and methods

A total of 262 patients with T2DM were enrolled for STOP-Bang questionnaire evaluation and polysomnography (PSG) monitoring between May 2015 and September 2016. Patients were divided into non-OSA and different OSA severity groups (mild, moderate, and severe) according to the apnea-hypopnea index (AHI). The value of the STOP-Bang questionnaire for OSA screening was evaluated.

Results

Efficiency of the STOP-Bang questionnaire for OSA screening among Chinese patients with T2DM was as follows: when AHI ≥ 5/h, the area under the curve (AUC) was 0.825 (95% confidence interval (CI): 0.763–0.887, p < 0.05), sensitivity was 85.6% (95% CI: 85.55–85.65%, p < 0.05) and specificity was 60% (95% CI: 59.85–60.15%, p < 0.05); when AHI > 15/h, the AUC was 0.856 (95% CI: 0.799–0.913, p < 0.05), sensitivity was 88.6% (95% CI: 88.55–88.65%, p < 0.05) and specificity was 38.4% (95% CI: 38.30–38.49%, p < 0.05); when AHI > 30/h, the AUC was 0.891 (95% CI: 0.836–0.946, p < 0.05), sensitivity was 90.5% (95% CI: 90.44–90.56%, p < 0.05), and specificity was 27% (95% CI: 26.94-27.07%, p < 0.05).

Conclusions

The STOP-Bang questionnaire is an effective tool for OSA screening among Chinese patients with T2DM. A cut-off score of 3 distinguishes OSA from non-OSA with high sensitivity.

Diabetes and complications of the heart in Sub-Saharan Africa: An urgent need for improved awareness, diagnostics and management

Type 2 diabetes mellitus is no longer a disease of high income countries but a global health pandemic. With the continued and rapid increase in its prevalence worldwide it is forecasted that diabetes will be a leading cause of morbidity and mortality. A major concern stems from its role in development and progression of cardiovascular disease, including cardiac dysfunction and heart failure. Within low- and middle-income areas such as Sub-Saharan Africa the burden of diabetes is already significant driven by many factors, including, socioeconomic (urbanisation), nutritional (high-calorie "western-diet", obesity) and lifestyle (physical inactivity) changes. Insufficient economic and community resources, poor health care system development and chronic disease management, poor education, and a lack of preventative and diagnostic measures further aggravate the severity of the diabetes problem. This review outlines the burden of type 2 diabetes mellitus in Sub-Saharan Africa and highlights the need for improved community health care and regulations to reduce its epidemiological spread and devastating impact on health.

The mixed benefit of low lipoprotein(a) in type 2 diabetes

Background

Lipoprotein(a) (Lp(a)), a variant low-density lipoprotein (LDL), is a major genetic risk factor for cardiovascular disease. It is unknown whether an inverse relationship exists between Lp(a) and β-cell function (BCF), as for LDL-cholesterol (LDL-C) lowering by statins.

We therefore assessedthe cardiometabolic phenotype of 340 men with type 2 diabetes mellitus (T2DM) in relation to Lp(a), focusing on BCF and hyperbolic product [BxS], which adjusts BCF to insulin sensitivity and secretion.

Methods

Two groups were analyzed according to Lp(a) quartiles (Q): a (very-)low Lp(a) (Q1;n = 85) vs a normal-to-high Lp(a) group (Q2-Q4;n = 255).

Results

In the overall cohort, mean Lp(a) was 52 nmol.L⁻¹. Median Lp(a) was 6 nmol.L⁻¹ (Q1) vs 38 nmol.L⁻¹ (Q2-Q4). There were no differences between groups regarding age; education; diabetes duration; body mass index; body composition and smoking. Q1 had significantly worse glycemic control, higher systolic blood pressure, more severe metabolic syndrome, and more frequent hepatic steatosis. Insulin sensitivity was significantly lower (− 37%) in Q1, who also had lesser hyperbolic product (− 27%), and higher [BxS] loss rate (+ 15%). Q1 also had higher frequency (+31%) and severity (+20%) of atherogenic dyslipidemia. Microangiopathy and neuropathy were higher in Q1 (+ 34% and + 48%, respectively), whereas Q2-Q4 patients had increased macroangiopathy (+ 51%) and coronary artery disease (CAD; + 94%).

Conclusions

Low Lp(a) appears both beneficial and unhealthy in T2DM. It is associated with unfavourable cardiometabolic phenotype, lesser BCF, poorer glycemic control, and increased microvascular damage despite being linked to markedly reduced CAD, suggesting that Lp(a)-related vascular risk) follows a J-shaped curve.