The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. 

https://www.ahajournals.org/doi/pdf/10.1161/CIR.0000000000001052

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). Methods: The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year’s worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year’s edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. 

Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association

The Framingham Heart Study has been a leader in the development and dissemination of multivariable statistical models to estimate the risk of coronary heart disease. These models quantify the impact of measurable and modifiable risk factors on the development of coronary heart disease and can be used to generate estimates of risk of coronary heart disease over a predetermined period, for example the next 10 years. We developed a system, which we call a points system, for making these complex statistical models useful to practitioners. The system is easy to use, it does not require a calculator or computer and it simplifies the estimation of risk based on complex statistical models. This system represents an effort to make available a tool for clinicians to aid in their decision-making process regarding treatment and to assist them in motivating patients toward healthy behaviours. The system is also readily available to patients who can easily estimate their own coronary heart disease risk and monitor this risk over time.

Likelihood Modelling: Presentation of Multivariate Data for Clinical Use: The Framingham Study Risk Score Functions

BACKGROUND
The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).


METHODS
The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.


RESULTS
Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.


CONCLUSIONS
The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.

BACKGROUND Identifying patients at high risk of diabetic kidney disease (DKD) helps improve clinical outcome. PURPOSE To establish a model for predicting DKD. DATA SOURCES The derivation cohort was from a meta-analysis. The validation cohort was from a Chinese cohort. STUDY SELECTION Cohort studies that reported risk factors of DKD with their corresponding risk ratios (RRs) in patients with type 2 diabetes were selected. All patients had estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 and urinary albumin-to-creatinine ratio (UACR) DATA EXTRACTION Risk factors and their corresponding RRs were extracted. Only risk factors with statistical significance were included in our DKD risk prediction model. DATA SYNTHESIS Twenty cohorts including 41,271 patients with type 2 diabetes were included in our meta-analysis. Age, BMI, smoking, diabetic retinopathy, hemoglobin A1c, systolic blood pressure, HDL cholesterol, triglycerides, UACR, and eGFR were statistically significant. All these risk factors were included in the model except eGFR because of the significant heterogeneity among studies. All risk factors were scored according to their weightings, and the highest score was 37.0. The model was validated in an external cohort with a median follow-up of 2.9 years. A cutoff value of 16 was selected with a sensitivity of 0.847 and a specificity of 0.677. LIMITATIONS There was huge heterogeneity among studies involving eGFR. More evidence is needed to power it as a risk factor of DKD. CONCLUSIONS The DKD risk prediction model consisting of nine risk factors established in this study is a simple tool for detecting patients at high risk of DKD.

https://care.diabetesjournals.org/content/diacare/43/4/925.full.pdf

Establishment and Validation of a Risk Prediction Model for Early Diabetic Kidney Disease Based on a Systematic Review and Meta-Analysis of 20 Cohorts.

Background Impaired glucose tolerance (IGT) is an important prediabetic stage characterized by elevated concentrations of glucose and insulin in the blood. The pathological hyperglycemia and hyperinsulinemia in IGT may regulate the expression of microRNA-21 (miR-21) and affect the downstream insulin signaling pathways, leading to endothelial cell dysfunction and early renal damage. Methods The individual and combined effects of insulin and glucose were investigated using human glomerular endothelial cells (HGECs). The expression levels of miR-21, and PTEN/AKT/eNOS and MAPK/ET-1 pathway proteins in the treated cells were measured. The levels of nitric oxide (NO) and endothelin-1 (ET-1) secreted by the cells were also measured. The role of miR-21 in mediating the regulatory effects of insulin and glucose was assessed by overexpression/inhibition of this miRNA using mimics/inhibitor. Results High (>16.7 mmol/L) concentration of glucose upregulated the expression of miR-21, leading to the activation and inhibition of the PTEN/AKT/eNOS and MAPK/ET-1 pathways, and upregulation of NO and downregulation of ET-1 secretion, respectively. High (>25 ng/mL) concentration of insulin downregulated the expression of miR-21, and lead to the activation of the MAPK/ET-1 and inhibition of the PTEN/AKT/eNOS pathway, thereby upregulating the expression of ET-1 and downregulating the secretion of NO. MiR-21 was observed to play a key role by directly controlling the activation of the insulin signaling pathways when the cells were cotreated with different concentrations of insulin and glucose. The expression of miR-21 was found to be dependent on the relative concentration of insulin and glucose. Under simulated conditions of the IGT stage (8.3 mmol/L glucose + 50 ng/mL insulin), the inhibitory effect of high insulin concentration on miR-21 expression in the cells attenuated the activation by high glucose concentration, resulting in the downregulation of miR-21, upregulation of ET-1 and downregulation of NO secretion. Conclusion Taken together, these results indicate that high insulin and glucose concentrations regulate the secretory function of glomerular endothelial cells in opposite ways by regulating the expression of miRNA-21. Pathological concentrations of insulin and glucose in the IGT stage may lead to a decrease in miR-21 expression, thereby disordering the secretion of vasoactive factors, resulting in renal tubule ischemia.

/pdf/pathological-hyperinsulinemia-and-hyperglycemia-in-the-1r0ht286f5.pdf

Pathological Hyperinsulinemia and Hyperglycemia in the Impaired Glucose Tolerance Stage Mediate Endothelial Dysfunction Through miR-21, PTEN/AKT/eNOS, and MARK/ET-1 Pathways.

Objective: To analyze the correlation between urinary albumin/creatinine ratio (ACR) and 24-hour urinary microalbumin (UMA) and evaluate the predictive value of ARC for early diabetic nephropathy. Methods: A total of 368 patients with type 2 diabetes mellitus were retrospectively collected. Early diabetic nephropathy was defined as 24h UMA 30~<300 mg/24h. The correlation between ACR and 24hUMA, and the area under the receiver operating characteristic (ROC) curve of ACR in diagnosis of early diabetic nephropathy were calculated. Gender, age, course of disease, fasting venous blood glucose, glycosylated hemoglobin, blood pressure, triglyceride and total cholesterol were used as adjusting variables to establish univariate and multivariate logistic models of ACR for early diabetic nephropathy, respectively. A regression model was used to evaluate the diagnostic value of ACR for early diabetic nephropathy. Results: The correlation between ACR and 24h UMA was 0.658. The area under ROC curve of ACR for early diabetic nephropathy was 0.907 before and 0.933 after adjustments of gender, age, course of disease, fasting venous blood glucose, glycosylated hemoglobin, blood pressure, triglyceride and total cholesterol, respectively. The OR value of ACR of diabetic nephropathy was 2.016 before and 2.762 after same adjustments. The calibration of Hosmer-Lemeshow chi-square test evaluation model was 19.362 before (P=0.13) and 14.928 after adjustments (P=0.061). Conclusion: ACR is a better predictor for early diabetic nephropathy although its value is influenced by gender, age, course of disease, blood sugar, lipid, and blood pressure.

[Can urine albumin/creatinine ratio replace 24 hours urinary albumin?]

Aims/introduction Hyperuricemia (HUA) occurs because of decreased excretion of uric acid, increased synthesis of uric acid or a combination of both mechanisms. The proportions of these three types of HUA in type 2 diabetes patients are not known. In the mean time, we assume that different types of HUA might manifest with different renal damage, even in patients with normal renal filtration function. Materials and methods We included 435 inpatients with type 2 diabetes at the Metabolic Disease Hospital of Tianjin Medical University from 2015 to 2016. Based on the clearance of uric acid, 90 patients with HUA were divided into three types: synthesis-increased HUA, excretion-decreased HUA and mixed type of HUA. Results Patients with the mixed type of HUA had the severest kidney injury manifested by a high level of 24 h urinary microalbumin, urinary immunoglobulin G, transferrin, α-galactosidase and β2-microglobulin compared with the normal uric acid group. Urinary immunoglobulin G, transferrin and α-galactosidase were also increased in patients with synthesis-increased HUA compared with the normal uric acid group. Patients with excretion-decreased HUA did not have an increased level of renal impairment markers; however, these patients had an increased body mass index, which might cause dysfunction of kidney excretion. Conclusions Excretion-decreased HUA is a more common type of HUA in type 2 diabetes patients that might be caused by dysfunction of tubular excretion instead of structural damage. The mixed type of HUA patients had the severest kidney glomerular and tubular damage compared with the normal uric acid group. Clinically, different types of hyperuricemia should be given individualized treatment according to their own characteristics.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jdi.12850

Renal impairment markers in type 2 diabetes patients with different types of hyperuricemia.

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Papers

Establishment and Validation of a Risk Prediction Model for Early Diabetic Kidney Disease Based on a Systematic Review and Meta-Analysis of 20 Cohorts.

Pathological Hyperinsulinemia and Hyperglycemia in the Impaired Glucose Tolerance Stage Mediate Endothelial Dysfunction Through miR-21, PTEN/AKT/eNOS, and MARK/ET-1 Pathways.

[Can urine albumin/creatinine ratio replace 24 hours urinary albumin?]

Renal impairment markers in type 2 diabetes patients with different types of hyperuricemia.