Objective: To estimate the prevalence and social, psychological and environmental-structural determinants of tobacco experimentation among adolescents in Shanghai, China. Methods: We conducted a cross-sectional study based on a two-stage cluster sample design by using the Chinese version of the Global Youth Tobacco Survey (GYTS) to investigate smoking behavior among 19,117 students from 41 junior and senior high schools in Shanghai, China. The associ ation between potential factors and tobacco experimentation were assessed using complex samples procedure logistic regression. Results: Of the 19,117 respondents, 10.5% (15.3% boys and 6.2% girls) reported the tobacco experimentation. The main social, psychological, and environmental-structural factors associated with tobacco experimentation were having close friends who smoke (AOR = 8.21; 95% CI: 6.49-10.39); one or both parents smoking (AOR 1.57; CI: 1.39-1.77); a poor school tobacco control environment (AOR 1.53; CI: 1.37-1.83); a high acceptance level of tobacco use (AOR 1.44; CI: 1.28-1.82); and a high level of media tobacco exposure (AOR 1.23; CI: 1.10-1.37). Peer smoking might contribute to smoking experimentation among girls (AOR 8.93; CI: 5.84-13.66) more so than among boys (AOR 7.79; CI: 5.97-9.94) and media tobacco exposure had no association with tobacco experimentation among female students. Conclusions: Social, psychological, and environmental factors are closely associated with tobacco experimentation among adolescents. Prevention programs aimed at reducing teen tobacco experimentation should be conducted at home and school with support by parents, peers and teachers. Our findings should prove useful for future development of intervention strategies among adolescents in Shanghai, China.

The 1245.29 Trial recently showed that empaglifozin improved both blood pressure and glucose control in African American (AA) patients with type 2 diabetes (T2D) and hypertension. Using the Diabetes Collaborative Registry, a large-scale US registry of outpatients with diabetes recruited from primary care, cardiology and endocrinology practices, we sought to understand the potential impact of these observations in routine clinical practice. Among 74 290 AA patients with T2D from 368 US clinics, 60.4% had hypertension, of whom 34.5% had systolic blood pressure ≥ 140 mm Hg (20.8% of the total AA T2D population). Only 1.7% of this eligible population had been prescribed a sodium-glucose co-transporter two inhibitor. The mean estimated 5-year risk of cardiovascular death was 7.7%, which could be reduced to 6.2% when modelling the antihypertensive effect of empagliflozin across the eligible population (based on an 8-mm Hg blood pressure reduction). These findings may represent a potential opportunity for better management of cardiovascular risk factors and improved outcomes in this vulnerable cohort.

Background: Although practice guidelines stress individualization of glucose management in patients with type 2 diabetes (T2D), the extent to which providers take patient factors into account when selecting medications is not well known. Methods: Diabetes Collaborative Registry (DCR) is an outpatient diabetes registry including primary care, cardiology, and endocrinology practices. T2D medications were grouped as those which may be suboptimal for key patient subgroups, and we examined patient factors associated with use of these agents using hierarchical, multivariable Poisson models. Results: In DCR, 157,551 patients from 374 US practices were prescribed a glucose-lowering medication. Patients with morbid obesity were more likely treated with medications prone to cause weight gain (relative rate [RR] 1.09, 95% CI 1.07–1.11). Older patients were more likely to be treated with medications with increased risk of hypoglycemia (RR 1.04 per 5 years, 95% CI 1.04–1.05). Patients with CKD 4/5 were less likely to be treated with agents with known risk in patients with advanced CKD (RR 0.74, 95% CI 0.71–0.77). Patients with coronary artery disease were no more or less likely to be treated with medications with potential cardiovascular safety issues (RR 0.99, 95% CI 0.96–1.01). Conclusions: We observed some targeted use of glucose-lowering therapies in certain subgroups but also identified potential opportunities for better personalization of treatment. Data sources such as the DCR can highlight potential areas for improving targeted approaches to pharmacologic therapy in order to optimize selection of patients most likely to benefit (and least likely to be harmed) from treatments.

Evidence for the role of inflammation in the pathogenesis of atherosclerosis is compelling and has generated interest in high-sensitivity C-reactive protein (hs-CRP) as a marker of cardiovascular risk. Data regarding hs-CRP and cardiovascular risk, though largely consistent, is of unclear clinical relevance. Most recently, the Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) trial has led to further debate regarding the utility of hs-CRP. This article provides a comprehensive review of the data regarding cardiovascular risk and hs-CRP with an emphasis on the JUPITER trial and concludes with an evidence-based analysis of the current role of hs-CRP in cardiovascular risk assessment.

BACKGROUND: Although guidelines and performance measures exist for patients with diabetes mellitus, achievement of these metrics is not well known. The Diabetes Collaborative Registry(®) (DCR) was formed to understand the quality of diabetes mellitus care across the primary and specialty care continuum in the United States. METHODS AND RESULTS: We assessed the frequency of achievement of 7 diabetes mellitus-related quality metrics and variability across the Diabetes Collaborative Registry(®) sites. Among 574 972 patients with diabetes mellitus from 259 US practices, median (interquartile range) achievement of the quality metrics across the practices was the following: (1) glycemic control: 19% (5-47); (2) blood pressure control: 80% (67-88); (3) angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers in patients with coronary artery disease: 62% (51-69); (4) nephropathy screening: 62% (53-71); (5) eye examination: 0.7% (0.0-79); (6) foot examination: 0.0% (0.0-2.3); and (7) tobacco screening/cessation counseling: 86% (80-94). In hierarchical, modified Poisson regression models, there was substantial variability in meeting these metrics across sites, particularly with documentation of glycemic control and eye and foot examinations. There was also notable variation across specialties, with endocrinology practices performing better on glycemic control and diabetes mellitus foot examinations and cardiology practices succeeding more in blood pressure control and use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers. CONCLUSIONS: The Diabetes Collaborative Registry(®) was established to document and improve the quality of outpatient diabetes mellitus care. While target achievement of some metrics of cardiovascular risk modification was high, achievement of others was suboptimal and highly variable. This may be attributable to fragmentation of care, lack of ownership among various specialists concerning certain domains of care, incomplete documentation, true gaps in care, or a combination of these factors.

China is one of the fastest developing countries in the world. Rapid economic progress has resulted in changes to both diet and physical activity. New found prosperity, increased urban migration, and the adoption of sedentary lifestyles by an aging Chinese population have resulted in a dramatic shift in disease burden—from infectious to chronic. Modern Chinese find themselves increasingly afflicted with the same noncommunicable chronic diseases typical of industrialized nations. Today, cardiovascular disease is the number one cause of both morbidity and mortality, affecting both rural and urban Chinese. The rising incidence of cardiovascular disease has been fueled by an epidemic of cardiometabolic risk factors. While hypertension and smoking have received considerable spotlight, little attention has been given to obesity, diabetes, and metabolic syndrome. Their increasing prevalence is the focus of this paper.

Background: Supplemental melatonin may ameliorate metabolic syndrome (MetS) components, but data from placebo-controlled trials are lacking. Methods: We conducted a double-blind, placebo-controlled, crossover, Phase II randomized pilot clinical trial to estimate the effects of melatonin supplementation on MetS components and the overall prevalence of MetS. We randomized 39 subjects with MetS to receive 8.0 mg oral melatonin or matching placebo nightly for 10 weeks. After a 6-week washout, subjects received the other treatment for 10 more weeks. We measured waist circumference, triglycerides, HDL cholesterol, fasting glucose, and blood pressure (BP) in each subject at the beginning and end of both 10-week treatment periods. The primary outcome was the mean 10-week change in each MetS component, and a secondary outcome was the proportion of subjects free from MetS, after melatonin versus placebo. Results: The mean 10-week change for most MetS components favored melatonin over placebo (except fasting glucose): waist circumference -0.9 vs. +1.0 cm (p = 0.15); triglycerides -66.3 vs.-4.2 mg/dL (p = 0.17); HDL cholesterol -0.2 vs.-1.1 mg/dL (p = 0.59); fasting glucose +0.3 vs.-3.1 mg/dL (p = 0.29); systolic BP -2.7 vs. +4.7 mmHg (p = 0.013); and diastolic BP -1.1 vs. +1.1 mmHg (p = 0.24). Freedom from MetS tended to be more common following melatonin versus placebo treatment (after the first 10 weeks, 35.3% vs. 15.0%, p = 0.25; after the second 10 weeks, 45.0% vs. 23.5%, p = 0.30). Melatonin was well-Tolerated. Conclusions: Melatonin supplementation modestly improved most individual MetS components compared with placebo, and tended to increase the proportion of subjects free from MetS after treatment.

Insulin therapy was first proposed as an adjunctive therapy in patients with acute coronary syndromes (ACS) in the 1960s. Since then, numerous randomised clinical trials have been conducted to determine the efficacy and to define the role of insulin therapy in ACS. This review will discuss: 1) completed trials of insulin therapy in ACS, including both glucose-insulin-potassium (GIK) approaches and non-GIK approaches; 2) trials of insulin therapy in critically ill non-ACS patients and the lessons from these trials that can be applied to trials of insulin in ACS patients; and 3) a summary of ongoing and planned trials of insulin in ACS patients.

Background-—Physician shortages and reimbursement changes have led to greater use of advanced practice providers (APPs). Prevalence of and outcomes associated with APP care following myocardial infarction are unknown. Methods and Results-—We examined outpatient cardiology or primary care visits within 90 days post-myocardial infarction among 29 477 Medicare-insured patients aged ≥65 years from 364 hospitals in Acute Coronary Treatment Intervention Outcomes Network Registry. We compared medication adherence, all-cause readmission risk, mortality, and major adverse cardiovascular events between patients seen by APPs versus physicians only. Overall, 11% of myocardial infarction patients were treated by an APP. Patients seen by APPs were more likely to have diabetes mellitus (37% versus 33%) and heart failure (20% versus 16%), be discharged to a nursing facility (21% versus 13%) and had more outpatient visits within 90 days post-discharge (median 6 versus 5, P<0.01 for all) than those seen by physicians only. Adherence to evidence-based medications (adjusted odds ratio, 0.98; 95% confidence interval, 0.89-1.08) and readmission risks (adjusted hazard ratio, 1.11; 95% confidence interval, 0.99-1.26) were similar between patients seen by APPs versus physicians only. Risks of 90-day mortality (adjusted hazard ratio, 1.18; 95% confidence interval, 0.98-1.42) and major adverse cardiovascular events (adjusted hazard ratio, 1.06; 95% confidence interval, 0.90-1.23) were also similar between patients seen by APPs versus physicians only. Conclusions-—APPs were likely used to provide more frequent monitoring of high-risk post-MI patients. Medication adherence, readmission risk, mortality, and major adverse cardiovascular events did not differ substantially between patients seen by physician-APP teams than those seen by physicians only.

IMPORTANCE The US Centers for Medicare and Medicaid Services Hospital Readmissions Reduction Program penalizes hospitals with higher-than-expected risk-adjusted 30-day readmission rates (excess readmission ratio [ERR] > 1) after acutemyocardial infarction (MI). However, the association of ERR with MI care processes and outcomes are notwell established. OBJECTIVE To evaluate the association between ERR forMI with in-hospital process of care measures and 1-year clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS Observational analysis of hospitalized patients with MI from National Cardiovascular Data Registry/Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With the Guidelines centers subject to the first cycle of the Hospital Readmissions Reduction Program between July 1, 2008, and June 30, 2011. EXPOSURES The ERR forMI (MI-ERR) in 2011. MAIN OUTCOMES AND MEASURES Adherence to process of care measures during index hospitalization in the overall study population and risk of the composite outcome of mortality or all-cause readmission within 1 year of discharge and its individual components among participants with available Centers for Medicare and Medicaid Services-linked data. RESULTS The median ages of patients in the MI-ERR greater than 1 and tertiles 1, 2, and 3 of the MI-ERR greater than 1 groupswere 64, 63, 64, and 63 years, respectively. Among 380 hospitals that treated a total of 176 644 patients with MI during the study period, 43%had MI-ERR greater than 1. The proportions of patients of black race, those with heart failure signs at admission, and bleeding complications increased with higher MI-ERR. Therewas no significant association between adherence to MI performance measures and MI-ERR (adjusted odds ratio, 0.94; 95%CI, 0.81-1.08, per 0.1-unit increase in MI-ERR for overall defect-free care). Among the 51 453 patients with 1-year outcomes data available, higher MI-ERRwas associated with higher adjusted risk of the composite outcome and all-cause readmission within 1 year of discharge. This associationwas largely driven by readmissions early after discharge andwas not significant in landmark analyses beginning 30 days after discharge. The MI-ERRwas not associated with risk for mortality within 1 year of discharge in the overall and 30-day landmark analyses. CONCLUSIONS AND RELEVANCE During the first cycle of the Hospital Readmissions Reduction Program, participating hospitals' risk-adjusted 30-day readmission rates followingMI were not associated with in-hospital quality ofMI care or clinical outcomes occurring after the first 30 days after discharge.