Cardiovascular Disease and Risk Management: Standards of Medical Care in Diabetes-2020

Combining Glucagon-Like Peptide 1 Receptor Agonists and Sodium-Glucose Cotransporter 2 Inhibitors to Target Multiple Organ Defects in Type 2 Diabetes

Long-term risks of macro- and microvascular complications may be reduced in people with type 2 diabetes who achieve early and sustained glycemic control. Delays in attaining A1C goals are associated with poor long-term cardiovascular (CV) outcomes. Glucagon-like peptide 1 (GLP-1) receptor agonists and sodium-glucose cotransporter 2 (SGLT2) inhibitors are glucose-lowering therapies that act through complementary mechanisms of action with regard to the pathophysiologic defects of type 2 diabetes. Trials of agents in both drug classes have demonstrated improvements in CV and renal outcomes. This review discusses the rationale for combination therapy with a GLP-1 receptor agonist and an SGLT2 inhibitor, including early initiation of this combination in newly diagnosed patients. This combination may lead to timely glycemic control and potentially additive CV and renal benefits. Clinical studies of the combination have shown partially additive effects on A1C reduction, additive effects on weight reduction, and potentially synergistic effects on blood pressure reduction. Long-term studies are needed to determine whether the combination provides an additional effect on CV and renal outcomes compared with agents from either drug class when used alone.

Prevention and management of cardiovascular disease in patients with diabetes: current challenges and opportunities

More than 100 million people in the USA have diabetes or prediabetes and are at high risk for developing cardiovascular disease. Current evidence-based guidelines support a multifactorial approach in patients with diabetes, including lifestyle intervention and pharmacological treatment of hyperglycemia, hypertension, and dyslipidemia. In addition, recent cardiovascular outcome trials demonstrated that sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide 1 receptor agonists improve cardiovascular outcomes in patients with diabetes. Albeit this evidence, over 80% of patients with diabetes do not achieve the recommended treatment goals. Considering the rising burden of cardiovascular complications, there is need to improve the quality of care in patients with diabetes. In this review, we discuss the current quality of health care in patients with diabetes in the USA, identify barriers to achieve guideline-recommended treatment goals and outline opportunities for the improvement in caring for patients with diabetes.

Abdominal aortic aneurysm: a review on the role of oral antidiabetic drugs

INTRODUCTION

A paradoxical negative association between diabetes mellitus and abdominal aortic aneurysm (AAA) prevalence and growth is established. However, so far is not possible to determine whether this protection comes from the disease itself or the medication for Diabetes. The aim of this manuscript is to review the association between oral antidiabetic drugs and AAA incidence and growth.

EVIDENCE ACQUISITION

A search was conducted on PubMed and Scopus databases until December 2019 to identify publications reporting on the association between oral antidiabetic drugs (biguanides/metformin, sulfonylureas(SU), thiazolidinediones(TZD), dipeptidyl-peptidase 4(DPP-4) inhibitors, glucagon-like peptide 1(GLP-1) agonists, sodium-glucose transporter protein-2(SGLT2) inhibitors) and the outcomes AAA incidence and growth. Only data from human studies were considered, with a minimum of 3 months follow-up.

EVIDENCE SYNTHESIS

Six studies enrolling 25,810 patients were included: one reporting on the AAA risk and five reporting on AAA growth. Metformin prescription was associated with a 28% reduction in AAA occurrence, while SU and TZD were associated with a 18% decrease in AAA risk. Regarding AAA enlargement, results were concordant for a slower expansion rate associated with metformin, with a decrease ranging from -0.30 mm/y to -1.30 mm/y, but not consistent for other antidiabetic drugs.

CONCLUSIONS

Metformin seems to be associated with a decrease in AAA risk and enlargement rate. Evidence for the other classes is lacking. Studies evaluating the association between oral antidiabetic drugs and AAA progression, independently of the diabetic status, are needed.

Statin-induced autoimmune hepatitis in patients with type 1 diabetes: A report of two cases and literature review

Statins are widely used medications for the treatment of hypercholesterolemia, as well as prevention of cardiovascular disease. We report two patients with type 1 diabetes who developed autoimmune hepatitis after the administration of statin. The first patient developed the marked elevation of liver enzymes 6 months into atorvastatin therapy. The second patient developed liver dysfunction 8 months after the initiation of rosuvastatin therapy. Liver biopsies in both patients showed either portal, interface and lobular hepatitis or a piece‐meal necrosis with lymphocytes and plasma cell infiltration that were compatible with autoimmune hepatitis. Then, both patients were started on prednisolone, to which they responded well. Liver biopsy is to be considered for type 1 diabetes patients if there is no improvement of liver dysfunction after discontinuation of statins.

Efficacy of SGLT-2 inhibitors in older adults with diabetes: Systematic review with meta-analysis of cardiovascular outcome trials

AIMS

Sodium-glucose cotransporter-2 inhibitors (gliflozins) and statins are oral drugs that may have beneficial cardiovascular effects in patients with type 2 diabetes, especially in those with known cardiovascular disease. We planned a systematic review and meta-analysis of cardiovascular outcome trials (CVOTs) that evaluated the effect of gliflozins on MACE risk in patients with T2D stratified by age and by statin use.

METHODS

The electronic search was carried out until 20 January 2020. RCTs were included if they were CVOTs performed in adults with T2D, compared add-on therapy with any gliflozin versus placebo, and had major cardiovascular events (MACE) as primary outcome. We limited the evaluation to MACE in order to minimize the statistical impact of post-hoc analyses. We used a random-effect model to calculate hazard ratio (HR) and 95% CI.

RESULTS

The hazard ratio for MACE was 0.95 (95% CI, 0.86-1.05) in people <65 years and 0.83 (95% CI, 0.71-0.96) for people ≥65 years, with no subgroup differences (P-value = 0.15), suggesting that the effect was consistent across age categories. The hazard ratio for MACE was 0.87 (95% CI, 0.81-0.94) in people taking a statin and 0.88 (95% CI, 0.77-1.01) for people not taking statin, with no subgroup differences (P-value = 0.90).

CONCLUSIONS

The results are reassuring, as they confirm that the efficacy profile of gliflozins is unchanged by age, and may further enhance the CV protection offered by statin.

Ten things to know about ten cardiovascular disease risk factors ("ASPC Top Ten - 2020")

Preventive cardiology involves understanding and managing multiple cardiovascular disease (CVD) risk factors. Given the rapid advancements in medical science, it may be challenging for the busy clinician to remain up-to-date on the multifaceted and fundamental aspects of CVD prevention, and maintain awareness of the newest applicable guidelines. The "American Society for Preventive Cardiology (ASPC) Top Ten 2020" summarizes ten essential things to know about ten important CVD risk factors, listed in tabular formats. The ten CVD risk factors include unhealthful nutrition, physical inactivity, dyslipidemia, hyperglycemia, high blood pressure, obesity, considerations of select populations (older age, race/ethnicity, and gender), thrombosis/smoking, kidney dysfunction and genetics/familial hypercholesterolemia. For the individual patient, other CVD risk factors may be relevant, beyond the CVD risk factors discussed here. However, it is the intent of the "ASPC Top Ten 2020" to provide a succinct overview of things to know about ten common CVD risk factors applicable to preventive cardiology.

Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)

PURPOSE

Commonly prescribed medications among patients with comorbid diabetes mellitus and hypertension include ARBs and ACEIs. However, these medications are associated with suboptimal adherence leading to inadequately controlled blood pressure. Unlike traditional single estimates of proportion of days covered (PDC), group-based trajectory modeling (GBTM) can graphically display the dynamic nature of adherence. The objective of this study was to evaluate adherence using GBTMs among patients prescribed ACEI/ARBs and identify predictors associated with each adherence trajectory.

PATIENTS AND METHODS

Patients with an ACEI/ARBs prescription were identified between July 2017 and December 2017 using a Medicare Advantage dataset. PDC was used to measure monthly patient adherence during the one-year follow-up period. The monthly PDC was added to a logistic group-based trajectory model to provide distinct patterns of adherence. Further, a multinomial logistic regression was conducted to determine predictors of each identified adherence trajectory. Predictors included various socio-demographic and clinical patient characteristics.

RESULTS

A total of 22,774 patients were included in the analysis and categorized into 4 distinct adherence trajectories: rapid decline (12.6%); adherent (58.5%); gaps in adherence (12.2%), and gradual decline (16.6%). Significant predictors associated with all lower adherence trajectories included 90 days refill, >2 number of other medications, ≥1 hospitalizations, and prevalent users. Significant predictors associated with the rapid decline trajectory included male sex, comorbidities, and increased CMS risk score. Further, significant predictors associated with the gaps in adherence trajectory included increasing age, and comorbidities. Lastly, significant predictors associated with the gradual decline trajectory included increasing age, no health plan subsidy, comorbidities, and increasing CMS risk score.

CONCLUSION

Identifying various patient characteristics associated with non-adherent trajectories can guide the development of tailored interventions to enhance adherence to ACEI/ARBs.