Cardiometabolic

Cardiometabolic spectrum

Cardiometabolic disorders are a spectrum of conditions including:

  • Type 2 diabetes and Non-Diabetic Hyperglycaemia, which is an intermediate diagnostic category between normal glucose metabolism and diabetes, sometimes referred to as ‘pre-diabetes’
  • Atherothrombotic cardiovascular disease, which manifests clinically as myocardial infarction, heart failure, stroke, and peripheral arterial disease
  • Raised blood pressure
  • Non-alcoholic fatty liver disease
  • Obesity

Overview

These highly prevalent conditions, which arise from interactions between susceptibility genes and behavioural factors (nutritional status and habitual levels of physical activity), are closely related in terms of their shared risk factors. Known collectively as the metabolic (or insulin resistance) syndrome these risk factors include excess fat storage (especially in metabolically disadvantageous ectopic sites including liver, pancreas and muscle), dyslipidaemias, dysregulated glucose metabolism, and hypertension. Other factors including chronic low-grade inflammation, and less well quantified environmental modifiers of risk such as air pollution, contribute to the development and progression of cardiometabolic disorders. Perhaps less widely appreciated is the contribution of these risk factors to the development of cognitive impairment, frailty and a propensity for numerous forms of cancer, making this an incredibly complex set of conditions.
A complex and multifaceted network of risk factors that interact in variable combinations, which differ from patient to patient.

Diagnosis and Therapy

Body weight, hypertension, dyslipidaemias and glucose intolerance are all eminently modifiable risk factors that lead to development of disease, yet are often sub-optimally managed. Thus, therapeutic targets for blood glucose, cholesterol and blood pressure which are typically targeted with pharmaceutical intervention, are frequently not achieved or sustained, even with the use of adjunctive pharmacotherapy in addition to lifestyle modifications.
Adverse lifestyles – especially overnutrition and sedentary behaviour – are now the primary contributor to non-communicable diseases (NCD) which account for the majority of global healthcare budgets. Attainment of optimal cardiometabolic health – including so-called primordial prevention to avert the development of subclinical risk factors – could avoid or defer much of the morbidity and premature mortality associated with these disorders, pointing to a need for a more effective earlier diagnosis.


Adherence and clinical inertia are barriers to best clinical care! Suboptimal adherence by patients to non-pharmacological and pharmacological interventions is common in clinical practice. This problem, which may be compounded by therapeutic inertia by clinicians, creates a substantial ‘translational medicine gap’. This term denotes the shortfall between an evidence base (data from randomized controlled trials that inform recommendations for best practice) and real-world clinical outcomes. On the non-pharmacological front, a chasm exists between knowledge of healthy lifestyles and the long-term implementation of appropriate preventive behaviour by high-risk individuals. And so, changes may need to be gradually introduced and reinforced using innovative approaches, e.g. through the use of wearable technology, in order to be sustainable. When considering novel pharmacotherapeutics, the arrival of new classes of safe and effective cardiometabolic drugs in recent years has usefully expanded treatment options for many patients. However, translation of clinical trial data into daily clinical practice in pursuit of the practice of precision medicine remains problematic.

Precision Medicine

Developments in precision medicine can be applied in clinical practice for cardiometabolic disorders. Glucose-lowering drugs to reduce cardiovascular events – New opportunities for reducing the toll from atherosclerotic cardiovascular events and heart failure have recently become available that have changed the therapeutic landscape for type 2 diabetes. While optimal positioning of sodium–glucose cotransporter (SGLT)-2 inhibitors and glucagon-like peptide (GLP)-1 receptor agonists requires additional clarification clinical practice guidelines have been revised to reflect the evidence for cardioprotection provided by these drugs. However, the resulting treatment algorithms attest to the complexity of the process of stratifying patients with type 2 diabetes according to characteristics such as presence/absence of cardiovascular disease, heart failure, and/or chronic kidney disease. These challenges are compounded by the inherent heterogeneity of type 2 diabetes, notably with respect to the interplay between reduced insulin action in multiple organs and impaired insulin secretion. The avoidance of iatrogenic disease, especially drug-induced hypoglycaemia, adds to the convolutions of the exercise for busy clinicians. In the context of multiple risk factor management, clinicians must also be aware of the potential for certain cardioprotective medications to induce or aggravate adverse metabolic profiles, e.g. statin therapy is associated with an increased risk of new-onset diabetes in susceptible patients. Opportunities now exist to improve the delivery of the most appropriate medications to patients that is safe, effective and timely.
Strategies for managing statin intolerance – A sizeable minority of individuals who might benefit from medications aimed at reducing the risk of cardiometabolic disease are unable to tolerate well-studied, safe and effective drugs. This problem is perhaps most apparent with statins. Improved engagement with healthy diets, including the use of therapeutic food products, could help reduce the need for pharmacotherapy. In the future, application of genetic profiling of individual patients may (a) improve the accuracy of calculating cardiovascular events and (b) help to stratify patients in terms of susceptibility to statin-associated adverse effects. These strategies could help target appropriate alternative cholesterol-reducing therapies to individuals at highest risk while ensuring cost-effectiveness.

Example: Hypertension

Diagnostic. Diagnostic Tree

Treatment. Treatment Tree