Clinicians Prof Elaine Chow, Prof Rodica Busui and Prof Ronald Ma explain at APAC ProCardio how proactive, precision monitoring could mitigate the risk of cardiovascular complications in people with diabetes.
Diabetes is one of the Asia-Pacific region’s most urgent healthcare challenges. Incidences in the Western Pacific and South-East Asia regions, defined by the International Diabetes Federation (IDF), are expected to reach 253.8 million by 20501.
Type 2 diabetes significantly increases the risk of serious cardiovascular (CV) complications, including heart failure, coronary heart disease, and cardiovascular death2. But while a cure isn’t yet in sight, early and intensive diabetes management can drastically reduce the risks of these complications3.
Advanced monitoring tools and diagnostics make this possible. Diagnostics are the cornerstone of resilient healthcare systems. They’re essential for preventing disease and determining the right therapy. And now, digital and technological advancements have ushered in a new era of decentralised diagnostics that bring personalised insights closer to home — from AI-enabled tools to blood-based biomarkers.
These innovations help us move from a reactive to a proactive approach, where predictive insights empower earlier intervention and improved self-care.
Advanced monitoring beyond HbA1c: Why averages aren’t enough
Traditional HbA1c testing offers only a long-term average of blood sugar levels. Averages can mask dangerously high day-to-day fluctuations4; two people with the exact same A1c can have completely different glucose distributions and degrees of variability. For patients living with comorbidities like advanced chronic kidney disease (CKD), HbA1c averages are even less reliable.
High glycaemic variability is linked to a higher risk of severe hypoglycaemia4, and acute glucose fluctuations generate oxidative stress that contributes to wider vascular complications4.
To see the true picture of glycaemic control, modern care is shifting toward Continuous Glucose Monitoring (CGM). A Continuous Glucose Monitor (CGM) is a wearable medical device that tracks blood sugar levels in real-time 24/7, using a tiny sensor under the skin to measure glucose in the fluid between cells. CGM delivers actionable metrics, such as Time in Range (TIR) and glycemic variability. This real-time data visibility drives improved metabolic outcomes by empowering patients to make immediate behavioural adjustments.
For clinicians, CGM is a critical tool for early intervention because it captures glycaemic variability — the peaks and lows of daily life — in real time. AI-enabled CGMs can predict glucose events before they happen; identifying these fluctuations early in the patient journey is critical for timely intervention and intensive management to prevent cardiovascular complications.
NT-proBNP is a powerful indicator for asymptomatic heart failure
People living with diabetes often develop complications which are difficult to detect early5. Heart failure, for example, is the most prevalent cardiovascular complication in diabetes, but often remains asymptomatic in its early stages. The heart of someone living with diabetes undergoes unique metabolic and structural changes, including inflammation and microvascular dysfunction, before overt symptoms present themselves.
Research highlights that NT-proBNP — a blood-based biomarker protein released by the heart when under stress or stretching due to fluid overload, primarily used to diagnose or rule out congestive heart failure — indicates cardiac wall stress and stretch. It reflects cardiac dysfunction before a patient feels unwell.
NT-proBNP is an essential screening tool, because elevated levels of this biomarker can identify asymptomatic patients at risk of developing heart failure and hospitalisation. Recent real-world data shows that NT-proBNP provides similar prognostic value in Type 1 diabetes as it does in Type 2 diabetes, showing a comparable, stepwise increase in the risk of heart failure or death as biomarker levels rise.
This biomarker has been shown to be superior to standard clinical risk scores and other markers like HbA1c or albuminuria for predicting cardiovascular events in people with diabetes. By identifying these silent signals, clinicians can start targeted therapies well before serious cardiovascular complications start to develop, potentially changing the course of the disease.
Shifting towards proactive, data-driven personalised management
Diabetes care is shifting from reactive treatment to proactive, personalised management. Moving beyond standard HbA1c, AI-enabled CGM empowers patients with real-time glucose forecasting to prevent dangerous blood sugar fluctuations.
Concurrently, precision biomarkers like NT-proBNP can detect silent heart stress before symptoms occur, allowing clinicians to stratify patient risk and initiate targeted therapies earlier. Through this dual-track approach of intensive glycemic control and early disease prevention, we can reduce the burden of CV complications for more of the population living with diabetes — and ultimately, improve diabetes health outcomes at scale.
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