Eyes serve as an early warning system for stroke risk

Stroke is a silent killer that racks up a death toll of roughly 6.7 million individuals each year among the estimated 100 million people who are affected worldwide.

Despite advances in healthcare, strokes often strike without warning, making it imperative to develop innovative tools that can predict and prevent this devastating condition.

Stroke prevention has often hinged on identifying notable risk factors like high cholesterol levels, poor diet, smoking, and high blood pressure.

However, new research has illuminated a potentially life-saving discovery: a person’s eyes could serve as an early warning system for stroke.

Examining eyes for stroke prevention

The retina, the light-sensitive tissue layer that lines the back of our eyes, isn’t just for sight. The study suggests that it can also be an indicator that predicts a person’s risk of developing a stroke.

This discovery highlights the retina’s value as a unique window into overall vascular health, and offers insights far beyond vision-related disorders.

The retina’s complex vascular network shares distinct anatomical and physiological similarities with the brain’s vasculature, which has led scientists to consider its credentials in assessing systemic damage from medical conditions like diabetes.

Vascular fingerprint on the retina

The experts found that a vascular “fingerprint” on the retina of the eyes could provide valuable insights into an individual’s stroke risk. This physiological fingerprint comprises 29 indicators of vascular health.

The researchers examined these indicators, considering features such as the caliber of veins and arteries – including their density, twistedness, branching angle, and complexity.

They also factored in demographic and socioeconomic backgrounds, lifestyle, and health measurements like blood pressure, cholesterol levels, and body weight.

The impressive part? These fingerprints can be obtained relatively easily, without invasive lab tests.

A technique known as fundus photography, captures images of the back of the eye and can be used to gather this information. It is particularly suited for primary healthcare and low-resource settings, and offers a practical, implementable approach.

Machine learning for stroke prediction

As much as the retinal fingerprint is a promising tool, its potential in stroke risk prediction hasn’t been exploited fully due to inconsistent uses of fundus photography or variable study outcomes.

Addressing these gaps is crucial to unlocking the full potential of retinal imaging as a reliable, non-invasive diagnostic tool.

Enter machine learning, which allowed the scientists to identify biological markers that could predict stroke risk accurately without resorting to invasive lab tests.

One of these advanced machine learning tools includes the Retina-based Microvascular Health Assessment System (RMHAS).

Changes in eye indicators and stroke risk

The researchers studied fundus images from over 68,000 participants, with the final group comprising 45,161 people (with an average age of 55).

Over 12.5 years, 749 participants had a stroke, with these individuals predominantly being older males who smoke and have diabetes, high blood pressure, or low levels of “good” cholesterol.

In total, 118 retinal vascular measurable indicators were included, with 29 significantly connected to first-time stroke risk after adjustments for traditional risk factors.

The study discovered that changes in these eye indicators correlated with increased stroke risks of between 10 – 19.5 percent.

So, does the retinal “vascular fingerprint” forecast future stroke risk accurately? According to the study, the answer is a resounding yes.

This fingerprint can predict stroke risk as efficiently as traditional risk factors alone, even when combined with just age and sex data.

Limitations of the study

It is imperative to note that this is an observational study. Therefore, it does not confirm any causal relationships.

Additionally, the research findings may not apply to diverse ethnicities as the majority of the participants were white. Moreover, the risk associated with different types of stroke could not be assessed.

Nevertheless, the potential application of this discovery, particularly in primary healthcare and low-resource settings, cannot be understated.

This breakthrough research has great potential in the fight against stroke. With further studies and exploration, we may be on the cusp of transforming the way we assess the risk of stroke around the world.

The full study was published in the journal Heart.

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