SFI study appears to improve stroke prediction in younger people

SFI study appears to improve stroke prediction in younger people



The team said they could help identify younger people at high risk for ischemic stroke who wouldn’t be identified using traditional methods.

Researchers at the Science Foundation Ireland Adapt center claim to have created a new prediction model that can more accurately identify people under the age of 60 at high risk for ischemic stroke.

Ischemic stroke occurs when a blood clot blocks blood flow in an artery in the brain, cutting off oxygen supply to the brain tissue. It is considered one of the leading causes of death worldwide. A 2020 study published in Oxford Academic said the annual cost of stroke in the UK was around £26 billion.

The researchers at the Adapt research center for AI-driven digital content technology at TU Dublin said there are people under the age of 60 who are at risk of stroke who will not be properly identified using a traditional prediction model.

“Age is a critical risk factor in predicting stroke,” said Prof. John D. Kelleher. “Unless we are careful about using age to predict stroke risk, however, age may dominate information coming from other risk factors.

“Another aspect to consider when predicting stroke risk is that not all risk factors contribute equally to stroke risk due to age.”

In their study published in the journal Frontiers of Neurology, the team said they created a series of models that can predict individual stroke risk by age group. Their study looked at whether the contribution of stroke risk factors to 5-year stroke risk is not proportional to age.

“This research shows that by creating different risk models for different age groups, we are better able to model the contribution of multiple factors to stroke risk that is appropriate for each age group,” Kelleher added.

One of the examples cited in the study is the fact that previous studies have shown that younger women have a lower short-term risk of stroke than men, but this changes as women get older.

“Age is a key factor in stroke risk, with the likelihood of stroke increasing with age,” the researchers said in the study. “However, there are other risk factors that are important in determining stroke risk by age, and if age is considered a risk factor in a model, we showed that the model can neglect the contribution of these other factors.”

The team believes their research will help identify people at the highest risk of ischemic stroke, reduce those risks and positively impact patient care. They said their new platform could affect millions of people at high risk.

The research is part of the Horizon 2020 research project Precise4Q, which aims to create predictive simulation computer models to enable personalized stroke treatment.

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