skip to primary navigationskip to content

Walking speed may predict future heart attacks and strokes

last modified May 22, 2019 08:24 AM

An interdisciplinary team led by Prof Mihaela van der Schaar (DAMTP) has discovered that a person's self-reported walking speed predicts cardiovascular events over the next five years.

The study used a novel machine learning method called AutoPrognosis to analyse data from the UK Biobank cohort of over 420,000 volunteers.

Of the 4,801 cardiovascular events recorded over 5 years, AutoPrognosis was able to correctly predict 368 more events compared to the standard Framingham risk score, recommended in US guidelines.

Machine learning also identified new important predictors not usually considered in existing risk prediction models, such as an individuals' usual walking pace and their self-reported overall health rating.

Furthermore, the model improved risk prediction in potentially relevant sub-populations, such as in those with diabetes, where the prediction of future heart attacks and strokes often fails.

Work is ongoing to incorporate genetic, proteomic and blood biomarkers into the machine learning model.

The study was published in PLoS One.

Cambridge Cardiovascular logo - transparent

Logo design by Dr Ana-Mishel Spiroski and Dr Sarah Morgan.


We connect cardiovascular researchers in Cambridge.

Please follow us on Twitter for local news about research, events, funding calls, and open positions.

For inquiries about our research or the website, please contact Dr Tammy Dougan