Researchers use big data to learn more about stroke risk

August 14, 2015 − by Suzanne Elvidge − in Big data, Big data in research, Data analytics, Data mining − No Comments

Atrial fibrillation (AF), a disorganised beating of the heart, increases the chance of blood clots and stroke, but it is not entirely clear when the patient is at most risk. US researchers, including the Stanford University School of Medicine, have used continuously-recorded medical information from patients with cardiac implantable electronic devices (CIEDs), such as pacemakers and defibrillators, to get a better understanding of timescales.

The team looked at a decade of data from the Veterans Administration Health Care System, covering 9850 patients with remotely monitored CIEDs, and linked it to medical records.

“This is truly a big data approach where we took raw data from implanted pacemakers and implanted defibrillators and linked it to clinical data,” says Mintu Turakhia of Stanford University.

Using case-crossover analysis of ischemic strokes, they compared the patient’s occurrences of atrial fibrillation in 30 days before stroke and 91-120 days pre-stroke (as a control). The aim was to see whether the patient’s stroke risk changes with attacks of atrial fibrillation.

“The medical device data comes from home remote monitoring systems that patients have and goes to the cloud. We pulled the raw data off the cloud and linked it to VA (Veterans Affairs) electronic health records, VA claims, Medicare claims, and death records,” says Turakhia.

The results, published in Circulation: Arrhythmia and Electrophysiology, found that patients were at an increased risk of stroke the first seven days after their hearts went into atrial fibrillation.

“This is truly a novel approach where we are assembling highly disparate data sources and linking them to gain insight into disease,” says Turakhia.

Guidelines recommend that patients with either sudden or continuous atrial fibrillation are treated with anti-coagulants long-term, but these results suggest that short-term treatment could be an option. Further studies are needed.

“Future treatment plans might explore the idea of some kind of wearable device that shows when a patient goes in and out of atrial fibrillation, then taking medications just when needed rather than for a lifetime,” says Turakhia.

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