Mobile Health Tech to Identify PAD

Lower Extremity Arterial Disease (LEAD) or commonly known as Peripheral Artery Disease (PAD) affects more than eight million Americans including up to 20% over the age of 60 and 200 million people worldwide. The goal is to detect Lower Extremity Arterial Disease (LEAD) sooner or as it is more commonly known as Peripheral Artery Disease (PAD).

The National Heart, Lung, and Blood Institute, https://www.nhlbi.gov part of NIH, recently awarded a five year $8 million grant titled “PASOS: Peripheral Artery Disease Study of SOL,” to researchers at Albert Einstein College of Medicine https://www.einstein.yu.edu and Montefiore Health System https://www.montefiorehealthsystem.org. They are going to use mobile health technology to identify early symptoms of PAD.

“One reason PAD is such a problem is that its typically not diagnosed until people go to the doctor complaining of cramping or pain while walking,” explained Robert Kaplan PhD, Professor of Epidemiology and Population Health at Einstein and Principal Investigator on the grant. “Some Hispanic groups have an elevated risk for PAD, but researchers don’t know if this is due to a genetic predisposition, behaviors, or some combination of both”.

The 16,000 participants in the Latinos/Hispanic Community Health Study (SOL/HCHS) are enrolled at four sites in the US. The study participants in the PAD study must be over 45 and schedule regular check-ups between 2020 and 2022. The researchers will first conduct PAD screening on approximately 6,000 participants in the study.

“We want to see if there are any early signals from the body that we can use to improve screening and initiate treatment earlier”, said Dr. Kaplan. Study participants will undergo standard diagnostic tests, including the ankle-brachial index test and the toe-brachial index test that compares blood pressure between the ankle and arm and between the toe and arms.

The participants will then be fitted with physical activity monitors called accelerometers. These wrist watches will measure not only the amount of activity, but also patterns of activity throughout the day over a seven day period.

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