Feb 19, 2019 Cedars-Sinai Staff
A simple plastic tool helps patients collect tiny drops of blood for precise biometric monitoring and heart health.
Heart attacks strike suddenly. Early warning signs are elusive, and symptoms often arise only after the damage is done. To predict and maybe prevent harmful cardiac events, patients would have to provide blood samples and other health data frequently. “I used to sit and worry about how to monitor patients’ health, especially at-risk individuals who can’t come to the lab for a blood draw every week,” says Jennifer Van Eyk, PhD, director of Basic Science Research in the Barbra Streisand Women’s Heart Center at the Smidt Heart Institute.
A plastic container protecting two or four small sticks with rigid, absorbent tips provides a valuable assist to physicians who are seeking signs of imminent heart attack. The Mitra Microsampler is an at-home blood-draw tool that instructs patients to prick a finger, use the Q-tip-like stick to absorb up 10 microliters of blood—a volume 1/100 the size of a drop of water—and secure it in a tiny clamshell container to mail to the lab. There, an automated system can detect any of 563 precise diagnostic biomarkers in the dried blood samples. Clinicians can ultimately analyze the data to determine disease risk and select the right interventions for each individual.
In an ongoing trial, Cedars-Sinai investigators are using the Microsampler to scan for 10 biomarkers in a group of mid-risk cardiovascular patients—about 20 percent of whom are likely to have a heart attack—to better understand hormonal indicators of the event.
Participants provide the blood collected at home along with Fitbit data, EKG measurements, and self-reported symptoms. Investigators integrate the information every month for insights into each patient’s health.
“Never before could we track the natural progression of disease in this way,” says Van Eyk, one of the project’s lead investigators and the Erika J. Glazer Chair in Women’s Heart Health.
Van Eyk and her collaborators aim to use the data to design a system that can predict and prevent heart attacks.