Heart disease is defined on the Mayo Clinic's Website as
"a range of conditions that affect your heart. Diseases under the heart disease umbrella include blood vessel diseases, such as coronary artery disease; heart rhythm problems (arrhythmias); and heart defects you're born with (congenital heart defects), among others."
In the U.s. heart disease is a leading killer, more deadly than all of the different cancers combined. In the U.S. someone suffers a heart attack every 34 seconds, 24 hours a day, 365 days a year.
Much of what we know is fairly recent. It is only in the past thirty years that physicians have been aware that blood pressure, cholesterol, and obesity are risk factors for heart disease. There remains much we do not know about identifying, treating, and preventing heart disease.
How have we learned what we do know, for example, about the relationship between blood pressure and heart health?
To understand, we need to go back into the early part of the 18th century. Recall that Newton had demonstrated in his 1687 book Principia Mathematica that nature's language was mathematics. With three simple mathematical equations it is possible to predict and explain the motion of any object in the universe from shooting stars to apples. (Harari, 2014, p. 287)
But Newton's equations are not sufficient to deal with phenomena like biology and economics which require additional forms of mathematics because of their complexity. The new branch of mathematics that can handle complex behavior is statistics.
In 1713 a Swiss mathematician proved a theorem which he called the Golden Theorem but which others have called the Law of Large Numbers (LLN). The Law of Large Numbers addresses the problem of prediction. While it is very difficult to reliably predict a single event, it is possible to predict an event if you perform multiple experiments or observations over time. If births and deaths are recorded carefully over many years, it will be possible to predict with a great deal of accuracy the life expectancy of a baby or how much longer a twenty year old born in a particular year is likely to live.
In medical science the principal of LLN is the basis for epidemiological studies. The large number of cases allows researchers to identify patterns that show risk factors for disease.
One of the landmark research epidemiological studies of heart disease is the Framingham Study. It was begun in 1948 when it enlisted 5,209 residents of Framingham, Massachusetts, aged from 28 to 62 (unusually for the time, half of the subjects were women). One of the many measures used to follow the participants over the years of the study was blood pressure.
It was medical practice at the time to view elevated systolic blood pressure as a non-issue. But in the first published study using Framingham data in 1957, the researchers noted that blood pressure greater than or equal to 160/95 was associated with a 4 fold increase in coronary heart disease per 1000 persons. In a later study, the research identified that stroke was also a major consequence of high blood pressure.
Despite the evidence, it took several decades for the medical community to accept the "validity of the epidemiological approach..." (Mahmoud, 2010)
The epidemiological approach to medical research is now well-established based on "the wealth of novel scientific data that [the Framingham Heart Study] generated over 5 decades and which has made a significant contribution to cardiovascular disease prevention in the United States and indirectly influenced global coronary vascular disease prevention strategies." (Mendis, 2010)
The epidemiological approach to medical research requires what is now termed Big Data. Following as large a population as possible makes the findings valuable as the Law of Large Numbers demonstrates.
It took the Framingham Heart Study four years to gather its initial cohort of 5,209 participants. But in the 21st century the technology that connects individuals to the internet has the potential to revolutionize the conduct of epidemiological research.
Health eHeart "an ambitious study to end heart disease" is a project of the medical school at the University of California-San Francisco, one of the top medical schools in the U.S. The Health eHeart study is recruiting online for anyone over 18 who has access to the internet which means just about everyone! Data will be gathered through online surveys, participants will collect their own data ("your own scale, blood pressure machine"), and you will pass the data up through a secure system, privacy guaranteed. Social media, and new technologies will be employed such as apps that will track heart rate on your smart watch or Fitbit.
Modern connected technology will allow the researchers to engage more people and thus "gather more data about heart health than any research study has done before." Following the Law of Large Numbers, epidemiological data will be used to "develop strategies to prevent and treat all aspects of heart disease."
About 1 out of every 4 people will have an irregular heartbeat, an arrhythmia. The most common arrhythmia is atrial fibrillation. The heart muscle fibers that squeeze blood from the atria lose their coordination, beat wildly, disrupting the normal operation of the heart.
Among the dangers of atrial fibrillation is stroke. The scary part of this is that we might not know we have had an arrhythmia, and had we known, there are treatments that could prevent a stroke.
mRhythm is one of the studies in the Health eHeart project; its goal is to develop technologies to detect atrial fibrillation. The researchers developed an app called Cardiogram capable of heart monitoring continuously using technology you can buy at your local Target. Cardiogram uses deep machine learning in an algorithm that can translate raw data coming from your smart watch into a diagnosis. In a study of 6,158 Cardiogram users, the algorithm was able to detect atrial fibrillation "with higher accuracy than previously validated methods."
To find out more about Heart eHealth.
To find out more about Cardiogram.
Harari, Yuval Noah (2014). Sapiens: A Brief History of Humankind. Vintage: London.
Mahmoud S. et. al. (2010). The Framingham Heart Study and the Epidemiology of Cardiovascular Diseases: A Historical Perspective, retrieved from (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4159698/)
Mendis, S. (2010). The contribution of the Framingham Heart Study to the prevention of cardiovascular disease: a global perspective. Progress in Cardiovascular Disease 53(1) 10-4. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/20620420
Olgin, Jeffrey S. (2017) Health eHeart. Retrieved from https://www.health-eheartstudy.org/
Dr. John Holton
Dr. John Holton joined the S²TEM Centers SC in July of 2013, as a research associate with an emphasis on the STEM literature including state and local STEM plans from around the nation.