Researchers in India have carried out a data mining exercise to determine which are the most important risk factors in increasing the chances of an individual suffering a heart attack. Writing in the International Journal of Biomedical Engineering and Technology, they confirm that the usual suspects high blood cholesterol, intake of alcohol and passive smoking play the most crucial role in "severe", "moderate" and "mild" cardiac risks, respectively.
Subhagata Chattopadhyay of the Camellia Institute of Engineering in Kolkata adds that being male aged between 48 and 60 years are exposed to severe and moderate risk by virtue of their age and gender respectively, whereas women over 50 years old are effected by mild risk in the absence of the other factors.
Medical prognosis is a highly subjective art as is determining risk for particular health events, such as heart attack. After all, clinical history, symptoms and signs rarely follow a linear path and their interpretation at the individual level by doctor does not usually conform to the rules of epidemiology - personal intuition, emotions, logic and experience all conspire to confound the conclusion drawn for each patient at a given time under a particular set of circumstances.
The use of computational data mining techniques that allow researchers to extract interesting and meaningful information from real-life clinical data could remove at least some aspect of the subjectivity of clinical prognosis and allow the epidemiology to work at the patient level more precisely. There have been data mining approaches tried before. However, they often have inherent problems in that the classification of the data for information retrieval is based on decision making learnt from examples set by doctors and so they incorporate the very subjectivity that Chattopadhyay hopes to avoid with his approach.
He has used 300 real-world sample patient cases with various levels of cardiac risk - mild, moderate and severe and mined the data based on twelve known predisposing factors: age, gender, alcohol abuse, cholesterol level, smoking (active and passive), physical inactivity, obesity, diabetes, family history, and prior cardiac event. He then built a risk model that revealed specific risk factors associated with heart attack risk.
"The essence of this work essentially lies in the introduction of clustering techniques instead of purely statistical modeling, where the latter has its own limitations in 'data-model fitting' compared to the former that is more flexible," Chattopadhyay explains. "The reliability of the data used, should be checked, and this has been done in this work to increase its authenticity. I reviewed several papers on epidemiological research, where I'm yet to see these methodologies, used."
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More information: "Mining the risk of heart attack: a comprehensive study" in Int. J. Biomedical Engineering and Technology, 2013, 11, 394-410
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Researchers in India have carried out a data mining exercise to determine which are the most important risk factors in increasing the chances of an individual suffering a heart attack. Writing in the International Journal of Biomedical Engineering and Technology, they confirm that the usual suspects high blood cholesterol, intake of alcohol and passive smoking play the most crucial role in "severe", "moderate" and "mild" cardiac risks, respectively.
Subhagata Chattopadhyay of the Camellia Institute of Engineering in Kolkata adds that being male aged between 48 and 60 years are exposed to severe and moderate risk by virtue of their age and gender respectively, whereas women over 50 years old are effected by mild risk in the absence of the other factors.
Medical prognosis is a highly subjective art as is determining risk for particular health events, such as heart attack. After all, clinical history, symptoms and signs rarely follow a linear path and their interpretation at the individual level by doctor does not usually conform to the rules of epidemiology - personal intuition, emotions, logic and experience all conspire to confound the conclusion drawn for each patient at a given time under a particular set of circumstances.
The use of computational data mining techniques that allow researchers to extract interesting and meaningful information from real-life clinical data could remove at least some aspect of the subjectivity of clinical prognosis and allow the epidemiology to work at the patient level more precisely. There have been data mining approaches tried before. However, they often have inherent problems in that the classification of the data for information retrieval is based on decision making learnt from examples set by doctors and so they incorporate the very subjectivity that Chattopadhyay hopes to avoid with his approach.
He has used 300 real-world sample patient cases with various levels of cardiac risk - mild, moderate and severe and mined the data based on twelve known predisposing factors: age, gender, alcohol abuse, cholesterol level, smoking (active and passive), physical inactivity, obesity, diabetes, family history, and prior cardiac event. He then built a risk model that revealed specific risk factors associated with heart attack risk.
"The essence of this work essentially lies in the introduction of clustering techniques instead of purely statistical modeling, where the latter has its own limitations in 'data-model fitting' compared to the former that is more flexible," Chattopadhyay explains. "The reliability of the data used, should be checked, and this has been done in this work to increase its authenticity. I reviewed several papers on epidemiological research, where I'm yet to see these methodologies, used."
Explore further: Your eyes may hold clues to stroke risk
More information: "Mining the risk of heart attack: a comprehensive study" in Int. J. Biomedical Engineering and Technology, 2013, 11, 394-410
Medical Xpress on facebook
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Your eyes may hold clues to stroke risk
Aug 12, 2013
Your eyes may be a window to your stroke risk. In a study reported in the American Heart Association journal Hypertension, researchers said retinal imaging may someday help assess if you're more likely to develop a stroke ...
CT angiography helps predict heart attack risk
Feb 19, 2013
Coronary computed tomography angiography (CCTA) is an effective tool for determining the risk of heart attacks and other adverse cardiac events in patients with suspected coronary artery disease but no treatable risk factors, ...
Study of cardiologists reveals less than ideal CV risk profiles
Aug 07, 2013
(HealthDay)—Italian cardiologists often do not have ideal or even favorable cardiovascular risk profiles themselves, according to a study published in the July 15 issue of The American Journal of Cardiology.
High cholesterol riskier for middle-aged men than women
Aug 16, 2013
High cholesterol levels are much more risky for middle-aged men than middle-aged women when it comes to having a first heart attack, a new study of more than 40,000 Norwegian men and women has shown.
Smoking cessation in old age: Less heart attacks and strokes within five years
Feb 20, 2013
Smokers increase their risk of myocardial infarction (heart attack) and stroke with every cigarette they smoke. Conversely, those who quit smoking even at an advanced age will have a considerable decrease in their risk after ...
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'Virtual heart' precision-guides defibrillator placement in children with heart disease
5 minutes ago
The small size and abnormal anatomy of children born with heart defects often force doctors to place lifesaving defibrillators entirely outside the heart, rather than partly inside—a less-than-ideal solution to dangerous ...
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Use of the "clot-busting" drug tissue plasminogen activator (tPA) to treat patients with strokes caused by a blockage of blood flow nearly doubled between 2003 and 2011. In their paper receiving online release in the journal ...
Study aims to help patients with peripheral artery disease become more active
Aug 20, 2013
For millions of Americans, simply walking to the mailbox can cause unbearable leg pain as muscles scream for more blood and oxygen.
Heart MRI test can identify patients at high risk of heart attack, death
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