New study may reduce time it takes to diagnose heart attacks

You are rushed to a hospital in Albany with chest pains and admitted to the emergency room. Your doctors say that it is too early to tell whether you are having or soon will have a heart attack, so they have you wait. During that time, it is possible that you have some kind of cardiac episode and doctors are not prepared for it. Or, you could end up waiting around only to learn that you had indigestion. This is not a hypothetical scenario, but something that happens in the Albany region every day.

A new study has been released, however, that may reduce the amount of time it takes to diagnose a cardiac episode. This could, of course, better prepare doctors for the damage or danger associated with such an event. It could also be extremely important in reducing or eliminating the tragic loss of life caused by an emergency room physician's failure to diagnose a heart attack.

A professor of medicine has commented that while the study will serve as an important tool in diagnostics, it has a little way to go before it is commonly used in the emergency room. The algorithm laid out in the study is generalized and will not apply to ever single group that comes in to the emergency room with signs of heart attack. Rather, there will need to be several different algorithms covering all the different potential patients who would need to be diagnosed.

The study traced the presence of a biochemical marker within 872 patients. The marker, known as high-sensitivity cardiac troponin assays, was charted from an initial reading to the end of the first hour. The amount of change was entered into the algorithm to determine if the patient fell into rule-out, rule-in or observational categories for cardiac events.

While this algorithm is not yet perfect, it stands to serve as an important tool in diagnosing patients in the future.

Source: Medical News Today, "Heart Attack Test Gives Diagnosis in 1 Hour," Catharine Paddock, August 16, 2012

Check out our medical malpractice page to learn more about physicians' failure to diagnose medical conditions.


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