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Test may predict coronary survival

An easy examination of blood looks for levels of hormone that rise when the heart is damaged. The lower the level, the more likely a patient will live.

November 18, 2002|Jane E. Allen | Times Staff Writer

A simple blood test may be able to predict the likelihood that a patient will survive after being admitted to a hospital with a heart attack.

The quick and inexpensive test detects levels of a hormone, B-type natriuretic peptide (BNP), that rises when the heart is damaged. Doctors had been using measurements of the hormone to diagnose heart failure and to determine the extent of damage after heart attacks or severe chest pain, which can be an indication of major blockages in the arteries.

But a team of Swedish researchers looked at how well the test could predict both initial survival and how the patients would do in the long run.

The scientists focused on part of the hormone, called the N-terminal fragment, or N-BNP.

They studied 609 patients admitted to the coronary care unit of Sahlgrenska University Hospital in Goteborg, Sweden, from 1995 to 2000 and tested for the hormone fragment.

The patients were followed for several years. Researchers found levels of the hormone were significantly lower in patients who survived than in those who died, according to findings published in last week's online issue of Circulation: Journal of the American Heart Assn.

Both BNP and N-BNP more strongly predict short-term and long-term survival than current tests, such as those for cardiac muscle proteins called troponins that rise within hours of heart damage, the authors said.

However, while agreeing that levels of BNP and N-BNP appear to be better predictors of long-term risk, Dr. James A. Lemos of the University of Texas Southwestern Medical School in Dallas and Dr. David A. Morrow of Brigham and Women's Hospital in Boston wrote an editorial in the same journal calling for additional research into using the test in patients admitted with a heart attack or chest pain, and in determining the optimal time to perform the test.

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