Troponin Blood Test Cleared for Heart Attacks Detection by FDA


The high-sensitivity test may prove to be significantly beneficial for at-risk females, who generally have lower troponin levels than men.


The US Food and Drug Administration (FDA) has granted clearance to a new diagnostic test for identifying heart attacks.

The ARCHITECT STAT High Sensitivity Troponin-I blood test from Abbott has been cleared for the detection of heart attacks—in a fashion which has been evidenced to be faster and more accurately than contemporary troponin tests.

The new test was the first of its kind in non-US markets to offer gender-specific cut-offs, which allowed physicians to more accurately diagnose heart attacks in women. This was evidenced in a recent trial showing the ARCHITECT STAT test discovered twice as many heart attacks in women than standard troponin tests. Women may benefit from the test as they generally have lowered troponin levels compared to men.

Another trial assessing the test showed it benefit in ruling out heart attack more quickly for two-thirds of defined at-risk patients, allowing for faster and more efficient hospital discharges. Thus far, the test has been used throughout hospitals and facilities internationally, and has been included in at least 200 clinical trials assessing its benefit for heart disease and cardiac event identification.

The clearance marks what Agim Beshiri, MD, senior medical director of Abbott Diagnostics global medical and scientific affairs, called an important milestone for physicians.

“As one of the most widely researched high sensitivity troponin tests, this technology could help address several challenges in emergency departments today, including overcrowding and more accurately identifying heart attacks in women,” Beshiri said in a statement.

The blood test is now approved for sale in the US, in use with Abbott’s fully-automated ARCHITEST analyzer. The company advised test results be used in conjunction with other diagnostic information including electrocardiogram (ECG), clinical observations, and information relative to patient information and symptoms.

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