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Nanotechnology Could Help Predict Outcomes After Heart Failure




Because heart failure occurs most frequently in the elderly, researchers have attempted to develop models to further predict the risk of adverse cardiac events in this age group. While risk-prediction models have historically produced unreliable results, a new study from the Veteran Affairs San Diego Medical Center in California shows promise.

The study followed 144 acute heart failure patients from hospital admission to 90 days after discharge, unless patients experienced death or heart failure-related readmission prior to 90 days. Researchers measured participants’ pro-B-type natriuretic peptide (BNP) and troponin levels upon hospital admission, discharge and up to four days during hospitalization. Although troponin measurements were used in earlier studies, relevant changes were too miniscule for standard assays to detect. In this study, a more highly sensitive assay with nanotechnology allowed researchers to quantify troponin measurements in 99% of participants’ serum samples.

The study indicated a statistically significant, positive correlation between troponin levels during hospitalization and mortality and readmission, but no significant associations with BNP were noted.

Based on these findings, troponin measurements might help physicians identify heart failure patients at high risk for adverse outcomes.


MD News February 2011


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