Translational medicine involves converting a scientific discovery into a health benefit. Dr. Cannistraci recognized that the key to success was the combination of his bioengineering skills in machine learning with the clinical expertise of the other corresponding author, Dr. Enrico Ammirati, of the San Raffaele Scientific Institute in Milano.
The authors, including KAUST professor, Dr. Timothy Ravasi, were working collaboratively at universities worldwide using systems biology techniques based on machine learning. The data was collected from a multi-ethnic group of over 200 patients from five countries in this gold standard case-control study. The researchers identified a characteristic circulating inflammatory cytokine pattern in emergency-room patients who presented with ST-elevation acute myocardial infarctions for the first time. This measure, named the Ammirati-Cannistraci index, is unrelated to the extent of the heart damage and other classical prognostic factors that are associated with mortality including age.
These observations could have potential implications for drug therapy at the time of the heart attack as well as for patient education around future risk.
The article can be viewed online in the high-impact cardiology journal, Circulation Research.
http://circres.ahajournals.org/content/early/2012/08/29/CIRCRESAHA.111.262477.full.pdf?ijkey=gKfHolBbUuvt77V&keytype=ref