Abbott Laboratories Corporation

Emory University

Agim Beshiri

Saul A Datwyler

Beth McQuiston

Jaime Marino

Frederick Korley

Arshed A Quyyumi

Janel Huang

Shaoqing Du

Shu Yuan Woon

Eliza Mohd Noor

Jeganathan Ravichandran

Jaganathan Sickan

Yee Cherng Lim

Kumar Suresh

Ramakrishnan Vigneswaran

Shihai Lu

Yek Song Quek

Disclosed herein are methods that aid in the diagnosis and evaluation of a human subject that has sustained or may have sustained an injury to the head, such as mild or moderate, severe, or moderate to severe traumatic brain injury (TBI), using cTnI. Also disclosed are methods for determining whether to perform a head computerized tomography on a subject by detecting levels of cTnI. Finally, also disclosed are methods of outcome in subjects suffering from a mild TBI.

Methods for aiding in diagnosing and evaluating a mild traumatic brain injury in a human subject using cardiac troponin I

Disclosed herein are methods that aid in the diagnosis and evaluation of a human subject that has sustained or may have sustained an injury to the head, such as mild or a moderate, severe, or moderate to severe traumatic brain injury (TBI), by detecting levels of cardiac troponin I (cTnI) and one or more early biomarkers which are not cTnI, such as ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), glial fibrillary acidic protein (GFAP), or a combination thereof, in biological samples taken from a human subject at time points within about 24 hours of injury after the subject has sustained or may have sustained the injury to the head.

Methods for aiding in diagnosing and evaluating a mild traumatic brain injury in a human subject using cardiac troponin I and early biomarkers

The invention provides decision tree based systems and methods for estimating the risk of acute coronary syndrome (ACS) in subjects suspect of having ACS. In particular, systems and methods are provided that employ additive decision tree based algorithms to process a subject's initial cardiac troponin I or T (cTnI or cTnT) concentration, a subject's cTnI or cTnT rate of change, and at least one of the following: the subject's age, the subject's gender, the subject's ECG value, the subject's hematology parameter value, to generate an estimate risk of ACS. Such risk stratification allows, for example, patients to be ruled in or rule out with regard to needing urgent treatment.

Decision tree based systems and methods for estimating the risk of acute coronary syndrome

Provided herein are methods for predicting or determining whether a subject with coronary artery disease is likely to experience or develop a major adverse cardiovascular event (MACE) based on determining cardiac troponin (cTnI) levels in a human at rest and during or after exercise.

Methods for predicting major adverse cardiovascular events in subjects with coronary artery disease

Growing community of inventors

Abbott Park, IL, United States of America

Agim Beshiri