MedAware Systems to Present Research on Biomarkers in Predicting Alzheimer's Disease at AAIC 2019

BROOMFIELD, Colo. - April 2, 2019 - PRLog -- MedAware Systems announced today that its comprehensive study Beyond Amyloid Beta and Tau - an Exploration of Alternative Measures Associated with Alzheimer's Disease Stage: A Review and Meta-Analysis has been accepted for presentation at the Alzheimer's Association International Conference (AAIC 2019), July 14 through 18, in Los Angeles, CA. The study was led by Travis Spear, MS, with support from Anna V. Ivashchenko, MPH, Kate Yzquierdo, MBA and Zung Vu Tran, PhD.

Cerebrospinal fluid (CSF) levels of amyloid beta and tau are well studied as biomarkers associated with Alzheimer's disease (AD). The validity of other minimally invasive biomarkers including brain volumes, albumin, and blood pressure is still debated. This study evaluated the association of amyloid beta, tau, and other potential biomarkers of AD, with Alzheimer's patients' cognitive performance as measured by the Mini-Mental State Examination (MMSE)

Results show that select biomarkers correlate with cognitive performance, measured by MMSE. They include t-tau, whole brain volume, total hippocampal volume, and systolic blood pressure.

"These results support the need to validate additional biomarkers to be used in the detection of AD.", said Dr. Zung Vu Tran, MedAware Systems' Chief Science Officer. He continued: "Whole brain and hippocampal volumes both displayed significant correlations with MMSE and may be a potential predictor of Alzheimer's disease. Systolic blood pressure also displayed a strong positive correlation with MMSE, an association that may be confounded by the unreported use of antihypertensive drugs at baseline."

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MedAware Systems, Inc. changes the way Pharma and medical device companies, physicians, payers and patients derive usable evidence from published clinical trials research. The Company's Science of Health Informatics (SOHInfo™) is a Scientific-Data-as-a-Service (SDaaS™) that solves the problem of making the vast and chaotic body of clinical science research data instantly available and indispensable for understanding the safety and efficacy of medical treatments and devices.

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