Biomarkers for Frailty and Unsuccessful Aging
Approved Research ID: 63081
Approval date: August 27th 2020
One of the main manifestations of unsuccessful aging - frailty - is highly prevalent among older adults, yet it is vastly under-diagnosed. A reason for this under-diagnosis is that testing for frailty in clinical practice requires time-consuming inputs from clinicians and patients. Another reason is that testing is often based on questionnaires that lack accuracy and reliability, or physical performance tests that lack feasibility in the acute care setting. Thus, there is an unmet need to objectively and efficiently measure frailty with minimal human work.
We propose to accomplish this by studying biomarkers that are associated with frailty, musculoskeletal aging and loss of muscle mass, cardiovascular aging, and age-related diseases or impairments. Specifically, the objectives of the current study are to develop artificial intelligence (AI) algorithms that can diagnose frailty and predict which patients may be at risk of developing frailty, as well as determine whether these novel frailty scores can be used to predict the risk of adverse health events, hospitalization outcomes, and clinical outcomes. By developing a more individualized measure of frailty that is easier for healthcare providers to assess, the public health impact of this two-year research study can help close current gaps in the diagnosis of frailty and provide a tool that can better guide treatment decisions.