Measuring frailty may help predict mortality in older adults undergoing cardiac surgery

An analysis of two databases found that measuring frailty could help predict mortality and functional status at six months or later after older adults undergo cardiac surgery.

A patient’s frailty status, assessed by mobility, disability and nutritional status, might also help predict functional decline, poor quality of life or lack of symptomatic benefit after patients undergo minimally invasive procedures.

Lead researcher Dae Hyun Kim, MD, MPH, of Beth Israel Deaconess Medical Center in Boston and colleagues published their results online in the Annals of Internal Medicine on Aug. 22.

The researchers searched the MEDLINE and EMBASE databases from their inception through May 2, 2016 and examined reference lists of reviews and articles that met their inclusion criteria. They identified 25 studies that evaluated the association between frailty and death or functional status at six months or later in patients who had a mean age of at least 60 years old.

In all, they evaluated 18,388 patients who underwent major cardiac surgery (CABG or open valve surgery) and 5,177 patients who underwent transcatheter aortic valve replacement (TAVR), which is a minimally invasive cardiac surgery.

The studies examining major cardiac surgery included nine frailty instruments. The researchers said there was moderate-quality evidence to asses mobility or disability and very low- to low-quality evidence to use a multicomponent instrument to predict mortality or major adverse cardiovascular and cerebrovascular events. None of the studies examined functional status in patients undergoing major cardiac surgery.

For patients undergoing TAVR, the studies evaluated three frailty instruments. The researchers mentioned there was moderate- to high-quality evidence for assessing mobility to predict mortality or functional status and low to moderate evidence to use multicomponent instruments to predict mortality, functional status or. major adverse cardiovascular and cerebrovascular events. They added that multicomponent instruments that measured different frailty domains were typically superior to single-component instruments.

The researchers mentioned that clinicians should classify patients into extreme-risk, high-risk and low-risk groups. They added that functional status could be just as important as health status.

Further, they mentioned a practical, sensitive and validated screening test such as gait speed or the TUG (Timed Up and Go) test could be used in a broad group of patients. In addition, they recommended that criteria should be established for selecting a single component or multicomponent frailty instrument and for determining which domains to measure. For instance, they suggested developing a risk prediction tool based on mobility, nutrition, disability and cognition could be beneficial at informing clinical care.

“Patients with positive screening results should have a comprehensive geriatric assessment that provides a benchmark for evaluating and managing frail older adults,” the researchers wrote. “The purpose of comprehensive assessment is to refine surgical risk stratification and to deliver individualized care to prevent complications and promote recovery and independence after cardiac surgery.”

Tim Casey,

Executive Editor

Tim Casey joined TriMed Media Group in 2015 as Executive Editor. For the previous four years, he worked as an editor and writer for HMP Communications, primarily focused on covering managed care issues and reporting from medical and health care conferences. He was also a staff reporter at the Sacramento Bee for more than four years covering professional, college and high school sports. He earned his undergraduate degree in psychology from the University of Notre Dame and his MBA degree from Georgetown University.

Around the web

Several key trends were evident at the Radiological Society of North America 2024 meeting, including new CT and MR technology and evolving adoption of artificial intelligence.

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.