Applying an artificial intelligence (AI) algorithm to abdominal imaging can help predict adults at higher risk for falling as early as middle age, according to a study published in the December issue of Mayo Clinic Proceedings: Digital Health.
Jennifer L. St. Sauver, Ph.D., from the Mayo Clinic in Rochester, Minnesota, and colleagues examined whether abdominal computed tomography (CT) measures of body composition (calculated via a validated deep learning algorithm applied to CT abdominal section) are associated with fall risk in adults aged 20 to 89 years. The analysis included 3,972 adult participants in the Rochester Epidemiology Project (2010 to 2020).
The researchers found that subcutaneous and visceral fat area, skeletal muscle area, bone area, and bone density were not associated with fall risk. The lowest tertile versus the middle tertile of muscle density was associated with an increased risk for falls (adjusted hazard ratio, 2.31). The association between low muscle density and an increased risk for falls was greatest in adults aged 45 to 64 years (adjusted hazard ratio, 4.98).
“One of the most important messages from this research is to keep your abdominal muscles in the best shape possible,” St. Sauver said in a statement. “Doing so may provide benefits that start in midlife and continue well into older adulthood.”
One author disclosed ties to the medical technology industry.
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