Courtney D Hall1,2, Samuel C Karpen3, Brian Odle4, Peter C Panus5, Zachary F Walls5,6. 1. Department of Physical Therapy, College of Clinical and Rehabilitative Health Sciences, East Tennessee State University, Johnson City, TN, USA. 2. Auditory and Vestibular Dysfunction Research Enhancement Award Program, James H. Quillen VA Medical Center, Mountain Home, TN, USA. 3. Office of Academic Affairs, Gatton College of Pharmacy, East Tennessee State University, Johnson City, TN, USA. 4. Department of Pharmacy Practice, Gatton College of Pharmacy, East Tennessee State University, Johnson City, TN, USA. 5. Department of Pharmaceutical Sciences, Gatton College of Pharmacy, East Tennessee State University, Johnson City, TN, USA. 6. Center of Excellence for Inflammation, Infectious Disease and Immunity, East Tennessee State University, Johnson City, TN, USA.
Abstract
Background: the development of an objective and comprehensive drug-based index of physical function for older adults has the potential to more accurately predict fall risk. Design: the index was developed using 862 adults (ages 57-85) from the National Social Life, Health, and Aging Project (NSHAP) Wave 1 study. The index was evaluated in 70 adults (ages 51-88) from a rehabilitation study of dizziness and balance. Methods: the prevalence among 601 drugs for 1,694 side effects was used with fall history to determine the magnitude of each side effect's contribution towards physical function. This information was used to calculate a Medication-based Index of Physical function (MedIP) score for each individual based on his or her medication profile. The MedIP was compared to the timed up and go (TUG) test as well as drug counts using receiver operating characteristic (ROC) analysis. The associations between various indices of physical function and MedIP were calculated. Results: within the NSHAP data set, the MedIP was better than drug counts or TUG at predicting falls based on ROC analysis. Using scores above and below the cutpoint, the MedIP was a significant predictor of falls (OR = 2.61 [95% CI 1.83, 3.64]; P < 0.001). Using an external data set, it was shown that the MedIP was significantly correlated with fall number (P = 0.044), composite physical function (P = 0.026) and preferred gait speed (P = 0.043). Conclusion: the MedIP has the potential to become a useful tool in the healthcare and fall prevention of older individuals.
Background: the development of an objective and comprehensive drug-based index of physical function for older adults has the potential to more accurately predict fall risk. Design: the index was developed using 862 adults (ages 57-85) from the National Social Life, Health, and Aging Project (NSHAP) Wave 1 study. The index was evaluated in 70 adults (ages 51-88) from a rehabilitation study of dizziness and balance. Methods: the prevalence among 601 drugs for 1,694 side effects was used with fall history to determine the magnitude of each side effect's contribution towards physical function. This information was used to calculate a Medication-based Index of Physical function (MedIP) score for each individual based on his or her medication profile. The MedIP was compared to the timed up and go (TUG) test as well as drug counts using receiver operating characteristic (ROC) analysis. The associations between various indices of physical function and MedIP were calculated. Results: within the NSHAP data set, the MedIP was better than drug counts or TUG at predicting falls based on ROC analysis. Using scores above and below the cutpoint, the MedIP was a significant predictor of falls (OR = 2.61 [95% CI 1.83, 3.64]; P < 0.001). Using an external data set, it was shown that the MedIP was significantly correlated with fall number (P = 0.044), composite physical function (P = 0.026) and preferred gait speed (P = 0.043). Conclusion: the MedIP has the potential to become a useful tool in the healthcare and fall prevention of older individuals.
Authors: Jamie N Justice; Marnie G Silverstein-Metzler; Beth Uberseder; Susan E Appt; Thomas B Clarkson; Thomas C Register; Stephen B Kritchevsky; Carol A Shively Journal: Geroscience Date: 2017-10-28 Impact factor: 7.713
Authors: Farhad Pazan; Heinrich Burkhardt; Helmut Frohnhofen; Christel Weiss; Christina Throm; Alexandra Kuhn-Thiel; Martin Wehling Journal: Drugs Aging Date: 2019-03 Impact factor: 3.923