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Full-Text Articles in Medicine and Health Sciences
Dynapenic Obesity And The Effect On Long-Term Physical Function And Quality Of Life: Data From The Osteoarthritis Initiative, John A. Batsis, Alicia J. Zbehlik, Dawna Pidgeon, Stephen J. Bartels
Dynapenic Obesity And The Effect On Long-Term Physical Function And Quality Of Life: Data From The Osteoarthritis Initiative, John A. Batsis, Alicia J. Zbehlik, Dawna Pidgeon, Stephen J. Bartels
Dartmouth Scholarship
Obesity is associated with functional impairment, institutionalization, and increased mortality risk in elders. Dynapenia is defined as reduced muscle strength and is a known independent predictor of adverse events and disability. The synergy between dynapenia and obesity leads to worse outcomes than either independently. We identified the impact of dynapenic obesity in a cohort at risk for and with knee osteoarthritis on function.
Pilot Comparative Effectiveness Study Of Surface Perturbation Treadmill Training To Prevent Falls In Older Adults, Jon D. Lurie, Alexandra B. Zagaria, Dawna M. Pidgeon, Judith L. Forman, Kevin Spratt
Pilot Comparative Effectiveness Study Of Surface Perturbation Treadmill Training To Prevent Falls In Older Adults, Jon D. Lurie, Alexandra B. Zagaria, Dawna M. Pidgeon, Judith L. Forman, Kevin Spratt
Dartmouth Scholarship
Falls are the leading cause of fatal and non-fatal injuries among older adults. Exercise programs appear to reduce fall risk, but the optimal type, frequency, and duration of exercise is unknown. External perturbations such as tripping and slipping are a major contributor to falls, and task-specific perturbation training to enhance dynamic stability has emerged as a promising approach to modifying fall risk. The purpose of this pilot study was 1) to determine the feasibility of conducting a large pragmatic randomized trial comparing a multidimensional exercise program inclusive of the surface perturbation treadmill training (SPTT) to multidimensional exercise alone (Standard PT); …
Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini
Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini
Dartmouth Scholarship
We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can …