MedElevator
Войти в исследования Archives of physical medicine and rehabilitation · 2015
Two-Year Trajectory of Fall Risk in People With Parkinson Disease: A Latent Class Analysis.
СтатьяМногоцентровое исследованиеПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Paul Serene S, Thackeray Anne, Duncan Ryan P, Cavanaugh James T, Ellis Theresa D, Earhart Gammon M, Ford Matthew P, Foreman K Bo, Dibble Leland E
Аннотация
OBJECTIVE: To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD).
DESIGN: Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories.
SETTING: Assessments were conducted at 1 of 4 universities.
PARTICIPANTS: Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230).
INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURES: Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed.
RESULTS: The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance.
CONCLUSIONS: Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD.
DESIGN: Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories.
SETTING: Assessments were conducted at 1 of 4 universities.
PARTICIPANTS: Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230).
INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURES: Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed.
RESULTS: The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance.
CONCLUSIONS: Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD.