Bowen Mary Elizabeth, Rowe Meredeth A, Ji Ming, Cacchione Pamela
School of Nursing, University of Delaware, STAR Tower, 100 Discovery Blvd., Newark, DE, 19713, USA.
Corporal Michael J. Crescenz VA Medical Center, 3900 Woodland Ave., Philadelphia, PA, 19104, USA.
BMC Res Notes. 2019 Sep 3;12(1):557. doi: 10.1186/s13104-019-4585-5.
Excessive and patterned ambulation is associated with falls, urinary tract infections, co-occurring delirium and other acute events among long-term care residents with cognitive impairment/dementia. This study will test a predictive longitudinal data model that may lead to the preservation of function of this vulnerable population.
METHODS/DESIGN: This is a single group, longitudinal study with natural observations. Data from a real-time locating system (RTLS) will be used to objectively and continuously measure ambulation activity for up to 2 years. These data will be combined with longitudinal acute event and functional status data to capture patterns of change in health status over time. Theory-driven multilevel models will be used to test the trajectories of falls and other acute conditions as a function of the ambulation activity and demographic, functional status, gait quality and balance ability including potential mediation and/or moderation effects. Data-driven machine learning algorithms will be applied to run screening of the high dimensional RTLS data together with other variables to discover new and robust predictors of acute events.
The findings from this study will lead to the early identification of older adults at risk for falls and the onset of acute medical conditions and interventions for individualized care.
在患有认知障碍/痴呆症的长期护理居民中，过度且有规律的行走与跌倒、尿路感染、同时发生的谵妄及其他急性事件相关。本研究将测试一种预测性纵向数据模型，该模型可能有助于保护这一脆弱人群的功能。
方法/设计：这是一项采用自然观察法的单组纵向研究。来自实时定位系统（RTLS）的数据将用于客观且持续地测量长达2年的行走活动。这些数据将与纵向急性事件和功能状态数据相结合，以捕捉健康状况随时间的变化模式。理论驱动的多层次模型将用于测试跌倒及其他急性状况的轨迹，作为行走活动以及人口统计学、功能状态、步态质量和平衡能力的函数，包括潜在的中介和/或调节作用。数据驱动的机器学习算法将应用于对高维度的RTLS数据以及其他变量进行筛选，以发现急性事件新的、可靠的预测因素。
本研究的结果将有助于早期识别有跌倒风险的老年人以及急性疾病的发作情况，并为个性化护理提供干预措施。
