Abstract
Objectives
To develop a prognostic model to predict the probability of a short-term fall (within
the next 7 to 30 days) in older adults with dementia.
Design
Prospective observational study.
Setting and Participants
Fifty-one individuals with dementia at high risk of falls from a specialized dementia
inpatient unit.
Methods
Clinical and demographic measures were collected and a vision-based markerless motion
capture was used to record the natural gait of participants over a 2-week baseline.
Falls were tracked throughout the length of stay. Cox proportional hazard regression
analysis was used to build a prognostic model to determine fall-free survival probabilities
at 7 days and at 30 days. The model's discriminative ability was also internally validated.
Results
Fall history and gait stability (estimated margin of stability) were statistically
significant predictors of time to fall and included in the final prognostic model.
The model's predicted survival probabilities were close to observed values at both
7 and 30 days. The area under the receiver operating curve was 0.80 at 7 days, and
0.67 at 30 days and the model had a discrimination performance (the Harrel concordance
index) of 0.71.
Conclusions and Implications
Our short-term falls risk model had fair to good predictive and discrimination ability.
Gait stability and recent fall history predicted an imminent fall in our population.
This provides some preliminary evidence that the degree of gait instability may be
measureable in natural everyday gait to allow dynamic falls risk monitoring. External
validation of the model using a separate data set is needed to evaluate model's predictive
performance.
Keywords
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Article info
Publication history
Published online: September 05, 2020
Footnotes
This work was supported by the Alzheimer's Association and Brain Canada (New Investigator Research Grant NIRG-15-364158); NSERC discovery grant (RGPIN 435653); NSERC Engage grant (499955-16); FedDev Ontario; Toronto Rehabilitation Institute start-up funds; an Academic Scholars Award from the Department of Psychiatry, University of Toronto (AI); a Canadian Institutes of Health Research Project Grant (169166) and New Investigator Award (MSH-141-983; AM); AGE-WELL Canada's Technology and Aging Network; The Walter and Maria Schroeder Institute for Brain Innovation and Recovery, and Mitacs Accelerate Award (No.: IT11267; SM).
A.J. Flint has received grant support from the US National Institutes of Health, the Patient-Centered Outcomes Research Institute, the Canadian Institutes of Health Research, Brain Canada, the Ontario Brain Institute, and Alzheimer's Association.
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© 2020 AMDA - The Society for Post-Acute and Long-Term Care Medicine.
