Abstract
Introduction
Several personal characteristics have been associated with an increased risk of injurious falls by lower limb prosthesis (LLP) users. To date, however, none have been used to effectively predict the occurrence of injurious falls.
Objective
To develop a model that could predict the number of injurious falls over the next 6 months and identify fall‐related circumstances that may increase the odds of a fall being injurious in unilateral LLP users.
Design
A secondary analysis of a prospective observational study.
Setting
Research laboratory.
Participants
Sixty unilateral LLP users with a transtibial or transfemoral amputation.
Intervention
Not applicable.
Main outcome measure(s)
Participants' characteristics were recorded at baseline. Falls and their circumstances and consequences were collected prospectively over 6 months via monthly telephone calls. Multivariate negative binomial regression was used to predict the number of injurious falls over the next 6 months in LLP users. Incidence rate ratios (IRRs) were derived to determine the risk of an injurious fall. Bivariate logistic regression was used to identify the associations between injurious falls and fall‐related circumstances. Odds ratios (ORs) were derived to characterize the odds that a fall would be injurious.
Results
The final multivariate model, which included the number of falls recalled in the past year (IRR = 1.31, 95% confidence interval [CI]: 1.01–1.71, p = .045) and balance confidence (p = .120), predicted the number of injurious falls in the next 6 months (χ2 (2) = 8.15, p = .017). Two fall‐related circumstances were found to increase the odds that a fall would be injurious, fatigue due to activity (OR = 13.5, 95% CI: 3.50–52.3, p = .001), and tiredness from a lack of sleep (OR = 5.36, 95% CI: 1.22–23.6, p = .026).
Conclusion
The results suggest that the number of falls recalled in the past year and balance confidence scores predict the number of injurious falls an LLP user will experience in the next 6 months.