Falls perceived as significant by lower limb prosthesis users are generally associated with fall consequences rather than circumstances.

PURPOSE: To determine if falls perceived as significant by lower limb prosthesis (LLP) users were associated with fall circumstances and/or consequences. MATERIALS AND METHODS: The circumstances and consequences of LLP users' most significant fall in the past 12-months were collected using the Lower Limb Prosthesis User Fall Event Survey. Participants rated fall significance from 0 (not significant) to 10 (extremely significant), which was then dichotomized into "low" and "high". Binary logistic regression was used to assess associations between fall significance and fall circumstances and consequences. RESULTS: Ninety-eight participants were included in the analysis. Five fall consequences were associated with greater significance: major injury (OR = 26.7, 95% CI: 1.6-459.6, p = 0.024), need to seek medical treatment (OR = 19.0, 95% CI: 1.1-329.8, p = 0.043), or allied-health treatment (OR = 18.2, 95% CI: 2.3-142.4, p = 0.006), decreased balance confidence (OR = 10.9, 95% CI: 2.4-49.3, p = 0.002), and increased fear of falling (OR = 7.5, 95% CI: 2.4-23.8, p = 0.001), compared to two fall circumstances: impact to the arm (OR = 5.0, 95% CI: 2.0-12.1, p = 0.001), and impact to the face, head, or neck (OR = 9.7, 95% CI: 1.2-77.4, p = 0.032). CONCLUSIONS: Significant falls were generally more associated with fall consequence than fall circumstances.

Falls remain common, injurious, costly, and socially isolating events for lower limb prosthesis (LLP) users.Falls perceived as most significant by LLP users were associated with injury, reduced balance confidence, and increased fear-of-falling.Studying falls perceived by LLP users as significant may help reduce falls that matter most to LLP users.

The number of falls recalled in the past year and balance confidence predict the frequency of injurious falls by unilateral lower limb prosthesis users.

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.

Recalled Number of Falls in the Past Year-Combined With Perceived Mobility-Predicts the Incidence of Future Falls in Unilateral Lower Limb Prosthesis Users.

OBJECTIVE: Falls are a frequent and costly concern for lower limb prosthesis (LLP) users. At present, there are no models that clinicians can use to predict the incidence of future falls in LLP users. Assessing who is at risk for falls, therefore, remains a challenge. The purpose of this study was to test whether easily accessible clinical attributes and measurements predict the incidence of future falls in LLP users. METHODS: In this prospective observational study, a secondary analysis of data from 60 LLP users was conducted. LLP users reported the number of falls that they recalled over the past year before prospectively reporting falls over a 6-month observation period via monthly telephone calls. Additional candidate predictor variables were recorded at baseline. Negative binomial regression was used to develop a model intended to predict the incidence of future falls. RESULTS: The final model, which included the number of recalled falls (incidence rate ratio = 1.13; 95% CI = 1.01 to 1.28) and Prosthetic Limb Users Survey of Mobility T-scores (incidence rate ratio = 0.949; 95% CI = 0.90 to 1.01), was significantly better than a null model at predicting the number of falls over the next 6 months (χ22 = 9.76) and fit the observed prospective fall count data (χ256 = 54.78). CONCLUSION: The number of recalled falls and Prosthetic Limb Users Survey of Mobility T-scores predicted the incidence of falls over the next 6 months in established, unilateral LLP users. The success and simplicity of the final model suggests that it may serve as a screening tool for clinicians to use for assessing risk of falls. Additional research to validate the proposed model in an independent sample of LLP users is needed. IMPACT: Owing to its simplicity, the final model may serve as a suitable screening measure for clinicians to ascertain an initial evaluation of fall risk in established unilateral LLP users. Analyzing falls data as counts rather than as a categorical variable may be an important methodological consideration for falls prevention research.