Article

This exploratory study investigated to what extent gait
characteristics and clinical physical therapy assessments predict falls in chronic stroke survivors. DESIGN: Prospective study. SUBJECTS:
Chronic fall-prone
and non-fall-prone stroke survivors. METHODS: Steady-state gait characteristics
were collected from 40 participants while walking on a treadmill with motion
capture of spatio-temporal, variability, and stability measures. An accelerometer
was used to collect daily-life gait characteristics during 7 days.
Six physical
and psychological assessments were administered. Fall events were determined
using a "fall calendar" and monthly phone calls over a 6-month period. After data
reduction through principal component analysis, the predictive capacity of each
method was determined by logistic regression. RESULTS: Thirty-eight percent of
the participants were classified as fallers. Laboratory-based and daily-life gait
characteristics predicted falls acceptably well, with an area under the curve of,
0.73 and 0.72, respectively, while fall predictions from clinical assessments
were limited (0.64). CONCLUSION: Independent of the type of gait assessment,
qualitative gait characteristics are better fall predictors than clinical
assessments. Clinicians should therefore consider gait analyses as an alternative
for identifying fall-prone stroke survivors.

Langue : ANGLAIS