[Purpose] This study aimed to examine the inter- and intra-rater reliability and validity
of the modified functional ambulation category (mFAC) scale. [Subjects and Methods] The
participants were 66 stroke patients with hemiparalysis. The inter- and intra-rater
validity of the mFAC was calculated using the Spearman correlation coefficient. A score
comparison of the stable or maximum gait speed with regard to mFAC and modified Rivermead
Mobility Index (mRMI) performances was performed as a univariate linear regression
analysis to determine how the Kruskal-Wallis test affects the mRMI and stable/maximum gait
speed with regard to mFAC. [Results] The inter-rater reliability of the mFAC (intraclass
coefficient [ICC]) was 0.982 (0.971–0.989), with a kappa coefficient of 0.923 and a
consistency ratio of 94%. In contrast, the intra-rater reliability of the mFAC (ICC) was
0.991 (0.986–0.995), with a kappa coefficient of 0.961 and a consistency ratio of 96%,
showing higher reliability. Moreover, there was a significant difference in stable/maximum
gait speed between the mFAC and the mRMI. [Conclusion] Since the mFAC has sufficient
inter- and intra-reliability and high validity, it can be used as an assessment tool that
reflects the gait performance and mobility of stroke patients.
Background:The cut-off values of walking velocity and classification of functional mobility both have a role in clinical settings for assessing the walking function of stroke patients and setting rehabilitation goals and treatment plans.Objective:The present study investigated whether the cut-off values of the modified Rivermead Mobility Index (mRMI) and walking velocity accurately differentiated the walking ability of stroke patients according to the modified Functional Ambulation Category (mFAC).Methods:Eighty two chronic stroke patients were included in the study. The comfortable/maximum walking velocities and mRMI were used to measure the mobility outcomes of these patients. To compare the walking velocities and mRMI scores for each mFAC point, one-way analysis of variance and the post-hoc test using Scheffe’s method were performed. The patients were categorized according to gait ability into either mFAC=VII or mFAC ≤ VI group. The cut-off values for mRMI and walking velocities were calculated using a receiver-operating characteristic curve. The odds ratios of logistic regression analysis (Wald Forward) were analyzed to examine whether the cut-off values of walking velocity and mRMI can be utilized to differentiate functional walking levels.Results:Except for mFACs III and IV, maximum walking velocity differed between mFAC IV and mFAC V (p<0.01), between mFAC V and mFAC VI (p<0.001), and between mFAC VI and mFAC VII (p<0.05). The cut-off value of mRMI is >26.5 and the area under the curve is 0.87, respectively; the cut-off value for comfortable walking velocity is >0.77 m/s and the area under the curve is 0.92, respectively; also, the cut-off value for maximum walking velocity is >0.92 m/s and the area under the curve is 0.97, respectively. In the logistic regression analysis, the maximum walking velocity (>0.92 m/s, OR=22.027) and mRMI (>26.5 scores, OR=10.283) are able to distinguish mFAC=VII from mFAC ≤ VI.Conclusion:The cut-off values of maximum walking velocity and mRMI are recommended as useful outcome measures for assessing ambulation levels in chronic stroke patients during rehabilitation.
Objective:The timed up and go (TUG) test is method used to determine the functional mobility of persons with stroke. Its reliability, validity, reaction rate, fall prediction, and psychological characteristics concerning ambulation ability have been validated. However, the relationship between TUG performance and community ambulation ability is unclear. The purpose of this study was to investigate whether the TUG performance time could indicate community ambulation levels (CAL) differentially in persons with chronic stroke. Design: Cross-sectional study. Methods: Eighty-seven stroke patients had participated in this study. Based on the self-reporting survey results on the difficulties experienced when walking outdoors, the subjects were divided into the independent community ambulation (ICA) group (n=35) and the dependent community ambulation group (n=52). Based on the area under the curve (AUC), the discrimination validity of the TUG performance time was calculated for classifying CAL. The Binomial Logistic Regression Model was utilized to produce the likelihood ratio of selected TUG cut-off values for the distinguishing of community ambulation ability. Results: The selected TUG cut-off values and the area under the curve were <14.87 seconds (AUC=0.871, 95% confidence interval=0.797-0.945), representing a mid-level accuracy. Concerning the likelihood ratio of the selected TUG cut-off value, it was found that the group with TUG performance times shorter than 14.87 seconds showed a 2.889 times higher probability of ICA than those with a TUG score of 14.87 seconds or longer (p<0.05).
Conclusions:The TUG can be viewed as an assessment tool that is capable of classifying CAL.
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