Determining the walking ability of post-stroke patients is crucial for the design of rehabilitation programs and the correct functional information to give to patients and their caregivers at their return home after a neurorehabilitation program. We aimed to assess the convergent validity of three different walking tests: the Functional Ambulation Category (FAC) test, the 10-m walking test (10MeWT) and the 6-minute walking test (6MWT). Eighty walking participants with stroke (34 F, age 64.54 ± 13.02 years) were classified according to the FAC score. Gait speed evaluation was performed with 10MeWT and 6MWT. The cut-off values for FAC and walking tests were calculated using a receiver-operating characteristic (ROC) curve. Area under the curve (AUC) and Youden's index were used to find the cut-off value. Statistical differences were found in all FAC subgroups with respect to walking speed on short and long distances, and in the Rivermead Mobility Index and Barthel Index. Mid-level precision (AUC > 0.7; p < 0.05) was detected in the walking speed with respect to FAC score (III vs. IV and IV vs. V). The confusion matrix and the accuracy analysis showed that the most sensitive test was the 10MeWT, with cut-off values of 0.59 m/s and 1.02 m/s. Walking speed cut-offs of 0.59 and 1.02 m/s were assessed with the 10MeWT and can be used in FAC classification in patients with subacute stroke between the subgroups able to walk with supervision and independently on uniform and non-uniform surfaces. Moreover, the overlapping walking speed registered with the two tests, the 10MeWT showed a better accuracy to drive FAC classification.

Convergent Validity of the Timed Walking Tests with Functional Ambulatory Category in Subacute Stroke / Martino Cinnera, Alex; Marrano, Serena; DE BARTOLO, Daniela; Iosa, Marco; Bisirri, Alessio; Leone, Enza; Stefani, Alessandro; Koch, Giacomo; Ciancarelli, Irene; Paolucci, Stefano; Morone, Giovanni. - In: BRAIN SCIENCES. - ISSN 2076-3425. - (2023). [10.3390/brainsci13071089]

Convergent Validity of the Timed Walking Tests with Functional Ambulatory Category in Subacute Stroke

Daniela De Bartolo;Marco Iosa;
2023

Abstract

Determining the walking ability of post-stroke patients is crucial for the design of rehabilitation programs and the correct functional information to give to patients and their caregivers at their return home after a neurorehabilitation program. We aimed to assess the convergent validity of three different walking tests: the Functional Ambulation Category (FAC) test, the 10-m walking test (10MeWT) and the 6-minute walking test (6MWT). Eighty walking participants with stroke (34 F, age 64.54 ± 13.02 years) were classified according to the FAC score. Gait speed evaluation was performed with 10MeWT and 6MWT. The cut-off values for FAC and walking tests were calculated using a receiver-operating characteristic (ROC) curve. Area under the curve (AUC) and Youden's index were used to find the cut-off value. Statistical differences were found in all FAC subgroups with respect to walking speed on short and long distances, and in the Rivermead Mobility Index and Barthel Index. Mid-level precision (AUC > 0.7; p < 0.05) was detected in the walking speed with respect to FAC score (III vs. IV and IV vs. V). The confusion matrix and the accuracy analysis showed that the most sensitive test was the 10MeWT, with cut-off values of 0.59 m/s and 1.02 m/s. Walking speed cut-offs of 0.59 and 1.02 m/s were assessed with the 10MeWT and can be used in FAC classification in patients with subacute stroke between the subgroups able to walk with supervision and independently on uniform and non-uniform surfaces. Moreover, the overlapping walking speed registered with the two tests, the 10MeWT showed a better accuracy to drive FAC classification.
2023
correlation of data; gait; gait disorders; neurologic; outcome measures; stroke; walking speed
01 Pubblicazione su rivista::01a Articolo in rivista
Convergent Validity of the Timed Walking Tests with Functional Ambulatory Category in Subacute Stroke / Martino Cinnera, Alex; Marrano, Serena; DE BARTOLO, Daniela; Iosa, Marco; Bisirri, Alessio; Leone, Enza; Stefani, Alessandro; Koch, Giacomo; Ciancarelli, Irene; Paolucci, Stefano; Morone, Giovanni. - In: BRAIN SCIENCES. - ISSN 2076-3425. - (2023). [10.3390/brainsci13071089]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1691256
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