Brain Sciences (Jul 2023)

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

  • Alex Martino Cinnera,
  • Serena Marrano,
  • Daniela De Bartolo,
  • Marco Iosa,
  • Alessio Bisirri,
  • Enza Leone,
  • Alessandro Stefani,
  • Giacomo Koch,
  • Irene Ciancarelli,
  • Stefano Paolucci,
  • Giovanni Morone

DOI
https://doi.org/10.3390/brainsci13071089
Journal volume & issue
Vol. 13, no. 7
p. 1089

Abstract

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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.

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