Prediction of gait independence using the Trunk Impairment Scale in patients with acute stroke

Abstract

Background: Gait recovery is one of the primary goals of stroke rehabilitation. Gait independence is a key functional component of independent activities in daily living and social participation. Therefore, early prediction of gait independence is essential for stroke rehabilitation. Trunk function is important for recovery of gait, balance, and lower extremity function. The Trunk Impairment Scale (TIS) was developed to assess trunk impairment in patients with stroke. Objective: To evaluate the predictive validity of the TIS for gait independence in patients with acute stroke. Methods: A total of 102 patients with acute stroke participated in this study. Every participant was assessed using the TIS, Stroke Impairment Assessment Set (SIAS), and Functional Independence Measure (FIM) within 48 h of stroke onset and at discharge. Gait independence was defined as FIM gait scores of 6 and 7. Multiple regression analysis was used to predict the FIM gait score, and multiple logistic regression analysis was used to predict gait independence. Cut-off values were determined using receiver operating characteristic (ROC) curves for variables considered significant in the multiple logistic regression analysis. In addition, the area under the curve (AUC), sensitivity, and specificity were calculated. Results: For the prediction of the FIM gait score at discharge, the TIS at admission showed a good-fitting adjusted coefficient of determination ( R2 = 0.672, p < 0.001). The TIS and age were selected as predictors of gait independence. The ROC curve had a TIS cut-off value of 12 points (sensitivity: 81.4%, specificity: 79.7%) and an AUC of 0.911. The cut-off value for age was 75 years (sensitivity: 74.6%, specificity: 65.1%), and the AUC was 0.709. Conclusion: The TIS is a useful early predictor of gait ability in patients with acute stroke.

Trunk Impairment Scale for Predicting Lumbar Spine Bone Mineral Density in Young Male Patients With Subacute Stroke

“…The novelty of this study lies in the focus on trunk stability in subacute stroke patients along with lumbar BMD. TIS scores in the early stages of stroke have usually been considered a predictor of functional ambulation at discharge [ 39 ]. In addition, our findings indicate that an early assessment of trunk balance could predict lumbar spine BMD in patients with trunk instability.…”

The relationship between characteristics of gait disturbance and injury patterns of the corticospinal tract and corticoreticular pathway in post-stroke patients: A case series of 3 patients

“…Walking speed was measured by a stopwatch marking when the patient passed the start and end lines of a 10-m walkway. In P1, some extent of recovery was observed regarding the weakness of her right lower extremity (from the FMA-LE score of 15-23, cutoff point: 21 [16] ) and trunk function (from the TIS score of 10-20, cutoff: 12 [17] ) over a 2-months period following her admission. The improvement in her balance performance stalled (from the Mini-BESTest score of 4-15, cutoff: 17.5 [18] ), but she was able to walk independently on an even floor at discharge (FAC score improvement from 0-4).…”

Development and internal validation of two prediction models of walking dependence and restricted walking speed in individuals with subacute stroke

“…The associated factors were based on published studies. We used age, leg strength, sitting balance, cognitive function, urinary function, and ADL independence [7][8][9][10][11][12][13][14][15][16][17][18][19][20]. The four variables of leg strength, sitting balance, cognitive function, and urinary incontinence were dichotomized, as previously described [26].…”

“…Previous longitudinal studies of walking dependence and walking speed in stroke have only reported associations in terms of odds ratios and other measures [7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Since it is clear that the strong associations captured by odds ratios do not translate into predictive ability in treating speci c patients, there is a need to use statistical methods focused on predicting outcomes for speci c individuals and to demonstrate the discrimination and calibration of prediction models [6, [21][22][23].…”

“…Previous studies reported that older age [7][8][9][10], poor leg strength of the affected side [9][10][11][12][13][14], poor sitting balance [14][15][16][17][18], the presence of cognitive impairment [10,20], urinary incontinence [19,20], and lower levels of functional independence [8,12,19,20] were associated with walking dependence and slow walking speed in individuals with stroke. Combining these factors will provide a more de nitive ability to predict walking outcomes.…”