This study aimed to predict balance and gait abilities with the Trunk Impairment scales (TIS) in persons with stroke.
Cross-sectional study.
Sixty-eight participants with stoke were assessed with the TIS, Berg Balance scale (BBS), and Functional Gait Assessment (FGA) by a therapist. To describe of general characteristics, we used descriptive and frequency analyses, and the TIS was used as a predictive variable to determine the BBS. In the simple regression analysis, the TIS was used as a predictive variable for the BBS and FGA, and the TIS and BBS were used as predictive variables to determine the FGA in multiple regression analysis.
In the group with a BBS score of >45 for regression equation for predicting BBS score using TIS score, the coefficient of determination (R^{2}) was 0.234, and the R^{2} was 0.500 in the group with a BBS score of ≤45. In the group with an FGA score >15 for regression equation for predicting FGA score using TIS score, the R^{2} was 0.193, and regression equation for predicting FGA score using TIS score, the R^{2} was 0.181 in the group of FGA score ≤15. In the group of FGA score >15 for regression equation for predicting FGA score using TIS and BBS score, the R^{2} was 0.327. In the group of FGA score ≤15 for regression equation for predicting FGA score using TIS and BBS score, the R^{2} was 0.316.
The TIS scores are insufficient in predicting the FGA and BBS scores in those with higher balance ability, and the BBS and TIS could be used for predicting variables for FGA. However, TIS is a strong predictive variable for persons with stroke who have poor balance ability.
The trunk plays an important role in functional independence as well as basic motor control in activity of daily living [1]. However, the recovery or rehabilitation of the trunk is a more neglected area in stroke rehabilitation research or intervention compared to limb rehabilitation [2]. Although persons with have unilateral impairments on one side of the body, most persons with stroke have impaired trunk strength or functional performance [3]. Stroke survivors have decreased control of trunk movements, and these impaired movements of trunk also affect the body’s ability to maintain balance and perform rotational movement of the lower parts during walking. Therefore, the trunk should be highly considered when developing rehabilitation goals and for activity of daily living [4].
The trunk is an essential and fundamental component for overall functional independence [5]. The trunk has a strong relationship with functional outcomes such as gait [6], sitting balance [7], and there is a strong positive correlation between trunk performance and balance in stroke [8]. Therefore, it is important to estimate of trunk performance that essential for daily activities of livings and higher performance motoric tasks [8]. However, although trunk performance is an important component for predicting balance and functional task, the supporting evidence is not fully suggested in the rehabilitation for the stroke population [3]. Verheyden
Based on previous studies, the relationship between trunk performance and functional task in stroke is a special area of interest for early trunk exercise and improving balancing activities for later stages of rehabilitation [8]. Verheyden
Despite the strong and significant relationship between trunk performance with balance and gait, but there is insufficient information on predicting balance and gait based on trunk performance rather than overall activities of daily living. Relationship is performed by correlation statics for describing two variables for strength of relationship, but for predicting one variable by one variable bases on relationship is regression analysis is commonly used [13]. For these reasons, the purpose of this study was to analyze the prediction and explanation of and the relationship between trunk with balance and gait in persons with stroke.
Sixty-eight persons with stroke participated in this study. Data were collected from both inpatient and outpatient physical therapy rehabilitation facilities in rehabilitation hospitals. The general subject characteristics can be viewed in Table 1.
The participants were included if they had been diagnosed with stroke, were able to communicate with the evaluator, and were able to stand without assistance. Participants were excluded if there was a history of neurological, orthopedic, or psychological disorders that would affect their balance and gait, or any cognitive deficits that would impair the ability to comprehend the study procedures. Prior to participating in the study, the subjects provided their informed consent based on the Declaration of Helsinki principles.
To investigate the relationship of trunk performance on balance and gait in persons with stroke, three common clinical scales, such as the Trunk Impairment scale (TIS), Berg Balance scale (BBS), and Functional Gait Assessment (FGA), were used for evaluation in a random order by a therapist. Subjects were verbally given standardized instructions in regards to the clinical scales and performed the tests in a quiet room. Rest intervals were provided between each test. Subjects wore their own shoes throughout the evaluation.
The TIS was developed to assess static and dynamic balance and also coordination of the trunk by observation of the quality of trunk performance that affect the performance of activity of daily living in stroke survivors [14]. Also, the TIS was developed to predict the ability of outcomes as well as mobility after stroke. The TIS were assessed on the table and chair, and it is consisted of 17 items with 7 points for static components, 10 points for dynamic components and 6 points for coordinative components. The duration of the assessment was 15 minutes, and 23 points indicated a high score. The TIS has a high reliability (r=0.98) and validity (r=0.99) [15,16].
The BBS is currently the most common used balance assessment tool related to activity of daily living in the clinic and research area [9,17]. The BBS was developed by Berg
The FGA has the best discriminative ability in detecting high walking function in persons with stroke [21]. The FGA was developed by Wrisley
Descriptive analysis was performed for the subject characteristics, such as age, height, weight, length of time after the stroke incident, TIS, BBS, and FGA scores. The frequency analysis was performed for gender, the side where the paraplegia or paresis was present, and disease type. To determine the relationship between trunk performance and balance and gait abilities based on clinical scales, the simple regression analysis was conducted. The multiple regression analysis was performed to investigate the relationship between variables, with the dependent variables being FGA, and the predictor variables being the TIS and BBS. A significant level of
The simple regression equation was used for calculating the predicted BBS (Table 2) and FGA (Table 3) scores by using the TIS scores. For the regression equation for predicting BBS score using the TIS score, the correlation coefficient (r) was 0.781, the coefficient of determination (R^{2}) was 0.610, the regression constant was 23.523, and the regression coefficient for the BBS score was 1.418. In the group with a BBS score of >45 for regression equation for predicting the BBS score using the TIS score, the correlation coefficient (r) was 0.483, the coefficient of determination (R^{2}) was 0.234, the regression constant was 45.673, and the regression coefficient for the BBS score was 0.444. In the group with a BBS score of ≤45 for regression equation for predicting BBS score using TIS score, the correlation coefficient (r) was 0.707, the coefficient of determination (R^{2}) was 0.500, the regression constant was 22.794, and the regression coefficient for the BBS score was 1.204.
For the regression equation for predicting the FGA score using the TIS score, the correlation coefficient (r) was 0.733, the coefficient of determination (R^{2}) was 0.537, the regression constant was 2.149, and the regression coefficient for the FGA score was 1.084. In the group with an FGA score of >15 for regression equation for predicting the FGA score using the TIS score, the correlation coefficient (r) was 0.439, the coefficient of determination (R^{2}) was 0.193, the regression constant was 15.987, and the regression coefficient for the FGA score was 0.445. In the group with an FGA score of ≤15 for regression equation for predicting the FGA score using the TIS score, the correlation coefficient (r) was 0.425, the coefficient of determination (R^{2}) was 0.181, the regression constant was 6.710, and the regression coefficient for the BBS score was 0.381.
Table 4 shows the multiple regression equation for calculating the predicted FGA score by using the TIS and BBS score. For the regression equation for predicting the FGA score using the TIS and BBS scores, the correlation coefficient (r) was 0.816, the coefficient of determination (R^{2}) was 0.666, the regression constant was –8.864, and the regression coefficient for the FGA score were 0.420 for TIS and 0.468 for BBS. In the group with an FGA score of >15 for regression equation for predicting FGA score using TIS and BBS score, the correlation coefficient (r) was 0.572, the coefficient of determination (R^{2}) was 0.327 the regression constant was 3.217, and the regression coefficient for the FGA score was 0.340 for BBS. In the group with an FGA score of ≤15 for regression equation for predicting FGA score using TIS and BBS score, the correlation coefficient (r) was 0.562, the coefficient of determination (R^{2}) was 0.316 the regression constant was 2.824, and the regression coefficient for the FGA score was 0.199 for BBS. As seen in Table 5, the most significant variable that determined the FGA score in all the FGA groups were the TIS and BBS scores, but the BBS score was the most significant variable for determining the FGA scores for either group with an FGA of >15 or FGA ≤15. The TIS was not a significant predictor of the FGA score in the FGA >15 group (
This study aimed to predict balance and gait ability using BBS and FGS scores based on trunk performance, which were based on TIS scores, in persons with stroke. The results of this study showed that the TIS is valuable in predicting balance and walking ability in persons with stroke. In regards to balance based on BBS scores, the TIS has a 61% ability to predict the BBS score in stroke survivors, and especially more predictable in the group with BBS scores of below 45 (50%) and has a correlative (r=0.70) role in the persons with stroke rather than the group with a BBS score of below 45 of BBS. In regards to walking ability based on the FGA, the TIS has a 53.7% ability to predict FGA scores in the stroke survivors. However, it is not highly predictive in groups with FGS scores below or above 15 in stroke survivors. The BBS has a more predictive ability of 66.6% with the TIS for FGA score in stroke patients, however in the group below or above 15 of FGA is only had predictive ability of BBS for FGA score in stroke patients.
The trunk plays a critical role rather than the extremities during stroke rehabilitation, and is an essential component for developing coordinative movements of the extremities for balance as well as for motor tasks [3,6]. In this study, the TIS was used to predict balance and gait ability based on the clinical scales for stroke survivors. The TIS had a high correlation coefficient (r=0.781) and a predictive ability of 61% for the BBS score, and a high correlation coefficient (r=0.707) and a predictive ability of 50% for those with BBS scores below 45 rather than above. This result shows that balance ability is greatly correlated with TIS scores in persons with stroke. Having trunk control is critical in assuming an upright position and for weight shifting during static and dynamic postural control [3]. Verheyden
In the predictive FGA score by TIS had high correlation coefficient (r=0.733), but the predictive ability of TIS had a 53.7% for FGA that is relatively low rather than BBS. And also, TIS had low correlation coefficient and low predictive ability in each group of FGA below or above 15. Kim
In conclusion, this study aimed to predict balance and gait ability with trunk ability using clinical scales. The TIS, BBS, and FGA scores of 68 persons with stroke were used for analyses with regression. The results suggested that the TIS is the strongest variable for predicting BBS in stroke survivors with poor balance ability. However, the TIS was not enough to predict the FGA and BBS scores in those with higher balance ability. Also, the BBS and TIS can be used for predicting variables for FGA. Therefore, the use of predictive variable with TIS is not enough supporting gait ability. TIS is a strong predictive variable in stroke survivors with poor balance ability.
This work was supported by the 2017 Research-Year Grant of Jeonju University.
The author declared no potential conflicts of interest with respect to the authorship and/or publication of this article.
General characteristics of the participants of this study (N=68)
Characteristic | Value |
---|---|
Age (y) | 55.47 (11.83) |
Height (cm) | 164.74 (8.73) |
Weight (kg) | 63.51 (13.91) |
Post-stroke duration (mo) | 22.04 (12.13) |
Trunk Impairment scale (scores) | 14.54 (5.06) |
Berg Balance scale (scores) | 44.15 (9.19) |
Functional Gait Assessment (scores) | 17.91 (7.48) |
Gender (male/female) | 41/27 |
Affected side (left/right) | 42/26 |
Type (infarction/hemorrhage) | 32/36 |
Values are presented as mean (SD) or number only.
The equations for TIS on the BBS by simple regression analysis (N=68)
Clinical scale | Regression equation | r | R^{2} | F ( | |
---|---|---|---|---|---|
BBS (scores) | (23.523)+(1.418×TIS) | 0.781 | 0.610 | 0.781 | 103.090 (<0.001) |
BBS >45 (n_{1}=35) | (45.673)+(0.444×TIS) | 0.483 | 0.234 | 0.483 | 10.050 (0.003) |
BBS ≤45 (n_{2}=33) | (22.794)+(1.204×TIS) | 0.707 | 0.500 | 0.707 | 30.997 (<0.001) |
TIS: Trunk Impairment scale, BBS: Berg Balance scale.
The equations for TIS on the FGA by simple regression analysis (N=68)
Clinical scale | Regression equation | r | R^{2} | F ( | |
---|---|---|---|---|---|
FGA (scores) | (2.149)+(1.084×TIS) | 0.733 | 0.537 | 0.733 | 76.640 (<0.001) |
FGA >15 (n_{1}=37) | (15.987)+(0.445×TIS) | 0.439 | 0.193 | 0.439 | 8.362 (0.007) |
FGA ≤15 (n_{2}=31) | (6.710)+(0.381×TIS) | 0.425 | 0.181 | 0.425 | 6.397 (0.017) |
TIS: Trunk Impairment scale, FGA: Functional Gait Assessment.
The equations for TIS and BBS on the FGA by multiple regression analysis (N=68)
Clinical scale | Regression equation | r | R^{2} | |
---|---|---|---|---|
FGA (scores) | −8.864+(0.420×TIS)+(0.468×BBS) | 0.816 | 0.666 | <0.001 |
FGA >15 (n1=37) | 3.217+(0.340×BBS) | 0.572 | 0.327 | 0.001 |
FGA ≤15 (n_{2}=31) | 2.824+(0.199×BBS) | 0.562 | 0.316 | 0.005 |
TIS: Trunk Impairment scale, BBS: Berg Balance scale, FGA: Functional Gait Assessment.
Output for multiple regression analyses for the prediction of the FGA score from the TIS and BBS (N=68)
Clinical scale | |||
---|---|---|---|
FGA (scores) | TIS | 0.284 | 0.016 |
BBS | 0.575 | <0.001 | |
R^{2}=0.666, F=64.911, | |||
FGA >15 (n_{1}=37) | TIS | 0.200 | 0.242 |
BBS | 0.437 | 0.014 | |
R^{2}=0.327, F=8.254, | |||
FGA ≤15 (n_{2}=31) | TIS | 0.067 | 0.761 |
BBS | 0.514 | 0.026 | |
R^{2}=0.316, F=6.478, |
FGA: Functional Gait Assessment, TIS: Trunk Impairment scale, BBS: Berg Balance scale.