Main findings and interpretation
The analysis adjusted for covariates demonstrated an association between LEPF and QoL. Notably, the effect size for our model, as indicated by Cohen’s f², is 1.93. This value significantly exceeds the threshold for a large effect size (f² = 0.35), suggesting a strong association between TUG scores and QoL changes. This underscores the importance of TUG performance as a predictor of QoL outcomes in individuals post-stroke, affirming its relevance in clinical assessments and interventions aimed at improving quality of life.
Importantly, for each additional second required to complete the TUG test at baseline (i.e. 3 months post stroke), we observed an estimated decrease of 1.37 points in SS-QoL scores. This finding is particularly noteworthy in the context of the minimal clinically important difference (MCID) for SS-QoL, which has been reported to be 4.7 points among patients with aneurysmal subarachnoid hemorrhage [
29]. Our results suggest that even modest increases in TUG times – reflecting decreased mobility – could contribute to clinically meaningful deteriorations in quality of life. Given that a change of approximately 3.43 s in TUG time would approach the MCID for SS-QoL, our study underscores the critical importance of physical function in the recovery and rehabilitation of stroke survivors. These findings highlight the potential value of interventions aimed at enhancing mobility, such as targeted physical therapy, in significantly impacting patients’ quality of life post-stroke. Thus, incorporating regular assessments of physical function, using tools like the TUG test, into clinical practice could provide valuable insights into patients’ rehabilitation progress and overall well-being.
Comparison with previous studies
A paucity of research exists regarding TUG being a predictor of QoL in Stroke patients. However, in other patient populations, higher measures of LEPF, including a quicker TUG performance and walking speed, have been demonstrated to be associated with higher values in QoL [
30‐
32]. These studies, which are discussed in more depth below, included patients with Parkinson`s disease [
32,
33] osteoporosis [
30,
34] and musculoskeletal disorders [
31].
Stegmöller and colleagues investigated the relationship between TUG performance and predictors of QoL on the Parkinson’s Disease Questionnaire (PDQ-39) for 1964 patients with a mean TUG score of 11.0 s [
32]. Significant correlations were reported between TUG and each of the PDQ-39 domains. Ellis and colleagues reported a similar correlation between higher physical function performance and PDQ-39 domains for 263 patients with Parkinson`s disease, with a mean TUG performance of 13.2 s [
33]. In a study describing an association between QoL, walking speed and TUG in patients with osteoporosis-related fractures, aged between 60 and 93 years (
n = 155), participants were categorized in the “Fast” group if they demonstrated a mean TUG of 9.9 s [
30]. A lower TUG performance was found to be associated with a lower health-related QoL [
30]. Similarly, Hirano concluded that the TUG test may be a useful clinical tool to evaluate the QoL of patients with musculoskeletal disorders (
n = 386). The mean TUG performance in their sample was 6.8 s [
31]. The participants included in our study demonstrated a mean TUG performance of 10.1 (SD 4.4) seconds 3 months after the stroke and 8.7 (SD 2.9) seconds 12 months after the stroke, suggesting that the included patients had a relatively adequate physical function post stroke. The relatively high physical function of patients in this sample may be related to the study exclusion criteria which excluded patients with severe mobility restrictions and therefore patients who were included had generally mild symptoms post stroke. The median NIHSS score of 2 of the current study population is indicative of minor stroke severity which would also have an impact on general physical function. However, as the studies discussed above were cross-sectional in design, these results should be interpreted with caution.
Further research is required to investigate the role of the TUG as a tool not only to assess physical function and mobility as such but also its (predictive) value regarding broader aspects of meaningful recovery for patients following a stroke such as QoL and other patient-reported outcomes.
Improvements in other measures of LEPF including balance (Berg Balance Scale (BBS)), gait speed, and step length (non-paretic and paretic limb) [
8] have been shown to be correlated with improvements in SS-QoL. Chen and colleagues demonstrated that the BBS was a major predictor of mobility and subsequent participation/role domains of the Health-Related Quality of Life (HRQoL) [
35]. Gait speed is commonly used to quantify functional capacity of stroke patients. Improved QoL scores correlated with improved walking speed at 6-month follow-up [
36]. Muscle strength and tone were also demonstrated to create an improvement in gait speed alongside balance [
37] and therefore are deemed vital areas of focus in neurorehabilitation post stroke to improve patient QoL. The TUG can be considered a combined assessment of dynamic balance, lower extremity strength, and walking ability. As such, our findings are in line with the results reported in the above studies. Overall, the results of this study are supported by the findings of previous studies regarding the integration of improving LEPF in post-stroke rehabilitation and its relationship with QoL.
Relevance for future interventions
LEPF has a positive impact on the self-reported QoL of individuals, as evident from the existing body of literature and the results of our study. Therefore, a quick recovery of physical function post stroke is relevant to further support the positive development of patients’ QoL.
Strengths and limitations
Strengths of this study include the longitudinal design (i.e. repeated measures at specific time points) as well as the rigorously standardised laboratory conditions in our hospital. This study was limited by a relatively small sample size which impacts the generalisability of the study results. The sample size also limited the number of potential confounders to be included in the regression model. As the study was conducted during the Covid-19 pandemic, opportunities for participation in social activities were limited and thus these social restrictions may have had an impact on QoL and thereby the study results. The exclusion criteria of this study ruled out participants who were experiencing an acute depression and those unable to walk with personal assistance and therefore the results may not be representative for all patient groups following a stroke. Specific data on the duration of hospitalisation post-stroke and the precise vasculature affected were not collected. Future studies might consider collecting these data.