Independent association and discriminative performance of the timed up and go test for disease activity and functional status in ankylosing spondylitis
摘要
To determine whether Timed Up and Go (TUG) performance is independently associated with patient-reported disease activity and functional status in AS and to assess its ability to identify unacceptable symptom states defined by patient acceptable symptom state (PASS) thresholds.
MethodsIn this cross-sectional study, 108 AS patients were included. Disease activity and functional status were assessed using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Bath Ankylosing Spondylitis Functional Index (BASFI). Functional mobility was evaluated with the TUG test. Unacceptable symptom state was defined using established PASS thresholds (BASDAI ≥ 4.1; BASFI ≥ 3.8). Associations were examined using Pearson/Spearman correlations and multivariable linear regression adjusting for age, sex, and body mass index. Discriminative performance of TUG was evaluated using ROC analyses.
ResultsMean TUG time was 9.12 ± 1.76 s, with BASDAI and BASFI values of 4.19 ± 1.99 and 3.16 ± 2.23. TUG was significantly correlated with BASDAI (r = 0.444, p < 0.001) and BASFI (r = 0.562, p < 0.001). In adjusted models, each 1-s increase in TUG was independently associated with higher BASDAI (0.533 points, 95% CI 0.341–0.726; p < 0.001) and BASFI (0.670 points, 95% CI 0.456–0.884; p < 0.001). ROC analyses showed moderate discrimination for BASDAI-based unacceptable symptom state (AUC = 0.760, 95% CI 0.668–0.852) and good discrimination for BASFI-based unacceptable symptom state (AUC = 0.800, 95% CI 0.714–0.887). Optimal cut-off values were 9.07 s for BASDAI and 9.51 s for BASFI. In an exploratory combined analysis, TUG also discriminated the simultaneous presence of BASDAI- and BASFI-defined unacceptable symptom states (AUC = 0.794, 95% CI 0.703–0.884).
ConclusionTUG shows independent associations with disease activity and functional status in AS and provides meaningful discrimination for identifying unacceptable symptom states defined by PASS thresholds, with stronger discrimination for functional impairment.