Authors
Jeong Soo Kim
Published in
Gait & posture. Volume 130. Pages 110264. Jun 18, 2026. Epub Jun 18, 2026.
Abstract
Independent outdoor ambulation is a key rehabilitation goal after stroke, but it is unclear whether instrumented gait analysis adds prognostic information beyond conventional clinical measures.
Do spatiotemporal gait parameters provide incremental predictive value beyond clinical assessments-independent of admission Functional Ambulation Category (FAC)-for outdoor ambulation in subacute stroke patients?
We retrospectively analysed 137 subacute stroke inpatients with admission FAC 2-3 (89 outdoor, 48 indoor-only ambulators at discharge); one patient was excluded for an implausible step time. Admission FAC was excluded from candidate predictors to avoid overlap with the outcome. Hierarchical logistic regression compared a clinical model (Motricity Index [MI], time since onset) with one adding GAITRite-derived spatiotemporal parameters, using likelihood-ratio and DeLong tests with Firth-penalised sensitivity analysis.
Model 1 achieved near-perfect discrimination (AUC = 0.995, 95% CI 0.984-0.999). Adding affected-side single- and double-support percentages (Model 2) significantly improved fit (likelihood-ratio χ² = 9.39, p = 0.009; AUC = 0.998); the AUC difference was not significant by DeLong's test (p = 0.262). Firth-penalised analyses produced concordant, stable coefficients. MI and gait velocity were the strongest single predictors (both AUC = 0.981); bootstrap optimism was ≤ 0.002.
Beyond a near-perfect clinical model, affected-side support-phase parameters add statistically detectable model information (improved fit and calibration) rather than a clinically decisive gain in discrimination, which is constrained by a ceiling effect. Their value is best understood as quantifying paretic-limb weight-bearing and balance-related gait quality not captured by bedside scales, in subacute stroke inpatients with admission FAC 2-3. The Youden cut-offs (MI ≥ 40, velocity ≥ 32.1 cm/s, single support ≥ 29.7%) are hypothesis-generating and require external validation before clinical use.
PMID:
42335499
Bibliographic data and abstract were imported from PubMed on 24 Jun 2026.
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