Changes in Gait Symmetry and Velocity After Stroke: A Cross-Sectional Study From Weeks to Years After Stroke
Bibliographic record
Abstract
BACKGROUND: There is little information about the quality of gait in the years following stroke. Long-term changes in mobility, using global indices of function, suggest a decline well after initial rehabilitation. However, global indices of mobility do not reveal more specific changes in walking competency or underlying gait-specific impairment. OBJECTIVES: The authors used a cross-sectional design with gait-specific measures (velocity and symmetry) to investigate whether deterioration in gait occurs over the long term poststroke. METHODS: Data were abstracted from a standardized database containing clinical assessments and spatiotemporal gait analyses for 171 individuals with stroke. Velocity and 3 expressions of symmetry ratios (swing time, stance time, and step length) were calculated for each individual; they were then assigned to 1 of the 5 following groups: 0 to 3, 3 to 12, 12 to 24, 24 to 48, and >48 months poststroke. RESULTS: Swing time, stance time, and step length symmetry demonstrated a systematic linear trend toward greater asymmetry in groups in the later stages poststroke, whereas velocity, neurological deficit, and lower-extremity (LE) motor impairment did not. CONCLUSIONS: The quality of gait, as measured by spatial and temporal symmetry, appears to worsen in later years. These results suggest a dissociation between quantitative measures of gait, such as velocity versus symmetry, and that these parameters may measure independent features. A longitudinal study is needed to confirm the presence and to interpret the clinical meaning of a long-term decline in specific parameters of poststroke gait.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".