Do functional walk tests reflect cardiorespiratory fitness in sub-acute stroke?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The Six-Minute Walk Test (6MWT) has been employed as a measure of functional capacity, but its relationship to cardiorespiratory fitness in stroke is not well established. Gait speed measured over short distances is commonly used as an index of walking competency following stroke. We evaluated the relationship between the 6MWT, aerobic fitness (VO2peak) and walking competency in sub-acute stroke. METHODS: Thirty-six individuals (mean age +/- SD, 64.6 +/- 14.4 years; time post-stroke 16.2 +/- 13.3 days) were evaluated using the 6MWT (distance, speed, heart rate), a maximal exercise test (VO2peak, heart rate, exercise test duration), and walking competency using a five meter walk (speed, symmetry ratio). Correlation analyses were used to examine the relationships between these outcomes. RESULTS: There was a strong correlation between the 6MWT and five meter walk velocity for preferred (r = 0.79) and fast (r = 0.82) speed (p < 0.001). On average, the 6MWT speed was faster than the preferred gait speed (94.9 cm/s vs. 83.8 cm/s, p = 0.003), but slower than the fast-paced walk (115.1 cm/s, p < 0.001). There was significant though more moderate association between 6MWT distance and VO2peak (r = 0.56, p < 0.001) and exercise test duration (r = 0.60, p < 0.001). CONCLUSION: The speed selected during the 6MWT was strongly related to the velocities selected during the five meter walk distance (intermediate to the selected preferred and fast speeds). Although the 6MWT may be challenging to the cardiorespiratory system, it appears to be more strongly influenced by potential limits to walking speed rather than cardiorespiratory capacity. As a result, this test is not, by itself, an adequate measure of aerobic fitness early after stroke.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".