Walking Energetics, Fatigability, and Fatigue in Older Adults: The Study of Energy and Aging Pilot
Bibliographic record
Abstract
BACKGROUND: Slow gait speed increases morbidity and mortality in older adults. We examined how preferred gait speed is associated with energetic requirements of walking, fatigability, and fatigue. METHODS: Older adults (n = 36, 70-89 years) were categorized as slow or fast walkers based on median 400-m gait speed. We measured VO2peak by graded treadmill exercise test and VO2 during 5-minute treadmill walking tests at standard (0.72 m/s) and preferred gait speeds. Fatigability was assessed with the Situational Fatigue Scale and the Borg rating of perceived exertion at the end of walking tests. Fatigue was assessed by questionnaire. RESULTS: Preferred gait speed over 400 m (range: 0.75-1.58 m/s) averaged 1.34 m/s for fast walkers versus 1.05 m/s for slow walkers (p < .001). VO2peak was 26% lower (18.5 vs 25.1ml/kg/min, p = .001) in slow walkers than fast walkers. To walk at 0.72 m/s, slow walkers used a larger percentage of VO2peak (59% vs 42%, p < .001). To walk at preferred gait speed, slow walkers used more energy per unit distance (0.211 vs 0.186ml/kg/m, p = .047). Slow walkers reported higher rating of perceived exertion during walking and greater overall fatigability on the Situational Fatigue Scale, but no differences in fatigue. CONCLUSIONS: Slow walking was associated with reduced aerobic capacity, greater energetic cost of walking, and greater fatigability. Interventions to improve aerobic capacity or decrease energetic cost of walking may prevent slowing of gait speed and promote mobility in older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".