Cognitive Function is a Predictor of the Daily Step Count in Patients With Subacute Stroke With Independent Walking Ability: A Prospective Cohort Study
Bibliographic record
Abstract
Objectives To investigate the physical, cognitive, and psychological factors related to daily step count in patients with subacute stroke. Design Prospective cohort study. Setting A subacute rehabilitation ward with 160 beds. Participants Patients with subacute stroke who could walk independently (N=101). Among the 101 participants enrolled in this study (mean age, 64.5±13.5y), 64.4% (n=65) were men and 69.3% (n=70) were patients with cerebral infarction. Interventions We assessed ambulatory activity using a pedometer placed in the pants pocket on the nonparalyzed side continuously for 7 consecutive days. We also obtained demographic and clinical information and recorded the following measurement scores: Stroke Impairment Assessment Set, FIM, Mini-Mental State Examination (MMSE), Self-Rating Depression Scale, and Apathy Scale. All measurements were collected at admission and discharge. Main Outcome Measures The outcomes assessed were ambulatory activity, motor and sensory functions, functional disability, cognitive function, depressive symptoms, and motivation. Results The median daily steps ambulated at admission and discharge were 5584 steps (interquartile range, 3763-7096 steps) and 5991 steps (interquartile range, 4329-8204 steps), respectively. In the univariate regression analysis, age, sex, serum albumin level, affected side of the brain, and MMSE score at admission were significantly associated with the daily step count at discharge. Multiple regression analysis using these 5 items as independent variables revealed that the MMSE score at admission (reference, 28-30 points; B, −2.07; 95% confidence interval, −3.89 to −0.35; β, −0.22; P =.027) was significantly associated with the daily step count at discharge. Conclusions Cognitive function at admission had a significant association with the daily step count at discharge in patients with subacute stroke who could walk independently.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".