Changes in sedentary behavior in the chronic phase following stroke
Bibliographic record
Abstract
BACKGROUND: Sedentary behavior increases risk for cardiovascular diseases. Little is known about sedentary behavior through the chronic phase after stroke. We aimed to describe how long and short bouts of sedentary behavior changed over the first three years after stroke and if cognition at baseline was an independent risk factor for sedentary behavior. METHODS: This is a sub-study of the Norwegian cognitive impairment after stroke (Nor-COAST) study, a multicenter study recruiting patients with acute stroke. Sedentary behavior was monitored with a thigh-worn sensor (ActivPal3®), at three-, 18- and 36-months post stroke. Stroke severity was assessed by National Institutes of Health Stroke Scale (NIHSS) and cognition by Montreal cognitive assessment (MoCA). Mixed model analysis with mean number of sedentary minutes accumulated daily as the dependent variable was repeated for all four zones (<30min, 30-60min, 60-90min, >90min) and for total sedentary time. RESULTS: The number of included participants was 528 (mean age 71.4, NIHSS on day 1, 2.7). The total amount of sedentary time accumulated between 08.00-22.00 increased significantly from about 9.8 hours at three months to 10.1 hours at 36 months post stroke (p=0.002). Patient characteristics associated with prolonged duration of the sedentary bouts and sedentary time were age, high BMI, comorbidities, and impaired physical function. No significant associations between MoCA score and sedentary time were found. CONCLUSION: The participants became increasingly sedentary and had fewer breaks in sedentary time from three to 36 months after stroke. Baseline cognition was not related to later sedentary behavior.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".