Early Mobilization After Stroke Is Not Associated With Cognitive Outcome
Bibliographic record
Abstract
Background and Purpose- We aimed to determine whether early mobilization after stroke affects subsequent cognitive function. Methods- AVERT (A Very Early Rehabilitation Trial) was an international, 56-site, phase 3 randomized controlled trial, conducted from 2006 to 2015. Participants were included if they were aged 18+, presented within 24 hours of stroke, and satisfied physiological limits for blood pressure, heart rate, and temperature. Participants were randomized to receive either usual stroke unit care or very early and more frequent mobilization in addition to usual stroke unit care. The Montreal Cognitive Assessment, scored 0 to 30, was introduced as a 3-month outcome during 2008. Results- Of the 2104 patients included in AVERT, 317 were assessed before the Montreal Cognitive Assessment's introduction. Of the remaining 1787, 1189 (66.5%) had complete Montreal Cognitive Assessment data, 456 (25.5%) had partially or completely missing data, 136 (7.6%) had died, and 6 (0.3%) were lost to follow-up. In surviving participants with complete data, adjusting for age and stroke severity, total Montreal Cognitive Assessment score was no different in the intervention (n=595; median, 23; interquartile range, 19-26; mean, 21.9; SD, 5.9) and usual care (n=594; median, 23; interquartile range, 19-26; mean, 21.8; SD, 5.9) groups ( P=0.68). Conclusions- Exposure to earlier and more frequent mobilization in the acute stage of stroke does not influence cognitive outcome at 3 months. This stands in contrast to the primary outcome from AVERT (modified Rankin Scale), where the intervention group had less favorable outcomes than controls. Clinical Trial Registration- URL: https://www.anzctr.org.au . Unique identifier: ACTRN12606000185561.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".