Cognitive impairment predicts engagement in inpatient stroke rehabilitation
Bibliographic record
Abstract
Patient engagement during inpatient rehabilitation is an important component of rehabilitation therapy, as lower levels of engagement are associated with poorer outcomes. Cognitive deficits may impact patient engagement during inpatient stroke rehabilitation. Here, we assess whether patient performance on the cognitive tasks of the 30-min National Institute of Neurologic Disorders and Stroke - Canadian Stroke Network (NINDS-CSN) screening battery predicts engagement in inpatient stroke rehabilitation. Prospective data from 110 participants completing inpatient stroke rehabilitation at an academic medical center were utilized for the present analyses. Cognitive functioning was assessed at inpatient stroke rehabilitation admission using the NINDS-CSN cognitive battery. Patient engagement was evaluated at discharge from an inpatient rehabilitation unit using the Hopkins Rehabilitation Engagement Rating Scale. The results demonstrate that the NINDS-CSN cognitive battery, specifically subtests measuring executive functioning, attention and processing speed, predicts patient engagement in inpatient stroke rehabilitation. Cognitively impaired patients undergoing rehabilitation may benefit from modifications and interventions to increase engagement and improve functional outcomes.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".