Stroke rehabilitation evidence and comorbidity: a systematic scoping review of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Most strokes occur in the context of other medical diagnoses. Currently, stroke rehabilitation evidence reviews have not synthesized or presented evidence with a focus on comorbidities and correspondingly may not align with current patient population. The purpose of this review was to determine the extent and nature of randomized controlled trial stroke rehabilitation evidence that included patients with multimorbidity. METHODS: A systematic scoping review was conducted. Electronic databases were searched using a combination of terms related to "stroke" and "rehabilitation." Selection criteria captured inpatient rehabilitation studies. Methods were modified to account for the amount of literature, classified by study design, and randomized controlled trials (RCTs) were abstracted. RESULTS: The database search yielded 10771 unique articles. Screening resulted in 428 included RCTs. Three studies explicitly included patients with a comorbid condition. Fifteen percent of articles did not specify additional conditions that were excluded. Impaired cognition was the most commonly excluded condition. Approximately 37% of articles excluded patients who had experienced a previous stroke. Twenty-four percent excluded patients one or more Charlson Index condition, and 83% excluded patients with at least one other medical condition. CONCLUSIONS: This review represents a first attempt to map literature on stroke rehabilitation related to co/multimorbidity and identify gaps in existing research. Existing evidence on stroke rehabilitation often excluded individuals with comorbidities. This is problematic as the evidence that is used to generate clinical guidelines may not match the patient typically seen in practice. The use of alternate research methods are therefore needed for studying the care of individuals with stroke and multimorbidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.244 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".