Longitudinal evaluation of cognition after stroke – A systematic scoping review
Bibliographic record
Abstract
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221735Background: Cognitive impairment affects up to 80 percent of the stroke population, however, both the available evidence about post-stroke cognition and the measures used to evaluate it longitudinally have not been well described. The aims of this systematic scoping review were: to identify and characterize studies evaluating cognition longitudinally after stroke; to summarize the cognitive instruments used and the domains they target; and to organize cognitive domains assessed using the International Classification of Functioning, Disability and Health (ICF). Methods: We used a systematic scoping approach to search for peer-reviewed articles involving adults with stroke that evaluated cognition longitudinally. Screening of titles, abstracts, and full reports was completed independently by two reviewers, across six electronic databases (PubMed, PsycInfo, Medline, Cinahl Plus, Embase, and Web of Science). Cognitive domains were mapped to an ICF function independently by the same two reviewers, using a previously tested, standardized approach. Results: A total of 5,540 records were found; 257 were included, representing a total pooled sample of 120,860 stroke survivors. Of these studies, 200 (78%) provided specific cognitive outcomes from the longitudinal evaluations, 57 (22%) reported model predictions, and 77 (30%) included interventions. Cognition was evaluated with 356 unique instruments, targeting 95 distinct cognitive domains, and 17 mental functions from the ICF. The Mini-Mental State Examination was the most frequently used instrument (117 reports, 46%). Other tools used longitudinally were the Trail Making Test (17% of reports), tests of verbal fluency (14%), the Functional Independence Measure (14%), the Montreal Cognitive Assessment (13%), the Digit Span (11%), and the Stroop test (10%). Global cognition was evaluated in 170 reports (66%), followed by higher-level cognitive functioning (29%), memory (28%), language (21%), attention (21%), and perceptual skills (14%). Studies using functional (or performance-based) cognitive assessments over time were scarce (< 1%). Conclusion: Our findings indicate that whilst there is a substantial number of studies available that report longitudinal evaluations of cognition after stroke, there is large variability in the measures used and the cognitive domains they target. Nonetheless, the available data for evaluation of cognition over time after stroke can be organized and described systematically.
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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 | 0.034 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.021 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".