Investigating the Long-Term Cognitive Impairments of Stroke: A Systematic Review
Bibliographic record
Abstract
Stroke is a major cause of long-term morbidity, a cognitive impairment that affects instrumental activities of daily living and quality of life for survivors and caregivers. It is imperative that patients with the risk of Post-stroke cognitive impairment (PSCI) are identified early and interventions instituted as soon as possible. This study aims to demystify cognitive domains affected after a stroke, discover features on imaging that suggest the likelihood for the development of PSCI, assess survivors’ quality of life, and examine the impact of non-pharmacological and pharmacological interventions on Post-stroke Cognitive impairment (PSCI). Using the PRISMA 2020 guideline, three databases were used: PubMed, Cochrane, and Google Scholar. 1,773 articles were identified; however, after applying inclusion and exclusion criteria and other filters, 13 articles were used for this study: 4 being observational studies, three systematic reviews and meta-analyses, and two narrative literature. The characteristics of each article that passed the quality check were analyzed in tabular form, and the discussion followed afterward. This study found that at three months following a stroke, survivors’ Montreal Cognitive Assessment (MoCA) improves. It also sheds more light on the various cognitive assessment tools available and the many nonpharmacologic interventions available to post-stroke victims and caregivers as more investigations are still being carried out to ascertain the usefulness of pharmacological intervention.
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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 | 0.007 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".