Persisting cognitive impairment predicts functional dependence at 1 year after stroke and transient ischemic attack: a longitudinal, cohort study
Bibliographic record
Abstract
OBJECTIVE: Minor stroke or transient ischemic attack (TIA) usually have mild and nondisabling symptoms, and these functional deficits may recover fully e.g., TIA, however, part of them still suffer from cognitive impairment and poor outcomes. We conducted a study to determine the relationship between cognition evaluated by Montreal Cognitive Assessment (MoCA) and poor functional outcomes assessed by the Modified Rankin Scale (mRS) (mRS ≥ 2) and Stroke Impact Scale (SIS)-16(SIS-16<25%). METHODS: The data of this study come from the impairment of cognition and Sleep (ICONS) after acute ischemic stroke or transient ischemic attack in Chinese patients study. A total of 1675 minor stroke patients and TIA patients were finally recruited. Patients' cognition were evaluated by Montreal Cognitive Assessment (MoCA) scale at 2-week (2w), 3 months (3 m) and 1 year(1y). Cognitive impairment (CI) was defined as MoCA score ≤ 22. According to MoCA score, patients were divided into 4 groups: no PSCI group: with MoCA-2w>22 and MoCA-3 m>22; improved PSCI group: with MoCA-2w ≤ 2 and MoCA-3 m>22;delayed PSCI group: MoCA-2w>22 and MoCA-3 m ≤ 22; persisting PSCI group: with MoCA-2w ≤ 22 and MoCA-3 m ≤ 22. RESULTS: A total of 1675 stroke patients were recruited in this study. There were 818 patients (48.84%) who had PSCI at baseline. Of these, 123 patients (15%) had mRS ≥2 at 3 months. The persisting PSCI group was a significant predictor of functional dependence at 3 months and 1 year after stroke and when adjusted for covariates such as gender, age, history of stroke, depression and intracranial atherosclerotic stenosis, stroke subtype and acute infarction type. CONCLUSION: Persisting PSCI increased the risk of poor functional outcome after 3 months and 1 year follow-up. These high-risk individuals should be identified for targeted rehabilitation and counseling to improve longer-term post-stroke outcome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".