The relationship of acute delirium with cognitive and psychiatric symptoms after stroke: a longitudinal study
Bibliographic record
Abstract
OBJECTIVE: Delirium, a common complication after stroke, is often overlooked, and long-term consequences are poorly understood. This study aims to explore whether delirium in the acute phase of stroke predicts cognitive and psychiatric symptoms three, 18 and 36 months later. METHOD: As part of the Norwegian Cognitive Impairment After Stroke Study (Nor-COAST), 139 hospitalized stroke patients (49% women, mean (SD) age: 71.4 (13.4) years; mean (SD) National Institutes of Health Stroke Scale (NIHSS) 3.0 (4.0)) were screened for delirium with the Confusion Assessment Method (CAM). Global cognition was measured with the Montreal Cognitive Assessment (MoCA), while psychiatric symptoms were measured using the Hospital Anxiety and Depression Scale (HADS) and the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Data was analyzed using mixed-model linear regression, adjusting for age, gender, education, NIHSS score at baseline and premorbid dementia. RESULTS: Thirteen patients met the criteria for delirium. Patients with delirium had lower MoCA scores compared to non-delirious patients, with the largest between-group difference found at 18 months (Mean (SE): 20.8 (1.4) versus (25.1 (0.4)). Delirium was associated with higher NPI-Q scores at 3 months (Mean (SE): 2.4 (0.6) versus 0.8 (0.1)), and higher HADS anxiety scores at 18 and 36 months, with the largest difference found at 36 months (Mean (SE): 6.2 (1.3) versus 2.2 (0.3)). CONCLUSIONS: Suffering a delirium in the acute phase of stroke predicted more cognitive and psychiatric symptoms at follow-up, compared to non-delirious patients. Preventing and treating delirium may be important for decreasing the burden of post-stroke disability.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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".