Cognitive impairment is differentially associated with depression and anxiety at six-months post-stroke
Bibliographic record
Abstract
Abstract Objective This study investigated the associations between general cognitive impairment and domain specific cognitive impairment with post-stroke depression and anxiety at six-months post-stroke. Methods Participants were a subset of 437 stroke patients from the OCS-CARE study who were followed up at a 6 months post-stroke assessment. Depression and anxiety symptoms were assessed by the Hospital Anxiety and Depression Scale sub-scales. General cognitive impairment was assessed using the Montreal Cognitive Assessment and stroke-specific cognitive domain impairments was assessed using the Oxford Cognitive Screen. Multivariable linear regression was used to examine the associations between cognition and depression/anxiety symptoms, controlling for acute stroke severity and ADL impairment, age, sex, education, and co-occurring post-stroke depression/anxiety. Results Six-month post-stroke depression was associated with six-month impairment on the MoCA (beta [ b ] =0.96, standard error [ SE ] =0.31, p =0.006), and all individual domains assessed by the OCS including spatial attention ( b =0.67, SE =0.33, p =0.041), executive function ( b =1.37, SE =0.47, p =0.004), language processing ( b =0.87, SE =0.38, p =0.028), memory ( b =0.76, SE =0.37, p =0.040), number processing ( b =1.13, SE =0.40, p =0.005), and praxis ( b =1.16, SE =0.49, p =0.028). Post-stroke anxiety was associated with impairment on the MoCA ( b =1.47, SE =0.42, p =0.001), and spatial attention ( b =1.25, SE =0.45, p =0.006), but these associations did not remain significant after controlling for co-occurring post-stroke depression. Conclusion The different profiles of associations between cognitive impairment and post-stroke depression and anxiety suggest that cognitive impairment is highly related to depressive symptomatology, but associations observed between cognitive impairment and anxiety may actually be the result of co-morbid post stroke depression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".