Cognitive and Functional Outcome After Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Aneurysmal subarachnoid hemorrhage (aSAH) is a medical emergency characterized by the accumulation of blood in the subarachnoid space surrounding the brain. The acute treatment of aSAH is well documented but less is known about the long-term effects of aSAH on cognition and day-to-day functioning. METHODS: We reviewed all studies in the past 10 years that have focused on the effects of aSAH on cognition and day-to-day functioning. RESULTS: Sixty-one empirical studies examining cognitive and functional outcome in patients with aSAH met inclusion criteria. Survivors of aSAH commonly experience deficits in memory, executive function, and language. These cognitive impairments interact to affect patients' day-to-day functioning, including activities of daily living, instrumental activities of daily living, return to work, and quality of life. Deficits in cognition and day-to-day functioning are further compounded by depression, anxiety, fatigue, and sleep disturbances. CONCLUSIONS: Much remains to be learned about the brain changes underlying cognitive and functional deficits, including the role of diffuse brain damage and secondary complications like vasospasm and elevated intracranial pressure. A consideration of these issues is necessary to obtain a better understanding of how aSAH affects cognition and day-to-day functioning in the long-term.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".