Delirium in Acute Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Delirium is common in the early stage after hospitalization for an acute stroke. We conducted a systematic review and meta-analysis to evaluate the outcomes of acute stroke patients with delirium. METHODS: We searched MEDLINE, EMBASE, CINAHL, Cochrane Library databases, and PsychInfo for relevant articles published in English up to September 2011. We included observational studies for review. Two reviewers independently assessed studies to determine eligibility, validity, and quality. The primary outcome was inpatient mortality and secondary outcomes were mortality at 12 months, institutionalization, and length of hospital stay. RESULTS: Among 78 eligible studies, 10 studies (n=2004 patients) met the inclusion criteria. Stroke patients with delirium had higher inpatient mortality (OR, 4.71; 95% CI, 1.85-11.96) and mortality at 12 months (OR, 4.91; 95% CI, 3.18-7.6) compared to nondelirious patients. Patients with delirium also tended to stay longer in hospital compared to those who did not have delirium (mean difference, 9.39 days; 95% CI, 6.67-12.11) and were more likely to be discharged to a nursing homes or other institutions (OR, 3.39; 95% CI, 2.21-5.21). CONCLUSIONS: Stroke patients with development of delirium have unfavorable outcomes, particularly higher mortality, longer hospitalizations, and a greater degree of dependence after discharge. Early recognition and prevention of delirium may improve outcomes in stroke patients.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".