Anxiety and Depression in Stroke: An Evaluation of these Psychopathologies on Outcomes of Stroke Type using the National Inpatient Sample
Bibliographic record
Abstract
BACKGROUND: Anxiety and depression have been reported to complicate the course of stroke. This study evaluated the association of anxiety and depression independently on ischemic vs non-ischemic stroke. METHODS: A cross-sectional survey of 4,983,807 admissions for acute stroke from 1994 to 2013 in the National Inpatient Sample compared stroke patients with depression and anxiety to stroke patients with no psychiatric comorbidities. The database was operationalized based on the inclusion/exclusion criteria approved by the Southern Illinois University School of Medicine Institutional Review Board. RESULTS: Patients with anxiety and depression were more likely to have an ischemic stroke (OR 1.64; 95% CI, 1.61 to 1.68) vs a non-ischemic stroke (OR 1.25; 95% CI, 1.23 to 1.27). Inpatient mortality was significantly less in both the depression and anxiety groups compared to the control group. CONCLUSIONS: Psychiatric disorders (anxiety and depression) may increase the risk of ischemic stroke; however, depressed and anxiety patients with ischemic stroke were less likely to die from stroke. Further well-designed studies are necessary to explore these findings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".