Abstract WMP31: Lifetime Stress, Acute Stress, And Long-term Outcomes After Stroke: A Longitudinal Study
Bibliographic record
Abstract
Background: Stroke is a sudden-onset, unexpected life event over which individuals have little control. These features can make the experience of having a stroke extremely stressful, which may potentiate its debilitating effects. We previously identified short-term associations among lifetime stress/trauma exposure (LSE), post-stroke acute stress (AS), Modified Rankin Scale (mRS) and Fugl-Meyer at 90 days post-stroke. However, their association with long-term stroke-related disability remains unknown. Hypothesis: Higher lifetime trauma and AS symptoms will be associated with poorer long-term disability 1-year post stroke. Method: Multi-site national study of patients admitted for a new stroke. Assessments included Acute Stress Disorder Interview 2-10 days post-stroke, LSE 90 days post-stroke, and Stroke Impact Scale (SIS), modified Rankin Scale (mRS), & Telephone Montreal Cognitive Assessment (tMOCA) at 1-year post-stroke. Structural Equation Modeling examined relationships among LSE, AS, and outcomes, controlling for admission NIHSS score and demographics. Results: Among key predictors and covariates (demographics, acute NIHSS), AS immediately post-stroke was the strongest direct correlate of poorer mRS scores and SIS scores at 1-year ( p s < .001), and the second strongest direct correlate of tMOCA scores at 1-year; higher d90 LSE was directly associated with poorer SIS ( p < .001), and indirectly associated with poorer mRS, SIS, & tMOCA scores at 1-year (all p s < .001) through its association with high AS ( p < .001) at admission. Conclusion: Lifetime stress and stress symptoms in the acute stroke setting are both associated with disability and cognitive impairment 12 months post-stroke; their assessment may be useful to facilitate early identification of high-risk patients and development of interventions that help improve functional and cognitive outcomes after stroke.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".