Is Stroke History Reliably Reported by Elderly with Cognitive Impairment? A Community-Based Study
Bibliographic record
Abstract
BACKGROUND/AIMS: Self-reported history of stroke has been questioned in the elderly due to the high prevalence of cognitive impairment. We tested the validity of response to a stroke questionnaire versus clinical diagnosis of stroke among elderly people with and without cognitive impairment. METHODS: Community-dwelling participants to the phase 1 Canadian Study of Health and Aging were screened for self-reported stroke. Physician-diagnosed stroke was set as the gold standard. The positive predictive value (PPV), sensitivity and specificity were determined. RESULTS: 1,536/ 1,659 (93%) participants aged 65 years and over had stroke information from both sources. Among stroke positive responders, the PPV was 81% overall: 76% for cognitively normal, 84% for cognitively impairment with no dementia (CIND), and 82% for demented. Among stroke diagnosed by physicians, history of stroke was reported by 38% cognitively normal, 54% CIND, and 55% demented. The specificity was over 97% in all cognitive categories. CONCLUSION: Among community-dwelling elderly people, any cognitive impairment did not imply inaccurate self-reported history of stroke. High prevalence of stroke and frequent contacts with health services among cognitively-impaired elderly may increase the awareness of stroke symptoms and signs. Stroke increases the risk of developing dementia in both cognitively normal and CIND, and efforts to accomplish stroke prevention are justified, especially in these categories.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".