Association between Stroke and Cognitive Decline in Community Dwelling Older and Oldest People: The SONIC Study
Bibliographic record
Abstract
Abstract Background Increasing in the older people and a decline in mortality after stroke, the rate of post-stroke cognitive decline has increased. The relationship between risk factors and post-stroke cognitive decline in dwelling old and oldest people who living in the community especially with asymptomatic stroke have to be elucidated. Therefore, the aim of this study is to investigate the association between stroke and cognitive decline during three years in community dwelling older and oldest people.Methods This study was longitudinal study with a 3-year follow-up in urban and rural areas of Japan. The participants were 1,333 community dwelling older and oldest people (70 years old = 675, 80 years old = 589, and 90 years old = 69). Data collected included basic data (age, sex, and history of stroke), vascular risk factors (hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, and current smoking), and social factors (educational level, frequency of going outdoors, and long-term care (LTC) service used). The Japanese version of the Montreal Cognitive Assessment (MoCA-J) was used for cognitive assessment, and a decline of ≥ 2 points was defined as cognitive decline. Multiple logistic regression analysis was used to investigate the association between stroke and other risk factors with cognitive decline during a 3-year follow-up.Results Rates of cognitive decline increased in advanced ages, equaling 33.3, 39.4, and 66.7% in those aged 70, 80, and 90 years old, respectively. The fit of the hypothesized model by multiple logistic regression showed that a history of stroke, advanced age, and greater MoCA-J score at the baseline were important risk factors, while the presence of dyslipidemia and a higher educational level were protective factors that were significantly correlated with cognitive decline during the 3-year follow-up.Conclusions The cognitive decline after the 3-year follow-up was influenced by the history of stroke, advanced age, and greater MoCA-J score at the baseline, but protective factors were the presence of dyslipidemia and a higher educational level. Therefore, these factors are considered important and should be taken into consideration when searching for creative solutions to prevent cognitive decline after stroke in community dwelling older and oldest people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".