Age and Marital Status Predict Mild Cognitive Impairment During Acute Coronary Syndrome Admission
Bibliographic record
Abstract
BACKGROUND: Mild cognitive impairment (MCI) has been reported after acute coronary syndrome (ACS), but it is uncertain who is at risk, particularly during inpatient admission. OBJECTIVE: In this study, we aimed to explore the prevalence and cognitive domains affected in MCI during ACS admission and determine factors that identify patients most at risk of MCI. METHODS: Inpatients with ACS were consecutively recruited from 2 tertiary hospital cardiac wards and screened with the Montreal Cognitive Assessment and the Hopkins Verbal Learning Test. Screening included health literacy (Newest Vital Sign), depressive symptoms (Patient Health Questionnaire-9), and physical activity (Physical Activity Scale for the Elderly). Factors associated with MCI were determined using logistic regression. RESULTS: Participants (n = 81) had a mean (SD) age of 63.5 (10.9) years, and 82.7% were male. In total, MCI was identified in 52.5%, 42.5% with 1 screen and 10% with both. Individually, the Montreal Cognitive Assessment identified MCI in 48.1%, and the Hopkins Verbal Learning Test identified MCI in 13.8%. In Montreal Cognitive Assessment screening, the cognitive domains in which participants most frequently did not achieve the maximum points available were delayed recall (81.5%), visuospatial executive function (48.1%), and attention (30.9%). Accounting for education, depression, physical activity, and ACS diagnosis, the likelihood of an MCI positive screen increased by 11% per year of age (odds ratio, 1.11; 95% confidence interval, 1.04-1.18) and by 3.6 times for those who are unmarried/unpartnered (odds ratio, 3.61; 95% confidence interval, 1.09-11.89). CONCLUSION: An estimated half of patients with ACS screen positive for MCI during admission, with single and older patients most at risk. Multiple areas of thinking were affected with potential impact on capacity for learning heart disease management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".