Being married/having an intimate partner/being has protective effects for mild cognitive impairment in acute coronary syndrome patients
Bibliographic record
Abstract
Abstract Background Cardiovascular disease (CVD) is a leading cause of mortality and morbidity and is known to contribute to cognitive impairment, a condition common in CVD patients. Cognitive impairment (CI) is important to detect, manage and accommodate because it limits the capacity of CVD patients to learn about secondary prevention and engage in appropriate self-care including lifestyle change. Purpose Therefore this study aimed to determine the prevalence and predictors of cognitive impairment in acute coronary syndrome (ACS) patients during hospital admission. Methods ACS (myocardial infarction, unstable angina) inpatients (n=81) who did not have a neurocognitive diagnosis were recruited to a prospective descriptive study in 2019. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) and the Hopkins Verbal Learning Test (HVLT). Results The sample had an age mean of 63.49±10.86 (range 40–89) years, was mostly male (82.7%) and 50.6% were university educated. MI occurred in 56.8%, equally STEMI (28.4%) and nSTEMI (28.4%) with 70.4% treated by coronary intervention. The mean education adjusted MOCA score was 25.73±3.05 (range 18–31) and 48.1% were classified as having mild CI (18–26). The domain with the worst performance was delayed recall/memory domain at mean 2.58±1.77 (of potential 0–5 points). The mean unadjusted recall score on HVLT was 19.56±6.18 (range 0–32), the mean z-score −0.69±1.21 (range −4.59–1.87) and 40.7% were classified as having mild CI (age and education adjusted Z-score ≥−1). Mild CI was classified by both MOCA and HVLT (both adjusted) in 24.7%. Patients classified as having mild CI (MOCA) were significantly older (66.87 versus 60.36 years, p=0.006) and less likely and to be married or have an intimate partner (21% versus 32% p=0.039). When all factors were taken into account using multiple linear regression, higher MOCA scores in patients who were married/partnered (B=1.6) and lower scores with advancing age (B=−0.08). Conclusions Mild CI and decreased delayed recall is prevalent in ACS patients and patient education strategies need to be accommodate this. Being married/partnered may have protective effects, therefore additional support may need to be directed to single patients. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Heart Foundation of Australia Vanguard Award
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".