Cognitive Decline in Older Patients With Non‐ST Elevation Acute Coronary Syndrome
Bibliographic record
Abstract
Background Dementia is a growing health burden of an aging population. This study aims to evaluate the prevalence of cognitive impairment and the predictors of cognitive decline at 1 year in older patients with non-ST-elevation acute coronary syndrome undergoing invasive care. Methods and Results Older patients with non-ST-elevation acute coronary syndrome were recruited into the ICON1 study. Cognition was evaluated using Montreal Cognitive Assessment. The composite major adverse cardiovascular events comprised death, myocardial infarction, unplanned revascularization, stroke, and significant bleeding at 1 year. Of 298 patients, 271 had cognitive assessment at baseline, and 211 (78%) had follow-up Montreal Cognitive Assessment at 1 year. Mean age was 80.5±4.8 years. There was a high prevalence (n=130, 48.0%) of undiagnosed cognitive impairment (Montreal Cognitive Assessment score <26) at baseline. Cognitive impairment patients were more likely to reach major adverse cardiovascular events by Kaplan-Meier analysis ( P=0.047). Seventy-four patients (35.1%) experienced cognitive decline (Montreal Cognitive Assessment score drop by ≥2 points) at 1 year. Recurrent myocardial infarction was independently associated with cognitive decline at 1 year (odds ratio 3.19, 95% confidence interval 1.18-8.63, P=0.02) after adjustment for age and sex. Conclusions In older patients undergoing invasive management of non-ST-elevation acute coronary syndrome, there is a high prevalence of undiagnosed cognitive impairment at baseline. Recurrent myocardial infarction is independently associated with cognitive decline at 1 year. Clinical Trial Registration URL: http://www.clinicaltrials.gov . Unique identifier: NCT01933581.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".