Cognitive Decline Before and After Incident Coronary Events
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that coronary heart disease (CHD) may be associated with accelerated cognitive decline. However, the temporal pattern of cognitive decline before and after incident CHD remains largely unknown. OBJECTIVES: The purpose of this study was to determine the cognitive trajectory before and after incident CHD diagnosis in a national representative cohort age ≥50 years. METHODS: This study included 7,888 participants (mean age 62.1 ± 10.2 years) with no history of stroke or incident stroke during follow-up from the English Longitudinal Study of Ageing. Participants underwent a cognitive assessment at baseline (wave 1, 2002 to 2003), and at least 1 other time point (from wave 2 [2004 to 2005] to wave 8 [2016 to 2017]). Incident CHD was identified as a diagnosis of myocardial infarction and/or angina during follow-up. RESULTS: Incident CHD was associated with accelerated cognitive decline during a median follow-up of 12 years. The annual rate of cognitive decline before CHD diagnosis among individuals who experienced incident CHD was similar to that of participants who remained CHD-free throughout follow-up. No short-term cognitive decline was observed in participants with CHD diagnosis after the event. In the years following CHD diagnosis, global cognition, verbal memory, and temporal orientation scores declined significantly faster than they did before the event, after multivariable adjustment. Sensitivity analyses yielded similar results. CONCLUSIONS: Incident CHD is associated with accelerated cognitive decline after, but not before, the event. Attention should be drawn to the long-term cognitive deterioration related to CHD. Careful monitoring of cognitive function is warranted in CHD patients in the years following the event.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".