Platelet-activating factors are associated with cognitive deficits in depressed coronary artery disease patients: a hypothesis-generating study
Bibliographic record
Abstract
BACKGROUND: Patients with coronary artery disease (CAD) are at risk of accelerated cognitive decline, particularly those with major depression. Mechanisms for cognitive deficits associated with CAD, and the effects of depression, remain poorly understood. However, CAD is associated with inflammatory processes that have been linked to neurodegeneration, may contribute to cognitive decline, and are elevated in depression. Platelet-activating factors (PAFs) are emerging as key lipid mediators that may be central to those processes and highly relevant to cognitive decline in CAD. METHODS: This cross-sectional study investigated relationships between various PAFs and cognitive performance in 24 patients with CAD (age, 60.3 ± 9.4; 70.8% male). Analyses were repeated in a subgroup of 15 patients with CAD with major depression (DSM-IV). Cognitive performance was assessed using a standardized battery and summary z scores were calculated based on age, sex, and education norms. Global cognitive performance was the average of domain-specific z scores. Plasma PAF analyses were performed using electrospray ionization mass spectrometry (precursor ion scan). RESULTS: A greater abundance of PAF PC(O-18:0/2:0) was associated with poorer global cognitive performance in patients with CAD (r=-0.45, P=0.03). In the major depressed subgroup, PAF PC(O-18:0/2:0) (r=-0.59, P=0.02) as well as PC(O-16:0/2:0) (r=-0.52, P=0.04), and lyso-PAF PC(O-16:0/0:0) (r=-0.53, P=0.04) were associated with poorer global cognitive performance. A greater abundance of PAF PC(O-19:5/2:0) was associated with better global cognitive performance (r=0.55, P=0.03), suggesting a possible compensatory species. CONCLUSIONS: This study suggests that certain PAFs might be associated with global cognitive performance in patients with CAD, with stronger relationships observed in those with major depression. Confirmation of these preliminary findings is warranted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".