Platelet activating factors are associated with depressive symptoms in coronary artery disease patients: a hypothesis-generating study
Bibliographic record
Abstract
INTRODUCTION: Depression is a frequent complication of coronary artery disease (CAD) with an unknown etiology. Platelet activating factor (PAF) lipids, which are associated with CAD, have recently been linked with novel proposed etiopathological mechanisms for depression such as inflammation, oxidative/nitrosative stress, and vascular endothelial dysfunction. METHODS AND RESULTS: This hypothesis-generating study investigated the relationships between various PAF species and depressive symptoms in 26 CAD patients (age: 60.6±9.2 years, 69% male, mean Hamilton Depression Rating Scale [HAM-D] score: 11.8±5.2, HAM-D range: 3-20). Plasma PAF analyses were performed using high performance liquid chromatography electrospray ionization mass spectrometry in precursor ion scan. Significant associations between depressive symptom severity (HAM-D score) and a greater plasma abundance of the PAFs phosphocholine (PC) PC(O-12:0/2:0) (r=0.49, P=0.01), PC(O-14:1/2:0) (r=0.43, P=0.03), PC(O-17:3/2:0) (r=0.44, P=0.04), and PC(O-18:3/2:0) (r=0.50, P=0.01) were observed. Associations between those PAFs and HAM-D score persisted after adjusting for age and sex. CONCLUSION: These preliminary findings support the exploration of the PAF lipidome for depressive symptom biomarkers in CAD patients. Patients were recruited as part of the following clinical trial: NCT00981383.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".