Elevated Free Fatty Acid is Associated with Cardioembolic Stroke Subtype
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Free fatty acids (FFAs), an important energy substrate, have an association with cardiovascular diseases, such as atherosclerosis, myocardial dysfunction and abnormal cardiac rhythm. However, limited reports are available on the association between FFAs and ischemic stroke. We hypothesized that plasma FFA concentration could be associated with an ischemic stroke, emphasizing the relationship between FFA and subtypes of ischemic stroke. METHODS: A cross-sectional study examined the association between FFA concentration and subtypes of stroke and cerebral atherosclerosis from a hospital-based acute stroke registry. RESULTS: Data of 715 stroke patients were analyzed. The concentration of FFA was highest in the cardioembolic stroke subtype compared with the other stroke subtypes. Logistic regression analysis revealed that an increase in FFA concentration was significantly associated with the cardioembolic subtype after the adjustment of covariates. FFA concentration was also higher in patients with atrial fibrillation (AF) than those without AF. According to the presence of atherosclerotic stenosis, no significantly difference of FFA concentration was found for intracranial and extracranial cerebral arterial atherosclerosis. CONCLUSION: Here we report a significant association between fasting FFA concentration and the cardioembolic stroke subtype. AF is suggested as the mediating factor between FFA and the cardioembolic stroke subtype.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".