Omentin Is Independently Associated with Stroke Severity and Ipsilateral Carotid Artery Stenosis in Patients with Acute Cerebral Ischemia
Bibliographic record
Abstract
Mounting evidence indicates an association between adipokines and inflammation-related atherosclerosis. Here, we sought to investigate the association of vaspin and omentin with clinical characteristics and outcomes of patients with acute cerebral ischemia (ACI). Consecutive ACI patients were evaluated within 24 h from symptom-onset. Stroke aetiology was classified using TOAST criteria. Adipokines were assayed using quantikine enzyme immunoassay commercially available kits. Stroke severity was assessed by NIHSS-score, and ipsilateral carotid stenosis (≥50% by NASCET criteria) by ultrasound and CT/MR angiography. Major cerebrovascular events were assessed at three months. We included 135 ACI patients (05 (78%) and 30 (22%) with acute ischemic stroke and transient ischemic attack, respectively; mean age ± SD: 59 ± 10 years; 68% men; median NIHSS-score: 3 (IQR:1–7)). Omentin was strongly correlated to admission stroke severity (Spearman rho coefficient: +0.303; p < 0.001). Patients with ipsilateral carotid stenosis had higher omentin levels compared to patients without stenosis (13.3 ± 8.9 ng/mL vs. 9.5 ± 5.5 ng/mL, p = 0.014). Increasing omentin levels were independently associated with higher stroke severity (linear regression coefficient = 0.290; 95%CI: 0.063–0.516; p = 0.002) and ipsilateral carotid stenosis (linear regression coefficient = 3.411; 95%CI: 0.194–6.628; p = 0.038). No association of vaspin with clinical characteristics and outcomes was found. Circulating omentin may represent a biomarker for the presence of atherosclerotic plaque, associated with higher stroke severity in ACI patients.
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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 | 0.001 |
| 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".