Blood Plasma Resistin and Atrial Fibrillation in Patients With Cardiovascular Disease
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) affects quality of life and prognosis of patients with cardiovascular disease. Resistin plays an important role in inflammatory response to internal and external factors. The aim of this study is to evaluate the association between resistin and permanent AF (PAF) in patients with cardiovascular disease. METHODS: In our study, we included 146 patients with cardiovascular disease. Plasma resistin concentrations and demographic characteristics of patients were recorded. The patients were divided in two groups: 118 patients without a history of PAF (NonAF group), and 28 patients with a history of PAF (AF group). Association of resistin with PAF and other variables was examined by parametric and non-parametric tests, and multivariable linear and univariable logistic regression analysis. RESULTS: No differences of demographic characteristics (gender, age and body mass index (BMI)) between two groups were observed (P > 0.05). Higher median levels of resistin were observed in group AF than in group NonAF (6.90 ng/mL vs. 5.83 ng/mL, P = 0.03). Multivariate linear regression analysis (adjusted to gender, age, BMI, hypertension, diabetes mellitus, coronary artery disease, and mitral valve disease) showed that resistin was associated with PAF (β = 0.79, 95% confidence interval (CI): 0.08 to 1.51, P = 0.03). CONCLUSIONS: Our analysis showed that plasma resistin was associated with PAF, and resistin concentration was higher in patients with AF compared to those without AF.
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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".