Association of Fibrinogen with Severity of Stable Coronary Artery Disease in Patients with Type 2 Diabetic Mellitus
Bibliographic record
Abstract
BACKGROUND: Some studies have suggested a relation of plasma fibrinogen to the severity of coronary artery disease (CAD). However, whether plasma fibrinogen can predict the presence and severity of CAD in patients with diabetes mellitus has not been determined. METHODS: A total of consecutive 373 diabetic patients with typical angina pectoris who received coronary angiography were enrolled and classified into three groups by tertiles of Gensini score (GS, low group <8; intermediate group 8~28; high group >28). The relationship between fibrinogen and GS was evaluated. RESULTS: There were correlations of fibrinogen with hemoglobin A1c, C-reactive protein, and GS (r = 0.17, r = 0.52, and r = 0.21, resp.; all P < 0.001). Area under the receivers operating characteristic curve of fibrinogen was 0.62 (95% CI 0.56-0.68, P < 0.001) for predicting a high GS. Multivariate analysis suggested that plasma fibrinogen was an independent predictor of a high GS for diabetic patients (OR = 1.40, 95% CI 1.04-1.88, and P = 0.026) after adjusting for traditional risk factors of CAD. CONCLUSIONS: The present data indicated that plasma fibrinogen, a readily measurable systematic inflammatory marker, appeared to be an independent predictor for the severity of CAD in diabetic 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 | 0.001 | 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) | 0.001 | 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".