Increased endothelin-1 levels in coronary artery disease with diabetes mellitus in an Indonesian population
Bibliographic record
Abstract
Diabetes mellitus (DM) increases risk of coronary artery disease (CAD). Endothelin-1 (ET-1) is a potential biomarker of endothelial dysfunction. This study aimed to evaluate ET-1 level in CAD patients and its relationship with DM. The cross-sectional design included subjects with angiographically proven CAD and controls among Indonesian. DM was defined by medical history and anti-diabetics use. Serum ET-1 level was measured in both subject groups. We recruited 305 subjects, 183 CAD patients and 122 controls. CAD subjects had higher percentage of males, DM, hypertension, dyslipidemia, smoking, family history of cardiovascular disease, and obesity. ET-1 level was significantly higher in CAD than in controls (2.44 ± 1.49 pg/mL vs. 1.76 ± 0.83 pg/mL; p < 0.001). Increased ET-1 level was significantly associated with DM and dyslipidemia. The highest ET-1 level was observed in CAD with DM, followed by CAD non-DM (2.79 ± 1.63 pg/mL vs. 2.29 ± 1.40 pg/mL; p = 0.023). Among controls, ET-1 level was the lowest in non-DM subjects. Female CAD had higher proportion of DM; however, ET-1 level was similar to male CAD with DM. In conclusion, an increased ET-1 level was significantly associated with DM in patients with CAD. Further research should investigate the potential role of ET-1 receptor antagonists in the secondary prevention of CAD with DM.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".