Ischemic Modified Albumin Predicts Critical Coronary Artery Disease in Unstable Angina Pectoris and Non-ST-Elevation Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: In this study, whether ischemia modified albumin (IMA) has a role in showing severity or criticality of coronary arteries in patients with unstable angina pectoris (USAP)/non-ST-elevation myocardial infarction (NSTEMI) was assessed. METHODS: A total of 65 patients (40 male (M) and 25 female (F) patients; mean age 59.7 ± 12.1 years) with the initial diagnosis of USAP/NSTEMI were included in this study. The levels of IMA, troponin T, creatine kinase MB (CK-MB), C-reactive protein (CRP), brain natriuretic peptide (BNP), creatinine, lipid panel, and whole blood count were measured from venous blood obtained from each patient within 3 h after the onset of symptoms. A 50% or greater coronary lumen stenosis of any coronary vessel or lateral branch was considered as critical stenosis. The severity of coronary artery disease (CAD) was assessed using the Gensini scoring system. RESULTS: IMA was significantly higher in patients with critical coronary artery stenosis (median, 206 vs. 23; P < 0.001). There was a weak correlation between the Gensini score and IMA; whereas there was a moderate correlation between the Gensini score and BNP levels (r = 0.44, P = 0.02). CONCLUSION: The level of IMA can predict the criticality of CAD; however, it cannot predict the severity of CAD according to Gensini score in patients with USAP/NSTEMI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".