Relationship between Inflammatory Markers and New Cardiovascular Events in Patients with Acute Myocardial Infarction Who Underwent Primary Angioplasty
Bibliographic record
Abstract
INTRODUCTION: The determination of inflammation markers in circulation has enabled an important improvement in the study of cardiovascular diseases. It was tested the hypothesis that non-specific markers such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and fibrinogen may provide prognostic information in patients with acute myocardial infarction with persistent ST-segment elevation (STEMI) undergoing primary angioplasty (PCI). PATIENTS: A cohort of 197 consecutive patients with STEMI undergoing primary PCI was enrolled, evaluating during hospitalization, the peak values of the following markers of inflammation: ESR, CRP and fibrinogen. A telephone follow-up has been made in order to investigate any possible new cardiovascular events after hospital discharge and the procedure performed. RESULTS: Higher values of CRP were statistically associated with adverse future events as composite endpoint and with the single endpoint of death. Furthermore, higher age, presence of hypertension, history of previous cardiovascular events, were statistically significantly associated with cardiac events at follow up. In this group were also overrepresented subjects with anterior myocardial infarction in the anterior localization and with an EF ? 35% at discharge. CONCLUSIONS: CRP appears to be a predictor of future cardiovascular events, confirming that a pro-inflammatory state promotes the progression of atherosclerotic disease and its complications.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".