Elevation of Tumor Necrosis Factor-α and Increased Risk of Recurrent Coronary Events After Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Levels of tumor necrosis factor-alpha (TNF-alpha) increase with acute ischemia. However, whether elevations of TNF-alpha in the stable phase after myocardial ischemia (MI) are associated with increased risk of recurrent coronary events is unknown. METHODS AND RESULTS: A nested case-control design was used to compare TNF-alpha levels obtained an average of 8.9 months after initial MI among 272 participants in the Cholesterol And Recurrent Events (CARE) trial who subsequently developed recurrent nonfatal MI or a fatal cardiovascular event (cases) and from an equal number of age- and sex-matched participants who remained free of these events during follow-up (controls). Overall, TNF-alpha levels were significantly higher among cases than controls (2.84 versus 2.57 pg/mL, P=0.02). The excess risk of recurrent coronary events after MI was predominantly seen among those with the highest levels of TNF-alpha, such that those with levels in excess of 4.17 pg/mL (the 95th percentile of the control distribution) had an approximately 3-fold increase in risk (RR=2.7, 95% CI 1.4 to 5.2, P=0.004). Risk estimates were independent of other risk factors and were similar in subgroup analyses limited to cardiovascular death (RR=2.1) or to recurrent nonfatal MI (RR=3.2). CONCLUSIONS: Plasma concentrations of TNF-alpha are persistently elevated among post-MI patients at increased risk for recurrent coronary events. These data support the hypothesis that a persistent inflammatory instability is present among stable patients at increased vascular risk. Novel therapies designed to attenuate inflammation may thus represent a new direction in the treatment of MI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".