Mortality After High-Risk Myocardial Infarction Over the Last 20 Years: Insights from the VALIANT and PARADISE-MI Trials
Bibliographic record
Abstract
AIMS: The temporal changes in clinical profiles and outcomes of high-risk myocardial infarction survivors enrolled in clinical trials are poorly described. This study compares mortality rates, baseline characteristics, and the prognostic impact of therapies among participants of the VALIANT and PARADISE-MI trials. METHODS AND RESULTS: Exclusively VALIANT participants who matched the inclusion criteria of the PARADISE-MI trial were included in the analysis. Risk of death was compared between trials using Cox regression models. The impact of baseline characteristics and therapies on mortality was estimated by the magnitude reduction of β coefficients using Cox proportional hazards regression models. A total of 9617 VALIANT participants matched the inclusion criteria of the PARADISE-MI trial (n = 5661). All-cause mortality in PARADISE-MI was less than half that in VALIANT (4.2 vs 9.9 per 100 patient-years; hazard ratio [HR] 0.41, 95% confidence interval [CI] 0.37-0.46). This difference was reduced after adjustment for clinical variables but remained substantial (adjusted HR 0.68, 95% CI 0.58-0.80). The most important mediator of this reduction related to covariate adjustment was the use of percutaneous coronary intervention (PCI), accounting for almost half of the attenuation observed. Similar results were found for cardiovascular (CV) death, while no between-trial significant differences were found in the non-CV mortality risk. CONCLUSIONS: Cardiovascular mortality following high-risk myocardial infarction has significantly declined over time, while the risk for non-CV death has remained unchanged. This improvement is partially attributable to advancements in CV care, particularly the use of PCI. Continued efforts to implement guidelines and standardize the quality of care are needed to sustain this positive trend.
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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 | 0.030 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".