Effect of prior revascularization on outcome following percutaneous coronary intervention. NHLBI Dynamic Registry
Bibliographic record
Abstract
AIMS: An increasing number of patients undergoing percutaneous coronary intervention (PCI) have experienced previous revascularization procedures. Their outcome after PCI has seldom been compared to that of patients without prior procedures. This study investigates which elements of prior revascularization affect in-hospital and long-term outcome after PCI. METHODS AND RESULTS: Baseline characteristics as well as in-hospital and 1-year outcomes were compared in 4010 consecutive patients undergoing PCI in the NHLBI Dynamic Registry, categorized by type of prior procedure. In-hospital mortality was lowest and procedural success highest among patients with prior PCI only. Patients with prior coronary artery bypass grafting (CABG) had higher rates for the combined endpoint of death and myocardial infarction (MI) at 1 year compared to patients with no prior procedures. However, in multivariate regression analysis adjusting for potential confounders, neither prior PCI nor prior CABG were independent predictors of death or death/MI at 1 year. Patients with prior procedure had higher rates for repeat PCI and patients with prior PCI had higher rates for CABG during the year following the index procedures. These associations persisted after adjustment for potential confounders. Finally, patients with prior procedures had a higher prevalence of angina at 1 year. CONCLUSIONS: Due to adverse baseline characteristics, patients with prior CABG have higher rates for death/MI during the first year after PCI and both groups of patients with prior procedures have higher revascularization rates. However, only the associations with repeat revascularization persist after adjustment for baseline and procedural factors.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".