Primary Coronary Intervention in Octogenarians and Nonagenarians With ST-Segment Elevation Myocardial Infarction: A Canadian Single-Center Perspective
Bibliographic record
Abstract
The proportion of individuals >80 years of age constitute an increasing proportion of patients who present with ST-segment elevation myocardial infarction (STEMI). The objective of this study is to evaluate in-hospital outcomes and 1-year survival of very elderly patients who present with an STEMI and undergo primary percutaneous coronary intervention (pPCI). Between 2009 and 2015, individuals >80 years of age (very elderly patients) with an STEMI presenting at a single tertiary Canadian care center were included in the study. A random sample of 100 individuals aged 65 to 69 years over the same time period were selected as a control group. A total of 284 patients were included in the study population including 100 controls, 164 octogenarians, and 20 nonagenarians. Of total, 1661 pPCIs occurred during this study period with the very elderly population (>80 years) comprising 11.1% of the total pPCIs. Compared with controls, individuals aged >80 are more likely to have a delay in treatment with increased rates of bleeding, acute kidney injury, rehospitalization, and a trend toward longer hospital stays following pPCI for STEMI. Although in-hospital and 1-year mortality were similar between both cohorts >80 years of age with STEMI, their overall survival was reduced compared with controls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".