Temporal treatments and outcomes following acute myocardial infarction among cancer survivors: A population-based study, 1995-2013.
Bibliographic record
Abstract
10058 Background: There is little contemporary information regarding cardiac care and mortality differences following an acute myocardial infarction (AMI) between cancer survivors (CS) and non-cancer patients (NCP). Methods: All patients with AMI (1995-2013) in Ontario, Canada were identified through administrative databases and stratified into CS (solid or hematologic) and NCP. Those with cancer within 1 year of AMI were excluded. We used inverse probability treatment weight of propensity scores to balance confounders. Coronary intervention use and survival following index AMI were compared between CS and NCP using Modified Poisson and Cox modeling, and their temporal trends were examined. Results: Of 270,089 AMI patients (62.1% men; 87.8% >65 yrs old for CS vs. 56.2% for NCP), 22,907 were CS (prostate 26%, colorectal 17%, breast 16%) and 247,182 NCP. From 1995-2013, coronary interventions usage increased similarly for both groups (Table). The overall 30-day use did not differ between CS and NCP (angiogram unadjusted 36% vs. 50%, adjusted RR 0.96, 95% CI 0.96-1.00, p=.21; percutaneous coronary interventions unadjusted 21% vs. 31%, adjusted RR 0.98, 95% CI 0.94-1.01, p=.21; bypass surgery unadjusted 5% vs. 7%, adjusted RR 0.95, 95% CI 0.87-1.04, p=.25). Unadjusted 30-day mortality following AMI decreased similarly for CS and NCP (Table). However, adjusted 30-day mortality was worse in CS (HR 1.09, 95% CI 1.04-1.15, p<0.001). Over median follow-up of 11 yrs, CS had worse survival than NCP (HR 1.22, 95% CI 1.18-1.26, p<0.0001). CS had higher risk of heart failure than NCP (HR 1.10, 95% CI 1.05-1.15, p<0.0001), while myocardial (re)-infarction and stroke were similar (HR 0.99, 95% CI 0.96-1.02, p=.46; HR 1.09, 95% CI 1.00-1.18, p=.052). Conclusions: Following AMI, coronary intervention use increased and early mortality decreased comparably between CS and NCP over time. However, CS had worse short-term and long-term survival, suggesting that continued emphasis on cancer and cardiovascular care is needed to improve outcomes. [Table: see text]
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".