Effect of primary percutaneous coronary intervention on in-hospital outcomes among active cancer patients presenting with ST-elevation myocardial infarction: a propensity score matching analysis
Bibliographic record
Abstract
AIMS: Primary percutaneous coronary intervention (pPCI) is the gold standard, guideline-recommended revascularization strategy in patients presenting with ST-elevation myocardial infarction (STEMI). However, there are limited data on its use and effectiveness among patients with active cancer presenting with STEMI. METHODS AND RESULTS: All STEMI hospitalizations between 2004 and 2015 from the National Inpatient Sample were retrospectively analysed, stratified by cancer type. Propensity score matching was performed to estimate the average treatment effect of pPCI in each cancer on in-hospital adverse events, including major adverse cardiovascular and cerebrovascular events (MACCE) and its individual components, and compare treatment effect between cancer and non-cancer patients. Out of 1 870 815 patients with STEMI, 38 932 (2.1%) had a current cancer diagnosis [haematological: 11 251 (28.9% of all cancers); breast: 4675 (12.0%); lung: 9538 (24.5%); colon: 3749 (9.6%); prostate: 9719 (25.0%)]. Patients with cancer received pPCI less commonly than those without cancer (from 54.2% for lung cancer to 70.6% for haematological vs. 82.3% in no cancer). Performance of pPCI was strongly associated with lower adjusted probabilities of MACCE and all-cause mortality in the cancer groups compared with the no cancer group. There was no significant difference in estimated average pPCI treatment effect between the cancer groups and non-cancer group. CONCLUSION: Primary percutaneous coronary intervention is underutilized in STEMI patients with current cancer despite its significantly lower associated rates of in-hospital all-cause mortality and MACCE that is comparable to patients without cancer. Further work is required to assess the long-term benefit and safety of pPCI in this high-risk group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".