Percutaneous Coronary Intervention Outcomes in Patients With Prior Thoracic Radiation Therapy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Thoracic radiation predisposes patients to accelerated coronary artery disease. There is a paucity of data in both short-term and long-term outcomes following revascularization in patients who have undergone thoracic radiation. Methods: We performed a search of the Medline, Cochrane, and Scopus databases for studies that compared outcomes in cancer patients who have undergone thoracic radiation and percutaneous coronary intervention (PCI). The primary outcome of our meta-analysis was all-cause mortality. Secondary outcomes included cardiac mortality, myocardial infarction (MI), and restenosis. Results: The analysis included four observational studies with a total of 13,941 patients for the primary outcome of all-cause mortality. There were a total of 1,322 patients analyzed for cardiac mortality, 13,103 for MI, and 10,530 for restenosis. The longest follow-up for the primary outcome was 16 years. There was statistically significant higher risk of all-cause mortality in patients who underwent thoracic radiation (risk ratio (RR): 1.29, 95% confidence interval (CI): 1.08 - 1.54, P = 0.004). There was no statistically significant difference in cardiac mortality (RR: 1.15, 95% CI: 0.83 - 1.61, P = 0.40), MI (RR: 1.01, 95% CI: 0.20 - 5.08, P = 0.99), and restenosis (RR: 1.92, 95% CI: 0.24 - 15.35, P = 0.54). Conclusion: In this meta-analysis, we found a higher risk of all-cause mortality in patients with a history of thoracic radiation undergoing PCI, likely from underlying malignancy itself.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".