The utility of cardiac stress testing for detection of cardiovascular disease in breast cancer survivors: a systematic review
Bibliographic record
Abstract
BACKGROUND: Heart function tests performed with myocardial stress, or "cardiac stress tests", may be beneficial for detection of cardiovascular disease. Women who have been diagnosed with breast cancer are more likely to develop cardiovascular diseases than the general population, in part due to the direct toxic effects of cancer treatment on the cardiovascular system. The aim of this review was to determine the utility of cardiac stress tests for the detection of cardiovascular disease after cardiotoxic breast cancer treatment. DESIGN: Systematic review. METHODS: Medline and Embase were searched for studies utilizing heart function tests in breast cancer survivors. Studies utilizing a cardiac stress test and a heart function test performed at rest were included to determine whether stress provided added benefit to identifying cardiac abnormalities that were undetected at rest within each study. RESULTS: Fourteen studies were identified. Overall, there was a benefit to utilizing stress tests over tests at rest in identifying evidence of cardiovascular disease in five studies, a possible benefit in five studies, and no benefit in four studies. The most common type of stress test was myocardial perfusion imaging, where reversible perfusion defects were detected under stress in individuals who had no defects at rest, in five of seven studies of long-term follow-up. Two studies demonstrated the benefit of stress echocardiography over resting echocardiography for detecting left ventricular dysfunction in anthracycline-treated breast cancer survivors. There was no benefit of stress cardiac magnetic resonance imaging in one study. Two studies showed a potential benefit of stress electrocardiography, whereas three others did not. CONCLUSION: The use of cardiac stress with myocardial perfusion imaging and echocardiography may provide added benefit to tests performed at rest for detection of cardiovascular disease in breast cancer survivors, and merits further research.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".