Comparison of Myocardial Perfusion Scintigraphy and Coronary Angiography Results in Breast Cancer Patients Treated with Radiotherapy
Bibliographic record
Abstract
Breast cancer is the most common type of malignancy in women and radiotherapy (RT) is an important part of treatment. Although it reduces cancer recurrence, it has been shown to cause accerelerated athnerosclerosis. This study aimed to compare the results of myocardial perfusion scintigraphy (MPS) for ischemia investigation with coronary angiography (CAG) findings and to investigate the effect of RT on the development of coronary artery disease in breast cancer patients who underwent RT. The results of 660 patients were analyzed and compared with each other in terms of clinical, demographic, laboratory parameters and MPS results. The mean age was 57.5 years and all of them were female. When the groups were compared, the Gensini score and marking of the left anterior descending artery (LAD) area as ischemic area localization were found more, but angiographically, the rate of severe stenosis in the area indicated by MPS was found to be lower in the RT group (p < 0.001). While the sensitivity of MPS in the RT group was 67.5% and non-RT group was 88.5% (p < 0.001), the result of our study shows that the sensitivity of the MPS test is significantly lower in the patient group receiving RT.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".