Myocardial scintigraphy correlates poorly with coronary angiography in the screening of transplant arteriosclerosis.
Bibliographic record
Abstract
BACKGROUND: Coronary angiography remains an important screening tool for transplant coronary arteriosclerosis (TxCAD) after heart transplantation despite criticism that it underestimates the incidence of TxCAD. In an effort to improve TxCAD incidence estimation, several methods of screening have been proposed. In the present study, the incidence of TxCAD assessed by both yearly coronary angiography and stress myocardial scintigraphy imaging was reviewed. PATIENTS AND METHODS: Ninety-nine consecutive primary heart transplantations were performed from 1988 to 1999. The standard immunosuppression protocol consisted of the introduction of antilymphocyte globulin and steroids, while maintenance therapy was with cyclosporine, imuran and steroids. Coronary angiography and a stress 2-methoxyisobutyl-isonitrile perfusion scan were performed yearly. TxCAD was defined by angiographic evidence of luminal abnormality by catheterization, or a perfusion abnormality at rest or after stress on myocardial scintigraphy. RESULTS: The mean recipient age was 49+/-12 years and the mean donor age was 33+/-13 years. The etiology of heart failure was ischemic cardiomyopathy (50%), dilated cardiomyopathy (41%) and congenital heart disease (9%). The freedom from angiographic TxCAD was 92% at one year, 64% at five years and 35% at eight years. The freedom from nuclear imaging TxCAD was 92% at one year, 69% at five years and 44% at eight years. However, a diagnosis of TxCAD by angiography only correlated with a diagnosis of TxCAD by nuclear imaging 52.8% of the time in the same patient, with a median time between studies of one month. CONCLUSION: The overall incidence of TxCAD diagnosed by angiography and nuclear imaging appears similar but correlates poorly in patients, casting doubt on the routine use of myocardial scintigraphy for screening TxCAD.
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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 | 0.003 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".