Prognostic Value of Rubidium-82 Positron Emission Tomography in Patients After Heart Transplant
Bibliographic record
Abstract
BACKGROUND: Cardiac allograft vasculopathy is a key prognostic determinant after heart transplant. Detection and risk stratification of patients with cardiac allograft vasculopathy are problematic. Positron emission tomography using rubidium-82 allows quantification of absolute myocardial blood flow and may have utility for risk stratification in this population. METHODS AND RESULTS: Patients with a history of heart transplant undergoing dipyridamole rubidium-82 positron emission tomography were prospectively enrolled. Myocardial perfusion and left ventricular ejection fraction were recorded. Absolute flow quantification at rest and after dipyridamole stress as well as the ratio of mean global flow at stress and at rest, termed myocardial flow reserve, were calculated. Patients were followed for all-cause death, acute coronary syndrome, and heart failure hospitalization. A total of 140 patients (81% men; median age, 62 years; median follow-up, 18.2 months) were included. There were 14 events during follow-up (9 deaths, 1 acute coronary syndrome, and 4 heart failure admissions). In addition to baseline clinical variables (estimated glomerular filtration rate, previously documented cardiac allograft vasculopathy), relative perfusion defects, mean myocardial flow reserve, and mean stress myocardial blood flow were significant predictors of adverse outcome. CONCLUSIONS: Abnormalities on rubidium-82 positron emission tomography were predictors of adverse events in heart transplant patients. Larger prospective studies are required to confirm these findings.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".