Defining the relationships among four tests for assessing antibody-mediated rejection in heart transplants in a prospective, observational study
Bibliographic record
Abstract
BACKGROUND: Four tests assess antibody-mediated rejection (ABMR) in heart transplants: standard of care local endomyocardial biopsy (EMB) histology, EMB molecular analysis (Molecular Microscope® Diagnostic System - MMDx), donor-derived cell-free DNA (dd-cfDNA), and donor-specific antibody (DSA). These tests have become critical for the development and use of novel therapies for ABMR. The Trifecta-Heart study (NCT04707872) aimed to define the relationships among these tests. METHODS: The study compared standard of care local histology diagnosis to the results of three central tests assessing ABMR: central DSA (One Lambda Inc.), dd-cfDNA (Natera, Inc.), and MMDx rejection assessments in 214 EMBs. Results were primarily expressed as positive-negative to facilitate analysis and to simulate the way all tests are used for clinical decision-making. RESULTS: MMDx diagnosed more ABMR, TCMR, and No rejection (NR) than histology, a pattern confirmed in a validation set from the larger INTERHEART study (NCT02670408). When correlations and partial correlation modeling were used to defined the hierarchy of relationships among all tests, MMDx ABMR correlated more strongly with dd-cfDNA and DSA than did histologic ABMR. In MMDx-histology discrepancies, biopsies with no histologic rejection but with MMDx ABMR had elevated DSA and dd-cfDNA, and biopsies with MMDx NR but histology ABMR had low DSA and dd-cfDNA. DSA-negative ABMR by MMDx or histology had elevated dd-cfDNA, similar to DSA-positive ABMR. Most cases with molecular injury and high dd-cfDNA also had concurrent molecular rejection. CONCLUSIONS: These inter-test relationships will be useful in guiding ABMR management, including monitoring of treatment responses and relapses, especially when discrepancies occur.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".