A consensus conference to define the utility of advanced infectious disease diagnostics in solid organ transplant recipients
Bibliographic record
Abstract
The last decade has seen an explosion of advanced assays for the diagnosis of infectious diseases, yet evidence-based recommendations to inform their optimal use in the care of transplant recipients are lacking. A consensus conference sponsored by the American Society of Transplantation (AST) was convened on December 7, 2021, to define the utility of novel infectious disease diagnostics in organ transplant recipients. The conference represented a collaborative effort by experts in transplant infectious diseases, diagnostic stewardship, and clinical microbiology from centers across North America to evaluate current uses, unmet needs, and future directions for assays in 5 categories including (1) multiplex molecular assays, (2) rapid antimicrobial resistance detection methods, (3) pathogen-specific T-cell reactivity assays, (4) next-generation sequencing assays, and (5) mass spectrometry-based assays. Participants reviewed and appraised available literature, determined assay advantages and limitations, developed best practice guidance largely based on expert opinion for clinical use, and identified areas of future investigation in the setting of transplantation. In addition, attendees emphasized the need for well-designed studies to generate high-quality evidence needed to guide care, identified regulatory and financial barriers, and discussed the role of regulatory agencies in facilitating research and implementation of these assays. Findings and consensus statements are presented.
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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 | 0.199 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.013 | 0.011 |
| Research integrity | 0.027 | 0.035 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".