Non-invasive diagnosis of invasive fungal disease with cell-free DNA PCR
Bibliographic record
Abstract
ABSTRACT Invasive fungal disease (IFD) is a major cause of morbidity and mortality in the immunocompromised population. Early diagnosis is challenging due to the low sensitivity and non-specificity of non-invasive fungal biomarkers, the need for invasive specimen collection, and the limitations of culture and histopathology. Detection of circulating fungal cell-free DNA (cfDNA) in plasma and serum by polymerase chain reaction (PCR) represents a novel testing modality for rapid and accurate diagnosis of IFD. In this review, we summarize the performance characteristics of fungal cfDNA PCR for the diagnosis of invasive aspergillosis, mucormycosis, and Pneumocystis pneumonia. We discuss a testing algorithm that incorporates fungal cfDNA and the added diagnostic value of invasive specimen collection when non-invasive mold cfDNA PCR is performed first. Lastly, we discuss the role of diagnostic stewardship in fungal cfDNA PCR testing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".