The Prognostic Value of (1→3)-β-D-Glucan in COVID-19 Patients with and Without Secondary Fungal Disease
Bibliographic record
Abstract
BACKGROUND: -D-Glucan (BDG) in serum may be indicative of invasive fungal disease (IFD), but even without IFD, elevated BDG can be associated with adverse patient outcomes. METHODS: COVID-19-infected patients (n = 125) who were screened for IFD with fungal biomarkers were evaluated to assess the prognostic value of BDG. BDG was correlated with patients' mortality, considering the influences of IFD and anti-fungal therapy (AFT). RESULTS: = 0.0001). In patients without IFD but with BDG > 31 pg/mL, mortality dropped to 50% when AFT was administered. In patients with BDG > 31 pg/mL and neither IFD nor AFT, the average probability of death was 3.38-fold greater. CONCLUSIONS: Elevated serum BDG is associated with significant mortality in COVID-19-infected patients without IFD, irrespective of AFT. A BDG-associated proinflammatory response might be driving the high mortality. BDG serves as a prognostic marker in COVID-19-infected patients with or without IFD. When BDG is very low (≤31 pg/mL) the likelihood of death remains consistent with the background mortality rates for COVID-19 within the ICU.
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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 | 0.001 |
| 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".