(1,3) β-D-Glucan in Bronchoalveolar Lavage of Lung Transplant Recipients for the Diagnosis of Invasive Pulmonary Aspergillosis
Bibliographic record
Abstract
(1,3) β-D-Glucan (BDG) is present in the cell wall of most fungi. Its detection in serum has been useful in the diagnosis of invasive aspergillosis (IA) in patients with hematologic malignancies. However, assaying for BDG did not perform well in the serum of lung transplant recipients. We undertook to study the performance of BDG in the bronchoalveolar lavage (BAL) of lung transplant recipients for the diagnosis of invasive pulmonary aspergillosis (IPA). Available and stored BAL samples from lung transplant recipients at the Toronto General Hospital between October 2007 and April 2013 were tested for BDG using the Fungitell kit from the Associates of Cape Cod Inc, Falmouth, MA, USA : The International Society for Heart and Lung transplantation (ISHLT) criteria was used for the diagnosis of IA. Of 195 samples, there were ten episodes of IA. The sensitivity and specificity of the test were 80% and 53% and 60% and 70% at 41 pg/ml and 108 pg/ml cut-offs, respectively. On excluding 52 bronchoscopies due to receipt of anti-Aspergillus therapy during specimen collection, the sensitivity and specificity improved to 75% and 91%, respectively, at a 524 pg/ml cut-off. However, only four episodes of IA remained in this analysis. Using BDG in BAL of lung transplant recipients for the diagnosis of IA, our study demonstrated moderate sensitivity and specificity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".