Perspectives on <i>Scedosporium</i> species and <i>Lomentospora prolificans</i> in lung transplantation: Results of an international practice survey from ESCMID fungal infection study group and study group for infections in compromised hosts, and European Confederation of Medical Mycology
Bibliographic record
Abstract
BACKGROUND: Scedosporium species and Lomentospora prolificans (S/L) are the second most common causes of invasive mold infections following Aspergillus in lung transplant recipients. METHODS: We assessed the current practices on management of S/L colonization/infection of the lower respiratory tract before and after lung transplantation in a large number of lung transplant centers through an international practice survey from October 2016 to March 2017. RESULTS: A total of 51 respondents from 45 lung transplant centers (17 countries, 4 continents) answered the survey (response rate 58%). S/L colonization was estimated to be detected in candidates by 48% of centers. Only 18% of the centers used a specific medium to detect S/L colonization. Scedosporium spp. colonization was a contraindication to transplantation in 10% of centers whereas L prolificans was a contraindication in 31%; 22% of centers declared having had 1-5 recipients infected with S/L in the past 5 years. CONCLUSIONS: This survey gives an overview of the current practices regarding S/L colonization and infection in lung transplant centers worldwide and underscores the need of S/L culture procedure standardization before implementing prospective studies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".