Fungal Cultures in Patients with Allergic Fungal Rhinosinusitis: Improving the Recovery of Potential Fungal Pathogens in the Canadian Laboratory
Bibliographic record
Abstract
BACKGROUND: There is no uniform consensus on how to grow fungi from sinus aspirates in the Canadian setting. Protocols vary between institutions, and the positivity rate for fungal cultures ranges between 10 and 20% even when endoscopically obvious allergic mucin is being sent to the laboratory. The aim of this study was to compare the occurrence of positive fungal cultures obtained by our institution's fungal culture method with the occurrence obtained by the Mayo Clinic's fungal culture method. The ultimate aim was to propose a modified, feasible, standardized protocol for culturing fungi from sinus aspirates in the Canadian laboratory setting. METHODS: Twenty-five allergic mucin aspirates were collected in 23 consecutive patients meeting the clinical diagnosis of allergic fungal rhinosinusitis. These samples were sent to the microbiology laboratory, where half of them were subject to our conventional laboratory protocol and the other half to the modified Mayo Clinic protocol. RESULTS: Positive fungal cultures were obtained in 16 of 25 (64%) specimens when the modified Mayo Clinic culture technique was used, with 12 cultures (48%) growing pathogenic fungus. Using our standard culture technique, 4 of 25 (16%) specimens resulted in a positive fungal culture, of which 3 grew pathogenic fungus (12%). A significantly greater fungal culture yield was obtained by the modified Mayo Clinic fungal culture technique than with our culturing technique. CONCLUSION: The modified Mayo Clinic fungal culture technique, although more costly, is a highly sensitive and effective technique for growing fungi from nasal specimens when compared with our traditional culture technique.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".