Development and Evaluation of a Novel Fast Broad-Range ITS/LSU DNA PCR and Sequencing Assay (FBR-PCR/S) for Rapid Diagnosis of Invasive Fungal Diseases: Multi-Year Experience in a Large Canadian Healthcare Zone and a Literature Review
Bibliographic record
Abstract
Abstract BackgroundThis study evaluated the performance of a novel fast broad range PCR and sequencing (FBR-PCR/S) assay for the improved diagnosis of invasive fungal disease (IFD) in high-risk patients in a large Canadian healthcare region.MethodsA total of 114 clinical specimens (CS) including bronchoalveolar lavages (BALs) were prospectively tested from 107 patients over a 2-year period. Contrived BALs (n=33) inoculated with known fungi pathogens were also tested to increase diversity. Patient characteristics, fungal stain and culture results were collected from the laboratory information system. Dual-priming oligonucleotide (DPO) primers targeted to the ITS (~350 bp) and LSU (~550 bp) gene regions were used to perform FBR-PCR/S assays on extracted BALs/CS. The performance of the molecular test was evaluated against results of fungal stains and culture, and where available, histopathology, and clinical review for the presence of IFD.ResultsThe 107 patients were predominantly male (67, 62.6%%) with a mean age of 59 yrs. (range = 0 to 85 yrs.): 74 (69.2%) patients had at least one underlying comorbidity: 19 (34.5%) had confirmed and 12 (21.8%) had probable IFD. Culture recovered 66 fungal isolates from 55 BALs/CS with Candida spp. and Aspergillus spp. being most common. For BALs, the molecular assay vs. fungal culture had sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and efficiency of 88.5% vs.100%, 100% vs. 61.1%, 100% vs. 88.5%, 61.1% vs. 100%, and 90.2% for both. For other CS, the molecular assay had similar performance to fungal culture with sensitivity, specificity, PPV, NPV and efficiency of 66.7%, 87.0%, 66.7%, 87.0% and 81.3% for both methods. Both methods also performed similarly, regardless of whether CS stain/microscopy showed yeast/fungal elements. FBR-PCR/S assays results were reported in ~8h compared to fungal cultures that took between 4 to 6 weeks.ConclusionsRapid molecular testing compared to culture has equivalent diagnostic efficiency but improves clinical utility by reporting a rapid species-level identification the same dayshift (~8h).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".