The Prospective Antifungal Therapy Alliance<sup>®</sup> Registry: A Two‐Centre Canadian Experience
Bibliographic record
Abstract
BACKGROUND: The Prospective Antifungal Therapy Alliance(®) registry is a prospective surveillance study that collected data on the diagnosis, management and outcomes of invasive fungal infections (IFIs) from 25 centres in North America from 2004 to 2008. OBJECTIVE: To evaluate surveillance data on IFIs obtained from study centres located in Canada. METHODS: Patients with proven or probable IFIs at two Canadian medical centres were enrolled in the registry. Information regarding patient demographics, fungal species, infection sites, diagnosis techniques, therapy and survival were analyzed. RESULTS: A total of 347 patients from Canada with documented IFIs were enrolled in the Prospective Antifungal Therapy Alliance registry. Infections occurred most commonly in general medicine (71.8%), nontransplant surgery (32.6%) and patients with hematological malignancies (21.0%). There were 287 proven IFIs, including 248 Candida infections. Forty-six patients had invasive aspergillosis (IA); all of these were probable infections. Most cases of invasive candidiasis were confirmed using blood culture (90.5%), while IA was most frequently diagnosed using computed tomography scan (82.6%) and serological methods (82.6%). Fluconazole was the most common therapy used for Candida infections, followed by the echinocandins. Voriconazole therapy was most commonly prescribed for IA. CONCLUSIONS: The present study demonstrated that general medicine, surgery and hematological malignancy patients in Canada are susceptible to developing IFIs. In contrast to the United States, Candida albicans remains responsible for most IFIs in these Canadian centres. Surrogate serum markers are commonly being used for the diagnosis of IA, while therapy for both IFIs has shifted to broader-spectrum azoles and echinocandins.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".