Impact of fluconazole prophylaxis on fungal colonization and infection rates in neutropenic patients
Bibliographic record
Abstract
Fungal colonization profiles from four different anatomical sites were evaluated in 266 neutropenic cancer patients receiving intensive cytotoxic therapy for acute leukaemia or for autologous marrow transplantation. At the beginning of chemotherapy patients were allocated randomly to receive oral fluconazole 400 mg daily or an identical placebo until prophylaxis failure or marrow recovery. Candida albicans colonization was reduced from 30 to 10% in the fluconazole recipients while it increased from 32 to 57% in the placebo patients (P<0.001). By the end of prophylaxis, colonization with non-albicans Candida species increased from 7 to 21% and 8 to 18% in the fluconazole and placebo patients, respectively (P = 0.396). Although Candida glabrata was isolated more frequently at the end of the prophylactic period in the fluconazole patients than in the placebo patients (16 versus 7%), only one definite invasive C. glabrata infection was noted. Overall, definite invasive fungal infections were documented in 26 patients [four fluconazole versus 22 placebo patients (P< or =0.001)]. In 23 (92%) patients the infections were caused by persistently colonizing or newly acquired organisms. While probable invasive fungal infections were noted in five fluconazole patients, 10 placebo patients were also affected (P = 0.19). An end-of-prophylaxis colonization index >0.25 was 76% sensitive but only 69% specific for invasive fungal infection. However, a colonization index < or =0.25 at baseline had a negative predictive value of 88% for development of invasive fungal infection. Fluconazole prophylaxis decreased colonization by fungi and subsequent invasive fungal infections in neutropenic cancer patients.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".