430Patients with Prolonged (>10 days) Neutropenia Displayed Similar IFI Rates Regardless of Hematologic Diagnosis and Chemotherapy Status: A Challenge to Antifungal Prophylaxis Decisions
Bibliographic record
Abstract
Background. Invasive fungal infections (IFI) are a significant source of morbidity and mortality in neutropenic patients. Risk based prophylaxis or pre-emptive therapy are debated clinical approaches. Since 2009, IPC at our tertiary care institution has collected the IFI rate per 1,000 neutropenic patient days. We examine IFI per neutropenic episode by patient characterictics and duration of neutropenia. Methods. All neutropenic Hematology ward patients were assessed, those with ANC of 0.5 x 109/L or less for >10 days were followed prospectively for development of Probable or Definite IFI by the 2008 EORTC criteria. Chart data were collected: demographics, hematologic diagnosis, type of chemotherapeutic regimen, and neutropenic days (NDS), and if an IFI was diagnosed; the fungus, site of culture, and outcome. Results. There were 277 neutropenic episodes in 180 patients, (mean 26 NDs) identified from January 2009 to December 2010. ‘Severe’ criteria was met in 177 episodes (63.9%) in 116 patients (mean 37.8 NDs). Twenty (17.2%) of these had IFI with 6 (30%) related deaths. IFI case patients (21 IFIs) had a mean of 43.9 NDs per episode (4-148 days) . There were 6 cases of aspergillosis, 14 candidiasis, and 1 fungus that failed to grow but resembled coccidiomycosis. Conclusion. The range of NDs per episode was broader than expected. In all but ALL patients the IFI rate was 10-16% of neutropenic episodes. Our current criteria for antimould prophylaxis (re/induction AML) would have applied to 10 IFI in 89 episodes, with 10 IFI in 69 episodes (all other non ALL patients) planned for prophylaxis under our current rules. Larger studies of the intensity and modifiability of IFI risk in nonacute hematologic diagnoses are needed. Disclosures. All authors: No reported disclosures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".