Clostridium difficile Infection in Pediatric Acute Myeloid Leukemia
Bibliographic record
Abstract
BACKGROUND: The prevalence and severity of Clostridium difficile infection (CDI) has increased over time in adult patients, but little is known about CDI in pediatric cancer. The primary objectives were to describe the incidence and characteristics of CDI in children with de novo acute myeloid leukemia (AML). The secondary objective was to describe factors associated with CDI. METHOD: We performed a multicenter, retrospective cohort study of children with de novo AML and evaluated CDI. Recurrence, sepsis and infection-related death were examined. Factors associated with CDI were also evaluated. RESULTS: Forty-three CDI occurred in 37 of 341 (10.9%) patients during 42 of 1277 (3.3%) courses of chemotherapy. There were 6 children with multiple episodes of CDI. Three infections were associated with sepsis, and no children died of CDI. Only 2 children had an associated enterocolitis. Both days of broad-spectrum antibiotics (odds ratio 1.03, 95% confidence interval: 1.01 to 1.06; P = 0.003) and at least 1 microbiologically documented sterile site infection (odds ratio 10.81, 95% confidence interval: 5.88 to 19.89; P < 0.0001) were independently associated with CDI. CONCLUSIONS: CDI occurred in 11% of children receiving intensive chemotherapy for AML, and outcomes were not severe. CDI is not a prominent issue in pediatric AML in terms of prevalence, incidence or associated outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".