Association Between Corticosteroids and Infection, Sepsis, and Infectious Death in Pediatric Acute Myeloid Leukemia (AML): Results From the Canadian Infections in AML Research Group
Bibliographic record
Abstract
BACKGROUND: Infection continues to be a major problem for children with acute myeloid leukemia (AML). Objectives were to identify factors associated with infection, sepsis, and infectious deaths in children with newly diagnosed AML. METHODS: We conducted a retrospective, population-based cohort study that included children ≤ 18 years of age with de novo, non-M3 AML diagnosed between January 1995 and December 2004, treated at 15 Canadian centers. Patients were monitored for infection from initiation of AML treatment until recovery from the last cycle of chemotherapy, conditioning for hematopoietic stem cell transplantation, relapse, persistent disease, or death (whichever occurred first). Consistent trained research associates abstracted all information from each site. RESULTS: 341 patients were included. Median age was 7.1 years (interquartile range [IQR], 2.0-13.5) and 29 (8.5%) had Down syndrome. In sum, 26 (7.6%) experienced death as a first event. There were 1277 courses of chemotherapy administered in which sterile site microbiologically documented infection occurred in 313 courses (24.5%). Sepsis and infectious death occurred in 97 (7.6%) and 16 (1.3%) courses, respectively. The median days of corticosteroid administration was 2 per course (IQR, 0-6). In multiple regression analysis, duration of corticosteroid exposure was significantly associated with more microbiologically documented sterile site infection, bacteremia, fungal infection, and sepsis. The only factor significantly associated with infectious death was days of corticosteroid exposure (odds ratio, 1.05; 95% confidence interval, 1.02-1.08; P = .001). CONCLUSIONS: In pediatric AML, infection, sepsis, and infectious death were associated with duration of corticosteroid exposure. Corticosteroids should be avoided when possible for this population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".