Infections During Induction Therapy of Protocol CCLG-2008 in Childhood Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
BACKGROUND: Infections remain a major cause of therapy-associated morbidity and mortality in children with acute lymphoblastic leukemia (ALL). METHODS: We retrospectively analyzed the medical charts of 256 children treated for ALL under the CCLG-2008 protocol in Beijing Children's Hospital. RESULTS: There were 65 infectious complications in 50 patients during vincristine, daunorubicin, L-asparaginase and dexamethasone induction therapy, including microbiologically documented infections (n = 12; 18.5%), clinically documented infections (n = 23; 35.3%) and fever of unknown origin (n = 30; 46.2%). Neutropenia was present in 83.1% of the infectious episodes. In all, most infections occurred around the 15 th day of induction treatment (n = 28), and no patients died of infection-associated complications. CONCLUSIONS: The infections in this study was independent of treatment response, minimal residual diseases at the end of induction therapy, gender, immunophenotype, infection at first visit, risk stratification at diagnosis, unfavorable karyotypes at diagnosis and morphologic type. The infection rate of CCLG-2008 induction therapy is low, and the outcome of patients is favorable.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".