Early Deaths in Pediatric Acute Leukemia: A Major Challenge in Developing Countries
Bibliographic record
Abstract
Children with acute leukemia may experience high treatment-related mortality, which often occurs early in the induction phase. The aim of the study was to assess the incidence and risk factors related to increased mortality during induction therapy of pediatric patients with acute leukemia. This is a retrospective study that included pediatric acute leukemia patients who presented to the National Cancer Institute, Cairo University, between January 2011 and December 2013. The study included 370 patients, 253 with acute lymphoblastic leukemia, 100 with acute myeloid leukemia, and 17 with mixed phenotype acute leukemia. The total and induction death rates were 40.5% and 19.2%, respectively. Most of the early deaths were attributed to infections (64.7%) and cerebrovascular accidents (18.3%). Using enhanced supportive care measures during 2013 had significantly reduced the overall and induction mortality rates (29% and 13.6%, respectively, in 2013 vs. 46% and 20.3% in 2011). Induction deaths in pediatric acute leukemia remain a major challenge in developing countries, and using enhanced supportive care measures is effective to improve the survival outcome in this group of 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".