Guideline for Antibacterial Prophylaxis Administration in Pediatric Cancer and Hematopoietic Stem Cell Transplantation
Bibliographic record
Abstract
BACKGROUND: Bacteremia and other invasive bacterial infections are common among children with cancer receiving intensive chemotherapy and in pediatric recipients of hematopoietic stem cell transplantation (HSCT). Systemic antibacterial prophylaxis is one approach that can be used to reduce the risk of these infections. Our purpose was to develop a clinical practice guideline (CPG) for systemic antibacterial prophylaxis administration in pediatric patients with cancer and those undergoing HSCT. METHODS: An international and multidisciplinary panel was convened with representation from pediatric hematology/oncology and HSCT, pediatric infectious diseases (including antibiotic stewardship), nursing, pharmacy, a patient advocate, and a CPG methodologist. The panel used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to generate recommendations based on the results of a systematic review of the literature. RESULTS: The systematic review identified 114 eligible randomized trials of antibiotic prophylaxis. The panel made a weak recommendation for systemic antibacterial prophylaxis for children receiving intensive chemotherapy for acute myeloid leukemia and relapsed acute lymphoblastic leukemia (ALL). Weak recommendations against the routine use of systemic antibacterial prophylaxis were made for children undergoing induction chemotherapy for ALL, autologous HSCT and allogeneic HSCT. A strong recommendation against its routine use was made for children whose therapy is not expected to result in prolonged severe neutropenia. If used, prophylaxis with levofloxacin was recommended during severe neutropenia. CONCLUSIONS: We present a CPG for systemic antibacterial prophylaxis administration in pediatric cancer and HSCT patients. Future research should evaluate the long-term effectiveness and adverse effects of prophylaxis.
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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 | 0.023 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".