Use of food restrictions to prevent infections in paediatric patients with cancer and haematopoietic cell transplantation recipients: a systematic review and clinical practice guideline
Bibliographic record
Abstract
Background: Food restrictions during periods of neutropenia have been widely used in oncology settings to prevent infections. As there is a lack of clearly demonstrated effectiveness, this strategy is being increasingly questioned. Methods: A multi-national panel of 23 individuals was convened to develop a clinical practice guideline (CPG) on the use of food restrictions to prevent infections in paediatric patients with cancer and haematopoietic cell transplantation (HCT) recipients. It included representation from persons with lived experience and physicians, dieticians, nurses, pharmacists and guideline methodologists working in paediatric oncology/HCT or infectious diseases. Panel members (female n = 15; 65%) were from North America (12, 52%), Europe (8, 35%), South America (2, 9%) and Australia (1, 4%). The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to formulate the CPG recommendations based on a systematic review of randomised controlled trials (RCTs). MEDLINE, MEDLINE in-Process and Embase databases were searched from January 1, 1980, to May 7, 2024, with a broad strategy which combined subject headings and text words relating to neutropenia, infection and diet. Findings: The systematic review, which provided the evidence base for the CPG recommendations, identified 4312 unique citations, of which 52 were retrieved for full-text evaluation. Eight RCTs met the eligibility criteria and informed panel deliberations. Although there was clinical heterogeneity in the food restrictions evaluated, data were consistent in suggesting that food restrictions lack clinically significant benefit in preventing infections. The panel made two conditional recommendations against the use of food restrictions in a) paediatric patients with cancer receiving chemotherapy and b) in the setting of allogeneic and autologous HCT. The panel developed a good practice statement to emphasise the importance of health care organisations and families adhering to local food safety practices. Interpretation: This CPG provides the first evidence-based recommendations on use of food restrictions to prevent infections in children and adolescents undergoing chemotherapy and paediatric haematopoietic cell transplant recipients. Funding: This CPG was funded and developed through the POGO Guidelines Program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".