Bibliographic record
Abstract
Introduction: Infection is a major complication of the treatment of paediatric cancer patients due to the immunosuppressive and myelosuppressive nature of the treatment.Prompt administration of antibiotics is the single most important factor in reducing morbidity and mortality in these patients.Antibiotic delivery in less than 60 min of presentation is an important quality measure for oncology centres and EDs.A clinical pathway for the initial management of fever or suspected infection in paediatric oncology patients presenting to the ED in NSW was developed through NSW Kids and Families.Objectives: To determine the effect of implementing this pathway at The Children's Hospital at Westmead on Time from presentation to Administration of Antibiotics (TTAb).Method: The ED admission records of all oncology patients with symptoms suggestive of infection who presented to ED in a 4 month period before the implementation of the pathway and a 1 month period immediately after its implementation were examined, and TTAb was extracted.Results: The study period included 87 patients before and 32 patients after introduction of the pathway.Median TTAb decreased from 74 min to 62 min after its implementation (P = 0.02) The proportion of patients receiving antibiotics in less than 60 min increased from 27.6% to 46.9% (P = 0.05).Conclusion: The implementation of the pathway resulted in a reduced TTAb and an increased proportion of patients receiving antibiotics within 60 min.Heightened awareness and ongoing education of the staff are necessary for sustaining and further reducing TTAb.Obstacles in reducing TTAb are identified and discussed.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.787 | 0.611 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".