International Survey on Determinants of Antibiotic Duration and Discontinuation in Pediatric Critically Ill Patients
Bibliographic record
Abstract
OBJECTIVES: We hypothesized that antibiotic use in PICUs is based on criteria not always supported by evidence. We aimed to describe determinants of empiric antibiotic use in PICUs in eight different countries. DESIGN: Cross-sectional survey. SETTING: PICUs in Canada, the United States, France, Italy, Saudi Arabia, Japan, Thailand, and Brazil. SUBJECTS: Pediatric intensivists. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used literature review and focus groups to develop the survey and its clinical scenarios (pneumonia, septic shock, meningitis, and intra-abdominal infections) in which cultures were unreliable due to antibiotic pretreatment. Data analyses included descriptive statistics and linear regression with bootstrapped SEs. Overall response rate was 39% (482/1,251), with individual country response rates ranging from 25% to 76%. Respondents in all countries prolonged antibiotic duration based on patient characteristics, disease severity, pathogens, and radiologic findings (from a median increase of 1.8 d [95% CI, 0.5-4.0 d] to 9.5 d [95% CI, 8.5-10.5 d]). Younger age, severe disease, and ventilator-associated pneumonia prolonged antibiotic treatment duration despite a lack of evidence for such practices. No variables were reported to shorten treatment duration for all countries. Importantly, more than 39% of respondents would use greater than or equal to 7 days of antibiotics for patients with a positive viral polymerase chain reaction test in all scenarios, except in France for pneumonia (29%), septic shock (13%), and meningitis (6%). The use of elevated levels of inflammatory markers to prolong antibiotic treatment duration varied among different countries. CONCLUSIONS: Antibiotic-related decisions are complex and may be influenced by cultural and contextual factors. Evidence-based criteria are necessary to guide antibiotic duration and ensure the rational use of antibiotics in PICUs.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".