Evaluation of antibiotic treatment decisions in pediatric intensive care units in Saudi Arabia: A national survey
Bibliographic record
Abstract
OBJECTIVE: To describe variables used by Saudi pediatric intensivists to make antibiotic-related decisions for children with suspected severe bacterial infections. METHODS: We conducted a cross-sectional survey, which was developed using a multi-step methodological approach. The survey included 4 clinical scenarios of the most relevant bacterial infections in pediatric critical care (pneumonia, sepsis, meningitis and intra-abdominal infection). The potential determinants of antibiotic treatment duration addressed in all scenarios included clinical variables (patient characteristics, disease severity), laboratory infection markers, radiologic findings, and pathogens. RESULTS: The response rate was 65% (55/85). Eight variables (immunodeficiency, 3 months of age, 2 or more organ dysfunctions, Pediatric Risk of Mortality III score >10, leukocytosis, elevated C-reactive protein [CRP], elevated erythrocyte sedimentation rate [ESR], and elevated procalcitonin [PCT]) were associated with prolonging antibiotic treatment duration for all 4 clinical scenarios, with a median increase ranging from 3.0 days (95% confidence interval [CI] 0.5, 3.5, leukocytosis) to 8.8 days (95% CI 5.5, 10.5, immunodeficiency). There were no variables that were consistently associated with shortening antibiotic duration across all scenarios. Lastly, the proportion of physicians who would continue antibiotics for ≥5 days despite a positive viral polymerase chain reaction test result was 67% for pneumonia, 85% for sepsis, 63% for meningitis, and 95% for intra-abdominal infections. CONCLUSION: Antibiotic-related decisions for critically ill patients are complex and depend on several factors. Saudi pediatric intensivists will use prolonged courses of antibiotics for younger patients, patients with severe clinical picture, and patients with persistently elevated laboratory markers and hospital acquired infections, even when current literature and guidelines do not suggest such practices. Antimicrobial stewardship programs should include interventions to address these misconceptions to ensure the rational use of antibiotics in pediatric intensive care units.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".