Point prevalence survey of antibiotics use among hospitalised neonates and children in Saudi Arabia: findings and implications
Bibliographic record
Abstract
Background: Neonates and children are more susceptible to a variety of infections, leading to frequent antibiotic prescriptions. However, the inappropriate use of antibiotics leads to antibiotic resistance and higher mortality rates. Therefore, this study aimed to determine the prevalence of antibiotic use, and current antibiotic prescribing practices among neonates and children admitted in the selected hospitals of Saudi Arabia. Methods: A cross-sectional study was conducted from September to November 2023 to assess the prevalence of antibiotic use, and the current antibiotic prescribing practices across six hospitals of Saudi Arabia. Results: The study included 499 children and neonates, with 94.6% receiving antibiotic prescriptions. The most frequently prescribed antibiotic class was third-generation cephalosporin (31.5%), with ceftriaxone being the most commonly prescribed antibiotic (15%). The majority of patients were prescribed one antibiotic (81.4%), and the intravenous route (96.4%) was the primary route for administration. The majority of patients were prescribed antibiotics empirically (69.7%), and community-acquired infections (64.2%) were the most common type of infection for antibiotic prescription. Similarly, sepsis (39.2%) was the most common indication for antibiotics, and the majority of prescribed antibiotics (61.7%) belonged to the 'Watch' category as per WHO AWaRe classification. Conclusion: Our study revealed excessive antibiotic consumption in neonates and children, therefore quality improvement programmes including antimicrobial stewardship programmes are urgently needed to address ongoing issues.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".