A Neonatologist-Driven Antimicrobial Stewardship Program in a Neonatal Tertiary Care Center in Oman
Bibliographic record
Abstract
OBJECTIVE: The overuse of antimicrobials in neonates is not uncommon and has resulted in a global health crisis of antibiotic resistance. This study aimed to evaluate changes associated with a neonatologist-driven antimicrobial stewardship program (ASP) in antibiotic usage. STUDY DESIGN: We conducted a pre-post retrospective cohort study in a tertiary care hospital in Oman. Neonates admitted in 2014 to 2015 were considered as the pre-ASP cohort. In 2016, a neonatologist-driven ASP was launched in the unit. The program included the optimization and standardization of antibiotic use for early- and late-onset sepsis using the Centers for Disease Control and Prevention's "broad principles," an advanced antimicrobial decision-support system to resolve contentious issues, and placed greater emphasis on education and behavior modification. Data from the years 2016 to 2019 were compared with previous data. The outcome of interest included days of therapy (DOT) for antimicrobials. Baseline characteristics and outcomes were compared using standard statistical measures. RESULTS: < 0.001). The proportion of neonates who received any antibiotics declined by 46% (pre-ASP = 1,161/2,098, post-ASP = 1,676/5,464). The most statistically significant reduction in DOT per 1,000 PD was observed in the use of cefotaxime (82%), meropenem (74%), and piperacillin-tazobactam (74%). There was no change in mortality, culture-positive microbial profile, or multidrug-resistant organism incidence in the post-ASP period. CONCLUSION: Empowering frontline neonatologists to drive ASPs was associated with a sustained reduction in antibiotic utilization. KEY POINTS: · Overuse of antimicrobials is not uncommon in neonatal intensive care units.. · ASPs and infection control and prevention measures may help in decreasing antibiotic consumption and culture-positive sepsis.. · Empowering frontline neonatologists resulted in a sustained decrease in antimicrobial use without extra resources or financial burden..
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".