Effectiveness of a neonatal intensive care unit–specific antimicrobial stewardship program: A ten-year review
Bibliographic record
Abstract
OBJECTIVE: To evaluate the change in consumption of specific antibiotics in a neonatal intensive care unit after the implementation of an antimicrobial stewardship program (ASP). DESIGN: Retrospective cohort study between January 1, 2010, and December 31,2019. SETTING: The neonatal intensive care unit at British Columbia Women's Hospital (Vancouver Canada), a tertiary-care center. PATIENTS: Admitted neonates prescribed antibiotics. METHODS: We implemented an ASP with an early implementation phase starting in January 2014 (period 2) and a later phase starting in January 2017 (period 3). Patient demographics were collected, including birth weight, gestational age, history of necrotizing enterocolitis (NEC), and surgical operations from existing databases. Interrupted time-series analysis was used, and comparison of antibiotic days of therapy (DOT) averages were conducted across the preimplementation period (period 1), period 2, and period 3 regarding total patients and subgroups. RESULTS: We identified 4,512 infants. There was a significant decrease in DOT from 472 (95% confidence interval [CI], 431-517) in period 1 to 405 (95% CI, 367-446) in period 2 to 313 (95% CI, 280-350) in period 3. We detected a significant decrease in the use of ampicillin, aminoglycosides, cloxacillin, and linezolid but not in vancomycin or cefotaxime. Subgroup analyses of infants <1,500 g and those without NEC or surgery showed decreases in the use of cloxacillin, aminoglycosides, and linezolid. CONCLUSIONS: The implementation of an ASP was associated with a significant decrease in the overall DOT and use of certain antibiotics. This study presents important targets for ongoing ASP work.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".