Assessment of Surgical Antibiotic Prophylaxis Compliance in Pediatrics: A Pre–post Quasi-experimental Study
Bibliographic record
Abstract
OBJECTIVE: Data from rigorous evaluations of the impact of interventions on improving surgical antibiotic prophylaxis (SAP) compliance in pediatrics are lacking. Our objective was to assess the impact of a multifaceted intervention on improving pediatric SAP compliance in a hospital without an ongoing antimicrobial stewardship program. STUDY DESIGN: A multidisciplinary team at the Montreal Children's Hospital performed a series of interventions designed to improve pediatric SAP compliance in June 2015. A retrospective, quasi-experimental study was performed to assess SAP compliance before and following the interventions. Our study included patients under 18 years old undergoing surgery between April and September in 2013 (preintervention) and in 2016 (postintervention). A 10-week washout period was included to rigorously assess the persistence of compliance without ongoing interventions. SAP, when indicated, was qualified as noncompliant, partially compliant (adequate agent and timing) or totally compliant (adequate agent, dose, timing, readministration, duration). RESULTS: A total of 982 surgical cases requiring SAP were included in our primary analysis. The composite partial and total compliance increased from 51.4% to 55.8% [adjusted odds ratio 1.3; 95% confidence interval: 1.0-1.8; P = 0.06]. Although improvements in correct dose and readministration were significant, there was no significant improvement in correct timing, agent selection or duration. CONCLUSION: Our study demonstrated that overall SAP compliance did not significantly improve following a washout period, illustrating the importance of ongoing surveillance and feedback from an antimicrobial stewardship program. Our strict approach in evaluating the timing criterion may also explain the lack of a significant impact on SAP compliance.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".