eP48 Multi-cycle audit on antibiotic duration and stepdown following laparotomy
Bibliographic record
Abstract
Abstract Aims To audit adherence to local guidelines on antibiotic stewardship in patients who underwent laparotomy, particularly, duration of antibiotics following definitive surgery/source control To increase antibiotic stewardship by reducing duration of antibiotic course and promoting consideration of early stepdown of antibiotics where clinically appropriate in patients following laparotomy Methods Data were reviewed for all adult general surgery patients who underwent laparotomy over a 4-month period in late 2023. Patients were excluded if there were incomplete or unavailable documentation relating to their operation or post-operative care. Data were extracted relating to patient demographics, type of operation and duration of antibiotic treatment post-operatively. Results were presented locally to the surgical team, highlighting trust-specific guidance on prescribing in intra-abdominal infection, and input from the microbiology team. A second 4-month cycle was completed in early 2024. Results Cycle 1: Data were extracted from 30 post-laparotomy patients. The most common indication for laparotomy was bowel obstruction (n=25), with confirmed perforation (n=8). The average duration of antibiotic treatment post-operatively was 11.2 days (± 7.7). Cycle 2: Data were reviewed from 49 post-laparotomy patients. 34 patients had bowel obstruction with 8 confirmed perforations intra-operatively. The average duration of post-operative antibiotic treatment was 8.6 days (± 5.8). Conclusions Duration of antibiotic therapy is significantly beyond what is recommended by microbiologists and local guidelines following source-control surgery. Possible contributing factors include surgical apprehension to stepdown or stop antibiotics in the peri-operative period, and system barriers caused by electronic prescribing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".