Impact of adherence with in-patient prospective audit and feedback recommendations on patient and economic outcomes
Bibliographic record
Abstract
Introduction: Prospective audit and feedback (PAF) are an antimicrobial stewardship intervention that reduces use of broad-spectrum antimicrobials among in-patients. The objective of this study was to assess the impact of adherence to PAF recommendations on the duration of broad-spectrum antimicrobials and patient outcomes. Methods: This retrospective cohort study included adult in-patients at two tertiary care hospitals in St. John's, Newfoundland and Labrador Canada. PAF included all prescriptions for piperacillin/tazobactam, meropenem, ertapenem, and imipenem, reviewed by an infectious disease specialist on day 3 of therapy, with recommendations provided in the electronic medical record. The primary outcome was duration of treatment following PAF. Secondary outcomes were time to all-cause mortality, time to readmission, length of stay, and time to Clostridiodes difficile infection. Adherence categories were compared. Results: Of the recommendations, 394 out of 786 (50.1%) were completely followed, 18.3% were partially followed, and 31.6% were not followed. There were no significant differences in adherence category based on patient age ( p = 0.48) or sex ( p = 0.93). Adherence category was associated with a graded reduction in mean duration of target antimicrobial treatment following PAF ( p < 0.001), and length of stay after PAF ( p < 0.05). Adherence category was not associated with mortality (log-rank = 0.58), readmission rate (log-rank p = 0.33), C. difficile DNA (log-rank p = 0.24) or C. difficile toxin (log-rank p = 0.084). Conclusions: Adherence to PAF reduces antimicrobial use and length of stay without creating harms, such as readmission. This shows that PAF can be beneficial, and future research should be tailored to increasing adherence to PAF recommendations.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".