Clinical outcomes in patients admitted to a hospitalist service exposed to an antimicrobial stewardship program – a retrospective matched cohort study
Bibliographic record
Abstract
Given global issues with antimicrobial resistance and a need to optimize antimicrobial usage, antimicrobial stewardship (AS) programs are becoming a necessary component of hospitals and are increasingly mandated worldwide. It is important to evaluate these programs with respect to relevant clinical outcomes. An AS program with a prospective audit and feedback service (PAF) of antimicrobial usage was initiated May 11, 2015 at our tertiary care center, for patients admitted under the hospitalist service. We conducted a retrospective matched cohort study. Patients assessed during the first year of this PAF were considered to be the exposed cohort and were compared to unexposed controls matched on gender, age and infectious diagnosis selected from patients who had been admitted under the hospitalist service prior to initiation of the PAF. Descriptive analysis was completed and a multivariate conditional logistic regression was performed to analyze differences between the exposed and control groups in terms of a composite endpoint of 30 day mortality, 30 day post hospital discharge mortality and hospital re-admission. A total of 348 patients were assessed and received PAF suggestions during the first year were compared to 827 matched control patients who did not receive PAF suggestions. Of 707 PAF suggestions made, the most common was to stop an antimicrobial (23%). A significantly lower (20.7% vs 28.8%, p = 0.008) composite endpoint was found in the group exposed to the PAF (OR 0.71 95%CI 0.52–0.97). This difference persisted when only patients with PAF suggestions that were completely or partially accepted were considered (18.6% vs 28.5%, p = 0.001) but was no longer significant when patients who had their ASP suggestions declined were analyzed (30.2% vs 26.7%, p = 0.610). In this retrospective cohort study, patient admissions in which PAF recommendations were accepted had better clinical outcomes than matched historical controls managed in the absence of this AS service.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".