162Antimicrobial Stewardship in the Micro Lab: Selective Susceptibility Reporting and Impact on Ciprofloxacin Utilization in a Hospital Setting
Bibliographic record
Abstract
Background. Resistance to ciprofloxacin has increased markedly over the past several years in response to increased prescribing. The objective of this study was to determine the impact of selective reporting of ciprofloxacin susceptibility on ciprofloxacin utilization as part of an antimicrobial stewardship program in a hospital setting. Methods. Our institution is a 375-bed community teaching hospital. Historically, the microbiology laboratory practice was to report ciprofloxacin susceptibility for all Enterobacteriaceae regardless of susceptibility to other agents. A selective reporting policy was created and implemented by the antimicrobial stewardship program in collaboration with the microbiology laboratory in February 2011. The policy involved the suppression (i.e., non-reporting) of ciprofloxacin susceptibility to Enterobacteriaceae when there was lack of resistance to the antibiotics on the gram negative panel. Ciprofloxacin utilization (measured by Defined Daily Doses (DDD)/1,000 patient days) 34 months before and 38 months after the intervention (policy implementation) was collected. An interrupted time series analysis was performed. Results. Pre-intervention (April 2008-Janurary 2011), ciprofloxacin utilization was 87.9 DDD/1,000 patient days. Following the intervention (February 2011 to January 2014), ciprofloxacin utilization decreased to 45.2 DDD/1,000 patient days. This represents an approximate 50% decrease (p < 0.0001) in ciprofloxacin utilization after selective ciprofloxacin susceptibility reporting. Conclusion. Selective reporting of ciprofloxacin antimicrobial sensitivity may result in a decrease of ciprofloxacin prescribing in a hospital setting when combined with a comprehensive antimicrobial stewardship program. Disclosures. All authors: No reported disclosures.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".