Understanding the Impact of Narrow Spectrum Beta-Lactam Use on Overall and Broad-Spectrum Antimicrobial Utilization in South Carolina
Bibliographic record
Abstract
Background: The standardized antimicrobial administration ratio (SAAR) is a metric utilized to measure antimicrobial use within and between hospitals by comparing observed to predicted antimicrobial days of therapy. However, it remains unknown whether narrow-spectrum beta-lactam (NSBL) use adds to overall antimicrobial utilization or substitutes broad-spectrum agents. This muti-hospital cohort study examined the impact of NSBL use on overall antimicrobial utilization and the correlation between the use of NSBL and various broad-spectrum antimicrobial categories in South Carolina (SC) hospitals. Methods: SAARs were collected from all hospitals in SC that reported antimicrobial use (AU) data to the National Healthcare Safety Network (NHSN) between 2017 and 2021. SAARs collected included: overall SAAR, broad-spectrum agents predominantly used for hospital-onset infections (BSHO), broad-spectrum agents predominantly used for community-acquired infections (BSCA), NSBL, and antibacterial agents posing the highest risk for Clostridioides difficile infection (CDI). Category SAARs were combined to include data in both the adult intensive care unit (ICU) and adult wards using the formula: [(total observed antimicrobial days ICU + total observed antimicrobial days ward) / (total predicted antimicrobial days ICU + total predicted antimicrobial days wards)]. Pearson correlation coefficient (r) was used to examine the correlation between various SAARs categories. Results: A total of 38 hospitals in South Carolina reported AU to NHSN at least during one calendar year during the study period. The use of NSBL agents was negatively correlated with the use of BSHO (r = -0.596, p < 0.001), BSCA (r = -0.543, p < 0.001), and high-risk CDI antibiotics (r = -0.601, p < 0.001). Moreover, the use of NSBL agents did not correlate with the overall SAAR (r = 0.008, p = 0.93), whereas the use of BSHO (r = 0.587, p < 0.001), BSCA (r = 0.494, p < 0.001), and high-risk CDI agents (r = 0.464; p < 0.001) positively correlated with the overall SAAR. Conclusion: In South Carolina hospitals, the use of NSBLs does not contribute to additional antibiotic use overall as it seems to replace broad-spectrum antimicrobials in various categories. By de-escalating from broad-spectrum agents to NSBL agents, one can improve antimicrobial use without negatively impacting the overall SAAR. This observation encourages implementation of antimicrobial stewardship interventions that increase utilization of NSBLs, when appropriate, such as de-escalation of antimicrobial therapy among others without concerns for increasing the SAAR for overall antibiotic use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".