Solid organ transplant patients: are there opportunities for antimicrobial stewardship?
Bibliographic record
Abstract
OBJECTIVE: Rising incidence of Clostridium difficile and multidrug-resistant organisms' infections and a dwindling development of new antimicrobials are an impetus for antimicrobial stewardship in organ transplant recipients. We sought to understand antimicrobial prescribing practices and identify opportunities for interdisciplinary collaboration among the transplant, antimicrobial stewardship, and infectious diseases teams. METHODS: In 2013, two assessors conducted four real-time audits on all antimicrobial therapy in transplant patients, assessing each regimen against stewardship principles established by the Centers for Disease Prevention and Control, supplemented by applicable transplant-specific infection guidelines. Chi-square test was used to compare stewardship-concordant and stewardship-discordant audit results relative to transplant infectious diseases consultation. RESULTS: Analysis was performed on 176 audits. Fifty-eight percent (103/176) received at least one antimicrobial, of which 69.9% (72/103) were stewardship-concordant. Infections were confirmed or suspected in 52.3% (92/176). Of those, 98.9% (91/92) received antimicrobials, and 41.8% (38/91) were prescribed by transplant clinicians. Infectious diseases consultation was associated with more stewardship-concordant prescriptions (78.5% vs. 59.6%, p = 0.03). The most common stewardship-discordant categories were lack of de-escalation, empiric antimicrobial spectrum being too broad, and therapy duration being too long. CONCLUSIONS: Opportunities exist for antimicrobial stewardship in transplant recipients, especially those who do not require infectious diseases consultation.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".