1795Above and Beyond Individual Exposure: Ward-level Antibiotic Prescribing Is the Principal Predictor of Increased Clostridium difficile Infection (CDI) Risk
Bibliographic record
Abstract
Background. Recent research on Clostridium difficile transmission suggests that exposure to spores from symptomatic patients may not completely explain hospital-acquired infections. Antibiotic exposure has been shown to be a primary risk factor for not only C. difficile infection (CDI), but also for asymptomatic colonization with C. difficile. In this study, we sought to discern the relative impacts of individual-level and ward-level antibiotic exposure on patient risk. Methods. A cohort study design was used to assess the association of antibiotic exposure with the incidence of CDI among patients admitted to Sunnybrook hospital in Toronto, Canada. The source cohort consisted of all patients over 18 years old, without a previous CDI diagnosis, and hospitalized in an acute care ward at Sunnybrook hospital in a period spanning June 1, 2010 to May 31, 2012 (n = 47,241). Results. Across wards, patients received antibiotics for 22% to 58% of days. We found that ward-level prescribing was strongly associated with increased CDI risk. Based on weighted linear regression, each 10% increase in ward-level ABx prescribing was associated with a 3.9 per 1,000 patient-days (95% CI: based on weighted linear regression: 2.1 to 5.6, p < 0.001) increase in CDI incidence, and explained 56% of ward level variation in CDI rates (figure). In multilevel Poisson analyses controlling for time since admission, age, individual-level antibiotic receipt, previous hospitalizations, infection pressure, and ICU admission, ward-level antibiotic prescribing was the strongest predictor of CDI risk. Each 10% increase in ward-level ABx prescribing was associated with a doubling of risk (RR = 1.83, 95% CI: 1.42 to 2.35); adjusted risk in the highest prescribing wards was thus 6 times higher (RR = 6.13, 95% CI: 2.86 to 12.98) than risk in the lowest prescribing wards. In comparison, individual-level exposure was associated with only a doubling of risk (RR = 2.06, 95% CI: 1.37 to 3.10). Conclusion. Although many studies have considered the impact of individual-level risk factors on CDI, we found that ward-level antibiotic prescribing better explains CDI risk, and this suggests that asymptomatic colonized patients may be driving infection spread. This research has major implications for infection control, hospital hygiene, and antimicrobial stewardship. 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".