Back to Search
Start Over
An International Prospective Cohort Study To Validate 2 Prediction Rules for Infections Caused by Third-generation Cephalosporin-resistant Enterobacterales
- Publication Year :
- 2021
-
Abstract
- [Background] The possibility of bloodstream infections caused by third-generation cephalosporin-resistant Enterobacterales (3GC-R-BSI) leads to a trade-off between empiric inappropriate treatment (IAT) and unnecessary carbapenem use (UCU). Accurately predicting 3GC-R-BSI could reduce IAT and UCU. We externally validate 2 previously derived prediction rules for community-onset (CO) and hospital-onset (HO) suspected bloodstream infections.<br />[Methods] In 33 hospitals in 13 countries we prospectively enrolled 200 patients per hospital in whom blood cultures were obtained and intravenous antibiotics with coverage for Enterobacterales were empirically started. Cases were defined as 3GC-R-BSI or 3GC-R gram-negative infection (3GC-R-GNI) (analysis 2); all other outcomes served as a comparator. Model discrimination and calibration were assessed. Impact on carbapenem use was assessed at several cutoff points.<br />[Results] 4650 CO infection episodes were included and the prevalence of 3GC-R-BSI was 2.1% (n = 97). IAT occurred in 69 of 97 (71.1%) 3GC-R-BSI and UCU in 398 of 4553 non–3GC-R-BSI patients (8.7%). Model calibration was good, and the AUC was .79 (95% CI, .75–.83) for 3GC-R-BSI. The prediction rule potentially reduced IAT to 62% (60/97) while keeping UCU comparable at 8.4% or could reduce UCU to 6.3% (287/4553) while keeping IAT equal. IAT and UCU in all 3GC-R-GNIs (analysis 2) improved at similar percentages. 1683 HO infection episodes were included and the prevalence of 3GC-R-BSI was 4.9% (n = 83). Here model calibration was insufficient.<br />[Conclusions] A prediction rule for CO 3GC-R infection was validated in an international cohort and could improve empirical antibiotic use. Validation of the HO rule yielded suboptimal performance.
Details
- Database :
- OAIster
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1333185023
- Document Type :
- Electronic Resource