Oral Antimicrobial Agents for Urinary Tract Infections Due to Enterobacteriales Species
Bibliographic record
Abstract
Background Urinary tract infections (UTIs) due to Enterobacteriales continue to pose a challenge because of increasing resistance rate to antimicrobial agents. The aim of this study was to evaluate in vitro susceptibility of oral antimicrobial agents against urinary isolates of Enterobacteriales species in patients with suspected UTIs at Hamilton Health Sciences hospitals in 2016. Methods Positive urine cultures for Enterobacteriales species in all patients 18 years or older with diagnosis of UTIs from 2 acute care hospitals in 2016 were included. Susceptibility rates were calculated for first- and second-line oral antimicrobial agents commonly used to treat UTIs. Results A total of 2773 urinary isolates of Enterobacteriales species were included in the analysis. The rates of susceptibility to nitrofurantoin were 96.3% (1925/1999) and 46.9% (188/401), respectively, for Escherichia coli and Klebsiella pneumoniae . The rates of susceptibility to trimethoprim-sulfamethoxazole and ciprofloxacin were 73.9% (1478/1999) and 84% (337/401), and 72.3% (1446/1999) and 86.3% (346/401), respectively, for E. coli and K. pneumoniae . The rate of E. coli susceptibility to oral cephalosporins was approximately 83%. The proportions of Enterobacteriales isolates that produced extended-spectrum β-lactamases (ESBLs) for E. coli and K. pneumoniae were 11.6% (231/1999) and 11.2% (45/401), respectively. The rates of ESBLs E. coli susceptibility to nitrofurantoin, trimethoprim-sulfamethoxazole, and ciprofloxacin were 91.3% (211/231), 30.3% (70/231), and 16% (37/231), respectively. Conclusions Oral antimicrobial agents have a limited role as empiric treatment of UTIs due to antibiotic-resistant Enterobacteriales species, with the exception of nitrofurantoin for E. coli including ESBL-producing strains. Oral cephalosporins were the second most susceptible agents to E. coli .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".