Tackling antimicrobial resistance in lower urinary tract infections: treatment options
Bibliographic record
Abstract
INTRODUCTION: Urinary tract infections (UTIs) are among the most common infectious diseases occurring in either the community or healthcare settings. A wide variety of bacteria are responsible for causing UTIs, however extra-intestinal pathogenic E. coli or ExPEC) remains the most common etiological agent. Since 2000, resistance to antibiotics emerged globally among ExPEC and is causing delays in appropriate therapy with subsequent increased morbidity and mortality. AREAS COVERED: The aim of this review article is to provide an overview on the definitions, etiology, treatment guidelines (including agents for infections due to antimicrobial resistant bacteria) of lower UTIs and to highlight recent aspects on antimicrobial resistance of ExPEC. Expert commentary: For patients with acute uncomplicated lower UTIs, nitrofurantoin, trimethoprim-sulfamethoxazole, fosfomycin or pivmecillinam should be prescribed for a 1-5 day course depending on the agent used. Single-dose fosfomycin is an excellent option for uncomplicated lower UTIs and has had similar clinical and/or bacteriological efficacy for 3- or 7-day regimens for alternate agents (i.e., ciprofloxacin, norfloxacin, cotrimoxazole or nitrofurantoin).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".