Acute Uncomplicated Cystitis in an Era of Increasing Antibiotic Resistance: A Proposed Approach to Empirical Therapy
Bibliographic record
Abstract
Acute uncomplicated lower urinary tract infection (cystitis) is one of the most common and easily cured bacterial infections in women. However, increasing antibiotic resistance complicates its treatment by increasing patient morbidity, costs of reassessment and retreatment, rates of hospitalization, and use of broader-spectrum antibiotics. Guidelines published in 1999 by the Infectious Diseases Society of America (IDSA) recommend trimethoprim-sulfamethoxazole (TMP-SMX) as first-line treatment for acute cystitis—noting, however, that resistance to this agent is increasing [1]. Although public health authorities have increasingly recommended narrow-spectrum antibiotics for treating community-acquired respiratory and urinary tract infections (UTIs) whenever possible, concerns about resistance have resulted in a burgeoning use of fluoroquinolones. In the past few years, use of fluoroquinolones (overall and for UTIs) in ambulatory care has dramatically increased, whereas use of TMP-SMX for UTIs has decreased [2–4]. If trends in the use of fluoroquinolones continue, this crucial class of drugs is likely to become less effective, not only for treating respiratory and urinary tract infections, but also for treating foodborne infections, sexually transmitted diseases, and health care—associated infections.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".