Quality of antibiotic prescribing for outpatient cystitis in adult females
Bibliographic record
Abstract
Background: Urinary tract infections (UTI) are responsible for a significant portion of female, outpatient antibiotic prescriptions. Especially true in uncomplicated cases, where symptoms remain the cornerstone of diagnosis, ensuring the optimal choice of agent, dose, and duration may mitigate future bacterial resistance and lower the likelihood of adverse events and/or recurrence. This study is the first in Canada to examine the quality of antibiotic prescribing to females in the outpatient setting, for uncomplicated UTI-by agent, dose, and duration. Methods: All adult female residents of British Columbia with a physician record for cystitis from January 1, 2014, to December 31, 2018, were identified. Patients with a history of urologic abnormalities, spinal cord injury, catheter use, kidney transplant, as well as pregnant females, were excluded. Primary outcomes included the proportion of total episodes prescribed and the proportion of appropriate antibiotic use, examined using Poisson regression. Results: A total of 182,162 episodes of cystitis were examined, with 70% receiving an antibiotic prescription. The rate of cystitis-associated prescribing was 697 prescriptions per 1,000 population. Overall, 35% of prescriptions were appropriate by guideline adherence or clinical justification. Nitrofurantoin and trimethoprim-sulfamethoxazole, accounted for 71% of total antibiotic use. Seven days was the most commonly dispensed duration of therapy, followed by 5, then 10. Conclusions: Shortening length of therapy in line with clinical guidelines and encouraging the use of first line agents present clear, actionable targets for provincial stewardship efforts.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".