Developing a Tool for Prospective Assessment of Treatment Appropriateness in Urinary Tract Infections
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Antimicrobial resistance is an increasingly serious threat to global public health. Antimicrobial stewardship programs need to identify inappropriate antibiotic use patterns and offer practical recommendations to prescribers and institutions. Urinary tract infection (UTI) is a common syndrome for which a standardized tool would be useful when treatment appropriateness is assessed. To date, few UTI treatment assessment tools have been published, and the available tools do not support appropriateness assessment against published guidelines, or consistent adjudication from one auditor to another. Objective: To develop a tool for auditing UTI antibiotic therapy that assesses treatment appropriateness based on guideline concordance, and with high inter-rater reliability. Methods: An audit tool was developed iteratively by the local antimicrobial stewardship team. Two auditors used the tool to adjudicate treatment appropriateness in a sample of UTI cases against local treatment guidelines. Inter-rater agreement was estimated with Cohen’s kappa statistic. Results: The final design of the tool had individual sections for evaluating five aspects of treatment appropriateness, depending on the stage at which a patient was in his or her course of antibiotic therapy: diagnosis, empiric therapy, culture-directed therapy, route of antimicrobial administration, and duration of therapy. A total of 50 cases were assessed; among these, the two auditors agreed on 45 cases (90% agreement). The estimated kappa was 0.8. Conclusion: A unique tool with substantial inter-rater agreement was developed for assessing appropriateness of antimicrobial therapy in UTI. The process and design features that were outlined can be adapted by other antimicrobial stewardship programs to monitor antimicrobial use and improve quality of care.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it