Drug use evaluation (DUE) of ceftriaxone: A quality metric in a pediatric hospital
Bibliographic record
Abstract
Background: Ceftriaxone is frequently used as empiric therapy because of its broad spectrum and dosing characteristics. The purpose of this study was to evaluate the appropriateness of ceftriaxone therapy among hospitalized children using drug use evaluation (DUE) methodology. Methods: Hospitalized patients who received one or fewer dose of intravenous ceftriaxone at Children's Hospital of Eastern Ontario between January 1, 2018, and June 30, 2018, were identified. Duration was defined as empiric if 72 or less and definitive if more than 72 hours. Two infectious disease physicians reviewed the charts and rated appropriateness using a previously developed scale. Results: A total of 276 ceftriaxone courses in 248 patients (mean age 6.0 y) were reviewed. Of these, 153 (55.4%) were assessed as definitively or possibly indicated. The most common reason for inappropriate empiric use was an overly broad spectrum. Of the 120 courses given empirically for which there was no indication, the three most common reasons were lower respiratory infections (51; 42.5%), head and neck infections (18; 15.0%), and intra-abdominal infections (15; 12.5%). Of the 39 (14.1%) courses of ceftriaxone that were given for more than 72 hours, 14 (35.9%) met criteria for a definitive or possible indication. Conclusion: Ceftriaxone is still overused as empiric therapy. Although 85% of courses were discontinued after three doses, 14% were continued for longer than 72 hours, with approximately one-third ultimately meeting an indication. DUE using Canadian pediatric and local guidelines criteria is useful to identify clinical presentations for which narrower spectrum antimicrobials should be used.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".