P-1682. Evaluation of Antibiotic Prescribing Practices for Pediatric Acute Otitis Media and Community-Acquired Pneumonia in an Emergency Department
Bibliographic record
Abstract
Abstract Background Acute otitis media (AOM) and community-acquired pneumonia (CAP) are common reasons for antibiotic prescriptions in children. As a result, antimicrobial stewardship efforts ensuring evidence-informed antibiotic prescriptions may be impactful. The objective of this study was to assess whether antibiotic prescriptions for AOM and CAP in a pediatric emergency department (ED) are consistent with current guidelines, and to identify opportunities for improvement. Duration of antibiotics prescribed for acute otitis media Bar graph depicting prescribed durations of therapy for acute otitis media, Prescriptions consistent with current guideline recommendations are in blue, while those that aren’t are in orange. Guidelines advise 10 days, rather than 5 days, of antibiotic therapy for children <2, perforated otitis media, treatment failure and recurrent otitis media. Methods We conducted a retrospective review of outpatient antibiotic prescriptions for AOM and CAP in the ED of a pediatric hospital from September 2022 to September 2023. Patients ages 0 – 18 years discharged from the ED with a diagnosis of AOM or CAP were identified using the electronic medical record system. Exclusion criteria included absence of a new antibiotic prescription, concomitant infections requiring antibiotic treatment, hospital admission, and patients with immunocompromising conditions or medications. Prescriptions were considered consistent with guidelines if they followed the Canadian Paediatric Society recommendations. Descriptive statistics were used for analysis. Duration of antibiotics prescribed for community-acquired pneumonia Bar graph depicting prescribed durations of therapy for community-acquired pneumonia. Prescriptions consistent with current guideline recommendations are in blue, while those that aren’t are in orange. Results A total of 1143 and 765 cases of AOM and CAP were included, respectively. Of the prescriptions for AOM, 688 (60%) were consistent with current guidelines. The 454 prescriptions that were not guideline-consistent were due to duration (n=281, 62%, Figure 1), dosing interval (n=142, 31%), antibiotic selection (n=74, 16%), and dose (n=38, 8.4%). Deferred prescriptions were provided to 177 (16%) patients; an additional 139 (12%) were eligible, but prescribed treatment. For CAP, 146 (19%) prescriptions were consistent with current guidelines. Of the 618 prescriptions that were not consistent, the majority were due to duration (n=576, 92%, Figure 2), dosing interval (n=134, 22%), antibiotic selection (n=38, 6%) and dose (n=14, 2%). Conclusion A significant number of patients with AOM (40%) and CAP (79%) were given antibiotic prescriptions that were not consistent with current guideline recommendations, with the most common reason being prolonged duration. This identifies an important antimicrobial stewardship opportunity in the ED and likely other outpatient settings. Disclosures Kathryn E. Timberlake, PharmD, Avir Pharma: Advisor/Consultant|Sanofi: Honoraria|Wolters Kluwer: Advisor/Consultant
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".