Quality of antibiotic prescribing for pediatric community-acquired Pneumonia in outpatient care
Bibliographic record
Abstract
BACKGROUND: Antibiotics remain the primary treatment for community acquired pneumonia (CAP), however rising rates of antimicrobial resistance may jeopardize their future efficacy. With higher rates of disease reported in the youngest populations, effective treatment courses for pediatric pneumonia are of paramount importance. This study is the first to examine the quality of pediatric antibiotic use by agent, dose and duration. METHODS: A retrospective cohort study included all outpatient/primary care physician visits for pediatric CAP (aged < 19 years) between January 1 2014 to December 31 2018. Relevant practice guidelines were identified, and treatment recommendations extracted. Amoxicillin was the primary first-line agent for pediatric CAP. Categories of prescribing included: guideline adherent, effective but unnecessary (excess dose and/or duration), under treatment (insufficient dose and/or duration), and not recommended. Proportions of attributable-antibiotic use were examined by prescribing category, and then stratified by age and sex. RESULT(S): A total of 42,452 episodes of pediatric CAP were identified. Of those, 31,347 (76%) resulted in an antibiotic prescription. Amoxicillin accounted for 51% of all prescriptions. Overall, 27% of prescribing was fully guideline adherent, 19% effective but unnecessary, 10% under treatment, and 44% not recommended by agent. Excessive duration was the hallmark of effective but unnecessary prescribing (97%) Macrolides accounted for the majority on non-first line agent use, with only 32% of not recommended prescribing preceded by a previous course of antibiotics. CONCLUSION(S): This study is the first in Canada to examine prescribing quality for pediatric CAP by agent, dose and duration. Utilizing first-line agents, and shorter-course treatments are targets for stewardship.
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 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 | 0.001 | 0.001 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".