Emergency Department Prescribing Patterns for Pharyngitis in Children
Bibliographic record
Abstract
Pharyngitis is commonly diagnosed in the emergency department (ED) and accounts for substantial antibiotic burden in pediatrics. This study describes ED patterns of group A streptococcal (GAS) pharyngitis diagnosis and antibiotic prescribing patterns. This was a secondary data analysis of the National Hospital Ambulatory Medical Care Survey. Diagnosis and antibiotic treatment for GAS and non-GAS (viral) pharyngitis were reported in all ages and specifically examined in children <3 years of age from 2010 to 2015. GAS pharyngitis was diagnosed in 29% of visits for children with pharyngitis; however, 60% of patients with any pharyngitis received antibiotics. Twenty percent of children <3 years were diagnosed with GAS pharyngitis, yet over half were given antibiotics. Broad-spectrum antibiotics were commonly prescribed. Antibiotic treatment of pharyngitis, including broad-spectrum antibiotics, remains high when compared with the known prevalence of GAS pharyngitis. Diagnosis and treatment of GAS pharyngitis in patients <3 years persists despite recommendations against testing.
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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".