Antibiotic Prescriptions for Children With Community-acquired Pneumonia: Findings From Italy
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: Community-acquired pneumonia (CAP) is one of the most common reasons of prescribing antibiotics for children, often with overuse of broad-spectrum antibiotics. The aim of this study is to describe the antibiotic prescriptions for Italian children with CAP, at the primary care level. STUDY DESIGN: Retrospective cohort study conducted among children 3 months-14 years of age with CAP, enrolled in Pedianet (http://www.pedianet.it) from January 1, 2009 to December 31, 2018. Antibiotic treatment was defined as narrow-spectrum (NS-ABT) if amoxicillin and broad-spectrum (BS-ABT) if amoxicillin/clavulanic acid, cephalosporins or any combination. Crude and adjusted logistic regressions for the odds of receiving NS-ABT were conducted (all episodes of CAP and per patient). A P value <0.05 was considered statistically significant. RESULTS: Among 9691 CAP, 7260 episodes from 6409 children followed by 147 pediatricians were analyzed. The 16.7% of CAP [1216/7260, 95% confidence interval (CI): 15.9%-17.6%] received an NS-ABT while 53.3% (3863/7260, 95% CI: 52%-54.4%) received BS-ABTs and 30% (2181/7260, 95% CI: 28.9%-31.1%) macrolides. Within 10 years, a slight but increasing trend of NS-ABT prescription was observed (P < 0.001). Factors independently associated with reduced odds of receiving an NS-ABT compared with BS-ABT including macrolides were being older than 5 years [odds ratio (OR) 0.45, 95% CI: 0.39-0.52], living in Central/Southern Italy (OR 0.13, 95% CI: 0.10-0.16) and being exposed to ABT 3 months before (OR 0.61, 95% CI: 0.53-0.70). These findings were confirmed comparing NS-ABT versus BS-ABT excluding macrolides (n = 5079) and when the analysis was limited to index CAP. CONCLUSION: Our findings report a very limited prescription of narrow-spectrum antibiotics for Italian children with CAP.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".