Antibiotic use in hospitalized children: current practices and the impact of virus diagnostic testing on antibiotic-related decisions
Bibliographic record
Abstract
Antibiotic overuse and bacterial resistance are major public health threats. This problem is particularly important in the hospital setting, especially in intensive care units. Factors contributing to antibiotic overuse are the lack of evidence-based criteria to guide antibiotic treatment duration for patients with bacterial infections, and the difficulty in differentiating between viral and bacterial acute respiratory infections (ARIs).It is currently unclear which criteria physicians use to tailor the duration of antibiotic therapy. We hypothesized that antibiotic use in pediatric intensive care units (PICUs) is based on criteria not always supported by evidence. Our first objective was therefore to describe the determinants of antibiotic use in PICUs across eight countries (Canada, the US, Saudi Arabia, Italy, Thailand, France, Japan, and Brazil). Our international survey results showed that physicians in all countries would prolong antibiotic duration based on patient characteristics, disease severity, pathogens, and infectious radiologic findings, ranging from a median increase of 1.75 (95% confidence interval [CI] 0.5, 4.0) to 9.5 (95%CI 8.5, 10.5) days. Importantly, physicians would prolong treatment duration based on non-reassuring characteristics including younger age, severe disease, and hospital-acquired infections, even if current literature does not support the use of these criteria. Physicians in Saudi Arabia, Thailand, and Brazil would recommend longer antibiotic courses than in Canada and France for patients with severe disease. Lastly, we found that a high proportion of physicians would still use a full course of antibiotics in patients with a positive viral test result, except in France, suggesting that local culture and context may influence the clinical utility of viral tests.Another factor driving antibiotic overuse in hospitalized children is the frequent use of antibiotics for viral ARIs, as viral and bacterial ARIs are often clinically indistinguishable. Respiratory virus (RV) diagnostic tests are commonly used in children hospitalized with ARI, but current literature regarding their clinical utility to reduce antibiotic use is conflicting. We hypothesized that the use of RV tests decreases unnecessary antibiotic use in this patient population. Our second objective was therefore to conduct a systematic review and meta-analysis to determine the impact of RV testing on antibiotic consumption, as well as on the use of ancillary testing, length of hospital stay, and use of influenza antivirals in children hospitalized with ARI. We included 23 studies, of which 19 (83%) were at serious risk of bias. Pooled results showed no difference in antibiotic prescription between patients with a positive vs. negative RV test result (odds ratio [OR] 0.84; 95% confidence interval [CI] 0.65,1.09). Analysis stratified by study design showed that RV testing decreased antibiotic use in prospective cohort studies (OR 0.58; 95%CI 0.45, 0.75). Pooled results showed no impact on use of chest x-rays (OR 0.71; 95%CI 0.48, 1.04).In conclusion, this thesis identified several antibiotic practices that may be associated with unnecessary antibiotic use in pediatric patients. We showed that physicians tend to overuse antibiotics by prolonging treatment duration in the face of non-reassuring clinical characteristics. In addition, while our meta-analysis did not find an impact of viral testing on antibiotic use, our survey showed that such tests may potentially be clinically useful depending on the local culture and context. Importantly, our results support the need for validated and evidence-based criteria to diagnose infections and guide treatment duration, in order to reduce unnecessary exposure to antibiotics in hospitalized children
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 | 0.002 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".