Prolonged Beta-Lactam Infusions in Children: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: To assess whether beta-lactam extended or continuous beta-lactam infusions (EI/CI) improve clinical outcomes in children with proven or suspected bacterial infections. STUDY DESIGN: We included observational and interventional studies that compared beta-lactam EI or CI with standard infusions in children less than 18 years old, and reported on mortality, hospital or intensive care unit length of stay, microbiological cure, and/or clinical cure. Data sources included PubMed, Medline, EBM Reviews, EMBASE, and CINAHL and were searched from January 1, 1980, to November 3, 2023. Thirteen studies (2945 patients) were included: 5 randomized control trials and 8 observational studies. Indications for antimicrobial therapies and clinical severity varied, ranging from cystic fibrosis exacerbation to critically ill children with bacteriemia. RESULTS: EI and CI were not associated with a reduction in mortality in randomized control trials (n = 1464; RR 0.93, 95% CI 0.71, 1.21), but were in observational studies (n = 833; RR 0.43, 95% CI 0.19, 0.96). We found no difference in hospital length of stay. Results for clinical and microbiological cures were heterogeneous and reported as narrative review. The included studies were highly heterogeneous, limiting the strength of our findings. The lack of shared definitions for clinical and microbiological cure outcomes precluded analysis. CONCLUSIONS: EI and CI were not consistently associated with reduced mortality or length of stay in children. Results were conflicting regarding clinical and microbiological cures. More well-designed studies targeting high-risk populations are necessary to determine the efficacy of these alternative dosing strategies.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".