Antibiotic Use at Planned Central Line Removal in Reducing Neonatal Post-Catheter Removal Sepsis: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Background: Post-catheter removal sepsis (PCRS) is a severe complication of indwelling central venous catheters (CVCs) in neonates, which is postulated to be secondary to the disruption of biofilms formed along catheter tips upon CVCs removal. It remains controversial whether antibiotic use upon CVCs removal will help to prevent this situation. We aimed to evaluate the protective effect of antibiotic administration at the time of CVCs removal in preventing PCRS in neonates. Methods: The systematic review was performed based on a registered protocol (CRD42022359677). We searched through PubMed, EMBASE and Cochrane databases, as well as reference lists of review articles (September 2022) for studies comparing the use of antibiotics versus no use within 12 hours of CVCs removal. Selection of studies and data extraction were performed independently by two researchers. Risk of bias was assessed using the modified Newcastle-Ottawa Scale or Cochrane risk-of-bias tool according to the study design. Results of quantitative analyses were presented as mean differences (MD) or odds ratio (OR). Subgroup and univariate meta-regression analyses were performed to identify heterogeneity. Results: The review included 470 central lines in the antibiotic group and 658 lines in the control group from five studies. Antibiotic use within 12 hours of CVCs removal did not significantly reduce the incidence of PCRS (OR=0.35, 95% CI: 0.08 to 1.53), but was associated with a lower incidence of post-catheter removal blood stream infection (OR=0.31, 95% CI: 0.11 to 0.86). Dosage of vancomycin and world region were major sources of interstudy heterogeneity. Conclusion: Antibiotic administration in neonates upon CVCs removal does not significantly reduce the incidence of PCRS but offers less post-catheter removal blood stream infection. Whether this will be converted to better clinical outcomes lacks evidential support. Further randomized controlled studies with longer follow-up are needed.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| 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".