Continuous Versus Intermittent Vancomycin Infusions for Coagulase-negative Staphylococcus Bacteremia in Neonates: A Propensity-matched Cohort Study
Bibliographic record
Abstract
BACKGROUND: Coagulase-negative staphylococci (CONS) are a major cause of late-onset neonatal sepsis, particularly in preterm infants, with high morbidity and mortality. While vancomycin is the first-line treatment for these infections, the optimal administration in neonates remains uncertain. OBJECTIVE: We aim to compare the outcomes of neonates with CONS bacteremia treated with adjusted continuous infusion (CIV) versus standard intermittent infusion (IIV) of vancomycin. METHODS: This retrospective study included 110 neonates, with 29 in the CIV group and 47 in the IIV group after propensity score matching. The primary outcome was treatment failure defined by the persistence of a positive blood culture for the same organism after at least 48 hours of vancomycin treatment. RESULTS: After matching, the CIV group exhibited significantly lower treatment failure rates [5/29 (17%) vs. 26/47 (44%); P = 0.014] and a higher rate of achieving therapeutic vancomycin levels after 24 hours [20/29 (69%) vs. 26/47 (44%); P = 0.002] compared to the IIV group. No significant differences were observed in terms of acute kidney failure between the 2 groups. CONCLUSION: Adjusted continuous vancomycin infusion in neonates with CONS bacteremia is associated with a lower treatment failure rate without an increase in renal toxicity compared to standard intermittent infusion. However, due to the observational design, larger prospective studies are needed to validate these results.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".