Does decreasing the frequency of changing intravenous administration sets (>24 h) increase the incidence of sepsis in neonates receiving total parenteral nutrition?
Bibliographic record
Abstract
BACKGROUND: The optimal timing for changing intravenous (IV) administration sets that contain total parenteral nutrition (TPN), with and without lipids, in neonates remains unknown. OBJECTIVE: To determine whether decreasing the frequency of changing IV administration sets (>24 h versus every 24 h) in neonates increases the incidence of sepsis within seven days of discontinuation of TPN and microbial contamination of the infusate. METHODS: The databases searched to identify studies that evaluated the frequency of IV administration sets on sepsis and microbial contamination of the infusate included MEDLINE, EMBASE, CINAHL, Cochrane Library, Scopus and Web of Science. The Evidence Evaluation Worksheet adapted from the American Heart Association's International Liaison Committee on Resuscitation was used to evaluate eligible studies for quality, level of evidence and direction of support. RESULTS: Two studies were reviewed; however, neither of the studies reported on the outcome of sepsis. One study reported that changing IV administration sets every 48 h did not increase the rate of infusate (amino acid or lipid) contamination compared with change every 24 h, while the other study reported an increase in the lipid infusate contamination rate when IV administration sets were changed every 72 h. CONCLUSIONS: There is insufficient evidence to support or refute routinely changing IV administration sets every 48 h or that decreasing the frequency of set changes increases the incidence of sepsis.
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 | 0.010 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".