Association between mixed oil lipid emulsions and all‐cause infections relative to soybean oil lipid emulsions in hospitalized adults: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Intravenous lipid emulsions are a key component of parenteral nutrition, and their fatty acid compositions may influence immune responses and clinical outcomes. METHODS: This retrospective cohort study conducted from January 2020 to December 2022 compared clinical outcomes of hospitalized non-critical care patients receiving parenteral nutrition with either mixed oil or soybean oil lipid emulsions for at least 48 h. The primary outcome was a composite of the presence of pneumonia, urinary tract infection, or an intra-abdominal collection diagnosed within 14 days of initiating parenteral nutrition. Secondary outcomes included catheter-related bloodstream infection, length of hospital stay, duration of antibiotic therapy, in-hospital mortality, and changes in the aspartate transaminase (AST)/alanine transaminase (ALT) ratio over time. RESULTS: Among 266 patients (mixed oil lipid emulsion: n = 130; soybean oil lipid emulsion: n = 136) there was no statistically significant difference in all-cause infections (P = 0.21). In patients receiving lipid emulsions for >7 days, the use of mixed oil lipid emulsions was associated with a shorter median antibiotic duration (4 days: interquartile range [IQR] 1-8.5 vs 7 days: IQR 5-10; P = 0.04). Additionally, patients who received mixed oil emulsions for >7 days had a significantly greater change in the AST/alkaline phosphatase ratio after 14 days compared with the soybean oil group (β = -0.51; P = 0.02). CONCLUSION: Although there was no difference in all-cause infections between types of lipid emulsions, mixed oil lipid emulsions were associated with shorter antibiotic use and lower AST/ALT ratio in hospitalized, non-critical care patients receiving parenteral nutrition for >7 days.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".