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A New Model for Non-Lipid Compounded Neonatal Parenteral Nutrition Solution Osmolality
Sivan Borenstein1, Ellen Mack1, Katherine Palmer2
1Department of Pediatrics, Cedars-Sinai Medical Center, Los Angeles, California, USA.
JPEN. Journal of Parenteral and Enteral Nutrition
|August 23, 2018
Summary
Calculated osmolarity underestimates parenteral nutrition (PN) osmolality. A new algorithm accurately predicts PN osmolality, aiding in preventing adverse events in neonates.
Area of Science:
- Neonatal intensive care
- Parenteral nutrition
- Clinical chemistry
Background:
- Osmotic stress from parenteral nutrition (PN) can cause adverse events like infiltration.
- Accurate prediction of PN osmolality is crucial for neonatal safety.
- Current methods may underestimate the true osmolality of compounded PN solutions.
Purpose of the Study:
- To improve the prediction of compounded PN osmolality.
- To test if calculated osmolarity underestimates measured osmolality in PN.
- To develop a predictive algorithm using North American neonatal PN components.
Main Methods:
- Calculated osmolarity using commercial software.
- Measured osmolality via freezing-point depression micro-osmometry.
- Developed regression models correlating calculated osmolarity with measured osmolality.
Main Results:
- Calculated osmolarity significantly underestimated measured osmolality in 363 PN samples.
- A polynomial regression model was developed, achieving R² = 0.99367 for osmolality prediction.
- The model effectively corrected for the osmolal gap, considering solute behavior and interactions.
Conclusions:
- Calculated osmolarity underestimates compounded PN osmolality.
- A novel algorithm accurately predicts PN osmolality using commercial software data and neonatal nutrient solutions.
- This algorithm can support research on PN osmolality's role in adverse events and safe concentration thresholds for neonates.
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