title: Probability-based compatibility curves for calcium and phosphates in parenteral nutrition formulations.
abstract: BACKGROUND
  The information content of the calcium phosphate compatibility curves for adult parenteral nutrition (PN) solutions may benefit from a more sophisticated statistical treatment. Binary logistic regression analyses were evaluated as part of an alternate method for generating formulation compatibility curves.
  
  
  METHODS
  A commercial PN solution was challenged with a systematic array of calcium and phosphate concentrations. These formulations were then characterized for particulates by visual inspection, light obscuration, and filtration followed by optical microscopy. Logistic regression analyses of the data were compared with traditional treatments for generating compatibility curves.
  
  
  RESULTS
  Assay-dependent differences were observed in the compatibility curves and associated probability contours; the microscopic method of precipitate detection generated the most robust results. Calcium and phosphate compatibility data generated from small-volume glass containers reasonably predicted the observed compatibility of clinically relevant flexible containers.
  
  
  CONCLUSIONS
  The published methods for creating calcium and phosphate compatibility curves via connecting the highest passing or lowest failing calcium concentrations should be augmented or replaced by probability contours of the entire experimental design to determine zones of formulation incompatibilities. We recommend researchers evaluate their data with logistic regression analysis to help build a more comprehensive probabilistic database of compatibility information.
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Thomas
authors.initials: T
authors.lastname: Gonyon
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Phillip W
authors.initials: PW
authors.lastname: Carter
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Gerald
authors.initials: G
authors.lastname: Phillips
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Heather
authors.initials: H
authors.lastname: Owen
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Dipa
authors.initials: D
authors.lastname: Patel
authors.affiliation: Baxter Healthcare, Round Lake, Illinois.
authors.forename: Priyanka
authors.initials: P
authors.lastname: Kotha
authors.affiliation: Baxter Healthcare, Round Lake, Illinois john_bruce_green@baxter.com.
authors.forename: John-Bruce D
authors.initials: JB
authors.lastname: Green
mesh_terms: D002118:Calcium / Q000032:analysis*; D002130:Calcium Phosphates / Q000032:analysis; D011232:Chemical Precipitation; D006863:Hydrogen-Ion Concentration; D016015:Logistic Models; D010288:Parenteral Nutrition; D057947:Parenteral Nutrition Solutions / Q000737:chemistry*; D010710:Phosphates / Q000032:analysis*; D011336:Probability
chemical_list: D002130:Calcium Phosphates; D057947:Parenteral Nutrition Solutions; D010710:Phosphates; C020243:calcium phosphate; D002118:Calcium
keywords: calcium phosphate; compatibility curves; experimental design; logistic regression; parenteral nutrition; particulate matter; precipitation