title: Validation of equations used to predict plasma osmolality in a healthy adult cohort.
abstract: BACKGROUND
  Plasma osmometry and the osmol gap have long been used to provide clinicians with important diagnostic and prognostic patient information.
  
  
  OBJECTIVE
  We compared different equations used for predicting plasma osmolality when its direct measurement was not practical or an osmol gap was of interest and identified the best performers.
  
  
  METHODS
  The osmolality of plasma was measured by using freezing point depression by microosmometer and osmolarity calculated from biosensor measures of select analytes according to the dictates of each formula tested. After a rigid analytic prescreen of 36 originally published equations, a bootstrap regression analysis was used to compare shrinkage and model agreement.
  
  
  RESULTS
  Sixty healthy volunteers provided 163 plasma samples for analysis. Of 36 equations considered, 11 equations met the prescreen variables for the bootstrap regression analysis. Of the 11 equations, 8 equations met shrinkage and apparent model error thresholds, and 5 equations were deemed optimal with an original model osmol gap <5 mmol.
  
  
  CONCLUSIONS
  The use of bootstrap regression provides a unique insight for osmolality prediction equation performance from a very large theoretical population of healthy people. Of the original 36 equations evaluated, 5 equations appeared optimal for the prediction of osmolality when its direct measurement was not practical or an osmol gap was of interest. Note that 4 of 5 optimal equations were derived from a nonhealthy population.
authors.affiliation: From the US Army Research Institute of Environmental Medicine, Natick, MA.
authors.forename: Kristen R
authors.initials: KR
authors.lastname: Heavens
authors.affiliation: From the US Army Research Institute of Environmental Medicine, Natick, MA.
authors.forename: Robert W
authors.initials: RW
authors.lastname: Kenefick
authors.affiliation: From the US Army Research Institute of Environmental Medicine, Natick, MA.
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Caruso
authors.affiliation: From the US Army Research Institute of Environmental Medicine, Natick, MA.
authors.forename: Marissa G
authors.initials: MG
authors.lastname: Spitz
authors.affiliation: From the US Army Research Institute of Environmental Medicine, Natick, MA.
authors.forename: Samuel N
authors.initials: SN
authors.lastname: Cheuvront
mesh_terms: D000328:Adult; D001827:Body Height; D001835:Body Weight; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009994:Osmolar Concentration; D010949:Plasma / Q000737:chemistry*; D012044:Regression Analysis; D015203:Reproducibility of Results; D055815:Young Adult