title: Use of a multivariable model to estimate the probability of discharge in hospitalized foals that are 7 days of age or less.
abstract: OBJECTIVE
  To create a mathematical model to assist in early prediction of the probability of discharge in hospitalized foals < or= 7 days old.
  
  
  METHODS
  Prospective study.
  
  
  METHODS
  1,073 foals.
  
  
  METHODS
  Medical records from 910 hospitalized foals < or = 7 days old for which outcome was recorded as died or discharged alive were reviewed. Thirty-four variables including historical information, physical examination findings, and laboratory results were examined for association with survival. Variables associated with being discharged alive were entered into a multivariable logistic regression model. Accuracy of the model was validated prospectively on data from 163 foals.
  
  
  RESULTS
  Factors in the final model included age group, ability to stand, presence of a suckle reflex, WBC count, serum creatinine concentration, and anion gap. Sensitivity and specificity of the model to predict live discharge were 92% and 74%, respectively, in the retrospective population and 90% and 46%, respectively, in the prospective population. Accuracy of an equine clinician's initial prediction of the foal being discharged alive was 83%, and accuracy of the model's prediction was 81%. Combining the clinician's prediction of probability of live discharge with that of the model significantly increased (median increase, 12%) the accuracy of the prediction for foals that were discharged and nonsignificantly decreased (median decrease, 9%) the accuracy of the predication for nonsurvivors.
  
  
  CONCLUSIONS
  Combining the clinician's initial predication of the probability of a foal being discharged alive with that of the model appeared to provide a more precise early estimate of the probability of live discharge for hospitalized foals.
authors.affiliation: Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA.
authors.forename: Barton W
authors.initials: BW
authors.lastname: Rohrbach
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Buchanan
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Drake
authors.forename: Frank M
authors.initials: FM
authors.lastname: Andrews
authors.forename: Fairfield T
authors.initials: FT
authors.lastname: Bain
authors.forename: Douglas T
authors.initials: DT
authors.lastname: Byars
authors.forename: William V
authors.initials: WV
authors.lastname: Bernard
authors.forename: Martin O
authors.initials: MO
authors.lastname: Furr
authors.forename: Mary Rose
authors.initials: MR
authors.lastname: Paradis
authors.forename: Jacquelin
authors.initials: J
authors.lastname: Lawler
authors.forename: Steeve
authors.initials: S
authors.lastname: Giguère
authors.forename: Bettina
authors.initials: B
authors.lastname: Dunkel
mesh_terms: D000367:Age Factors; D000818:Animals; D000831:Animals, Newborn / Q000502:physiology*; D016001:Confidence Intervals; D005260:Female; D006734:Horse Diseases / Q000401:mortality*; D006736:Horses; D006762:Hospitals, Animal / Q000706:statistics & numerical data*; D016013:Likelihood Functions; D008297:Male; D008433:Mathematics; D015233:Models, Statistical; D015999:Multivariate Analysis; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012044:Regression Analysis; D012720:Severity of Illness Index; D016019:Survival Analysis