Use of a multivariable model to estimate the probability of discharge in hospitalized foals that are 7 days of age or less.
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.
Rohrbach
Barton W
BW
Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA.
Buchanan
Benjamin R
BR
Drake
Jennifer M
JM
Andrews
Frank M
FM
Bain
Fairfield T
FT
Byars
Douglas T
DT
Bernard
William V
WV
Furr
Martin O
MO
Paradis
Mary Rose
MR
Lawler
Jacquelin
J
Giguère
Steeve
S
Dunkel
Bettina
B
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