Use of a multivariable model to estimate the probability of discharge in hospitalized foals that are 7 days of age or less

Barton W. Rohrbach Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996.

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Benjamin R. Buchanan Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996.

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Jennifer M. Drake Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996.

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Frank M. Andrews Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996.

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Fairfield T. Bain Hagyard Equine Medical Institute, 4250 Iron Works Pike, Lexington, KY 40511.

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Douglas T. Byars Hagyard Equine Medical Institute, 4250 Iron Works Pike, Lexington, KY 40511.

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William V. Bernard Rood and Riddle Equine Hospital, 2150 Georgetown Rd, Lexington, KY 40511.

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Martin O. Furr Marion DuPont Scott Equine Medical Center, 17690 Old Waterford Rd at Morven Park, PO Box 1938, Leesburg, VA 20177.

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Mary Rose Paradis Department of Clinical Sciences, School of Veterinary Medicine, Tufts University, North Grafton, MA 01536.

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Jacquelin Lawler Peterson Smith Equine Hospital, 4747 Southwest 60th Ave, Ocala, FL 34474.

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Steeve Giguère Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL 32610.

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Bettina Dunkel New Bolton Center Campus, Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA 19348.

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Abstract

Objective—To create a mathematical model to assist in early prediction of the probability of discharge in hospitalized foals ≤ 7 days old.

Study Design—Prospective study.

Animals—1,073 foals.

Procedures—Medical records from 910 hospitalized foals ≤ 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 and Clinical Relevance—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.

Abstract

Objective—To create a mathematical model to assist in early prediction of the probability of discharge in hospitalized foals ≤ 7 days old.

Study Design—Prospective study.

Animals—1,073 foals.

Procedures—Medical records from 910 hospitalized foals ≤ 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 and Clinical Relevance—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.

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