The cost of hospitalization for neonatal foals is high because of the intensive treatment, cost of equipment necessary to monitor patients, and time commitment of hospital personnel. An estimate of the cost of daily care in 1998 at a university referral hospital ranged from $250 to > $1,000/d.1 The time required for treatment and monitoring of neonatal foals can range from a few hours up to 24 h/d. It is therefore imperative that accurate quantitative information regarding the probability for survival be provided to clients early in the course of hospitalization so they can make informed choices regarding case management options. Along with the quantitative probability of survival, the decision to treat may also be based on the estimated cost of treatment, value of the foal, effect of the condition on future performance, and personal priorities of the client.
Clinicians can make an initial estimate of the probability of survival in neonatal foals by assessment of history, clinical examination, and selected laboratory test results that are readily available early in the course of hospitalization. The use of a mathematical model to assist in establishing an early estimate of the probability of survival has the advantage of combining the clinician's estimate, based on prior experience, with quantitative information gained from observations of a large number of hospitalized neonates.
A mathematical model used to predict survival has features that are similar to any other diagnostic test. The accuracy of the result of a diagnostic test for the individual patient depends on the situation in which it is used.2 Therefore, to interpret a diagnostic test, the clinician must first decide how likely it is that the foal will survive on the basis of an initial evaluation. This estimate does not have to be precise but must distinguish foals with a low probability from those with a high probability of survival, and it must be expressed as a probability from 0 to 1. For example, given a large group of foals with historical and clinical examination findings similar to the patient being evaluated, what proportion of those foals would be expected to survive? The clinician's estimate of the probability of survival can then be combined with the results of the diagnostic test (ie, the mathematical model), by use of the sensitivity and specificity based on a single cut-point, to predict whether or not the foal will survive or to generate an adjusted quantitative probability of survival. Increased accuracy for the estimate of the probability of survival can be gained by the use of LRs.3 Likelihood ratios are a series of constants that can be combined with the clinician's estimate of the pretest odds of survival to provide a more precise posttest estimate of the probability of survival. Likelihood ratios have properties and provide information similar to sensitivity and specificity; however, LRs take into consideration the degree of abnormality, based on a range of probabilities for survival from 0 to 1, that can be generated by the model to further refine the estimate of survival for a specific foal.
Previous studies have identified risk factors for survival in neonatal foals and combined those factors into multivariable logistic regression models to predict a probability of survival. Those studies have been characterized by small sample sizes and have focused on specific subpopulations such as foals with septicemia,1 septic arthritis,4 and radiographic evidence of pulmonary disease,5 and foals admitted to ICUs.6,7 The results of those studies cannot be directly compared because the age of foals and selection criteria for inclusion varied considerably. To the authors' knowledge, there are no published studies that include a large, unselected population and incorporate the use of LRs to estimate the probability of survival in hospitalized foals ≤ 7 days of age. Although a more homogeneous sub group of foals may result in improved accuracy of the model, the advantage of using an unselected population of foals is that results of the model can be applied to a wider population of foals and the clinician does not have to decide whether the foal being evaluated is septicemic or meets the somewhat vague criteria for admission to an ICU.
The purpose of the study reported here was to develop a mathematical model that can be used by clinicians shortly after a foal ≤ 7 days of age is hospitalized to improve the estimate of the probability of survival.
Intensive care unit
Hagyard Equine Medical Institute
Rood and Riddle Equine Hospital
Veterinary Teaching Hospital, College of Veterinary Medicine, University of Tennessee
Failure of passive transfer
PROC FREQ, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
PROC TTEST, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
PROC NPAR1WAY, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
PROC LOGISTIC, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
PROC GPLOT, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
PROC UNIVARIATE, SAS 9.1 for Windows, SAS Institute Inc, Cary, NC.
Access, Microsoft Corp, Redmond, Wash.
SAS for Windows, version 9.1, SAS Institute Inc, Cary, NC.
Excel, Microsoft Corp, Mountain View, Calif.
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