Prognostic variables for survival of neonatal foals under intensive care

J Vet Intern Med. 1992 Mar-Apr;6(2):89-95. doi: 10.1111/j.1939-1676.1992.tb03157.x.

Abstract

The costly nature of intensive care for neonatal foals prompted a study of predictive variables for survival in a referral hospital. Applying stepforward logistic regression to parameters that differed significantly (P less than 0.10) between survivors (S) and nonsurvivors (NS) in a retrospective study (n = 56), two variables retained statistical significance [anion gap (AG, P = 0.0047) and venous PO2 (PvO2, P = 0.0342)], thus forming the basis for a predictive equation for survival: the Pn (probability of NS) = eA/(1 + eA) where A = -1.46 - 0.107 (PvO2) + 0.213 (AG). The predictive equation was evaluated prospectively in foals (n = 48), irrespective of diagnosis, that underwent intensive care. Sepsis was the most common medical problem identified in both groups of foals (51/104). In the prospective study, a Pn less than or equal to 0.5 predicted S (positive test) and Pn greater than 0.5 predicted NS (negative test). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the predictive equation were 100%, 40%, 62%, and 100%, respectively. All foals with Pn greater than 0.4 (n = 14) did not survive. Erroneous predictions were consistently false positives (predicted S, outcome NS). The predictive equation for survival may aid in identification of high risk neonates, i.e., unlikely to survive. The prognostic merits of anion gap and PvO2 imply that tissue oxygen debt was a significant problem for these critically ill foals.

MeSH terms

  • Acid-Base Equilibrium
  • Animals
  • Animals, Newborn
  • Bacterial Infections / mortality
  • Bacterial Infections / therapy
  • Bacterial Infections / veterinary
  • Breeding
  • Cohort Studies
  • Critical Care*
  • Female
  • Horse Diseases / mortality
  • Horse Diseases / therapy*
  • Horses
  • Male
  • Oxygen / blood
  • Probability
  • Prognosis
  • Prospective Studies
  • Regression Analysis
  • Retrospective Studies

Substances

  • Oxygen