Evaluation of the survival prediction index as a model of risk stratification for clinical research in dogs admitted to intensive care units at four locations.
OBJECTIVE
To prospectively evaluate a survival prediction index (SPI) in dogs admitted to intensive care units (ICU) and to generate and test an improved SPI (ie, SPI2).


METHODS
Medical records of 624 critically ill dogs admitted to an ICU.


METHODS
Data were collected from dogs within 24 hours after admission to an ICU. Variables recorded reflected function of vital organ systems, severity of underlying physiologic derangement, and extent of physiologic reserve; outcome was defined as dogs that survived or did not survive until 30 days after admission to the ICU. Probabilities of survival were calculated, using an established model (SPI). We then performed another logistic regression analysis, thereby reestimating the variables to create the new SPI2. Cross-validation of the models obtained was performed by randomly assigning the total sample of 624 dogs into an estimation group of 499 dogs and validation group of 125 dogs.


RESULTS
Testing of SPI resulted in an area under the curve (AUC) of 0.723. Testing of SPI2 revealed an AUC of 0.773. A backwards-elimination procedure was used to create a model containing fewer variables, and variables were sequentially eliminated. The AUC for the reduced model of SPI2 was 0.76, indicating little loss in predictive accuracy.


CONCLUSIONS
The new SPI2 objectively stratified clinical patients into groups according to severity of disease. This index could provide an important tool for clinical research.
King
L G
LG
Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia 19104-6010, USA.
Wohl
J S
JS
Manning
A M
AM
Hackner
S G
SG
Raffe
M R
MR
Maislin
G
G
D000818:Animals; D015331:Cohort Studies; D003422:Critical Care; D004283:Dog Diseases / Q000401:mortality*; D004285:Dogs; D005260:Female; D006762:Hospitals, Animal; D016015:Logistic Models; D008297:Male; D008954:Models, Biological; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012307:Risk Factors; D016019:Survival Analysis