title: The acute patient physiologic and laboratory evaluation (APPLE) score: a severity of illness stratification system for hospitalized dogs.
abstract: BACKGROUND
  Objective risk stratification models are used routinely in human critical care medicine. Applications include quantitative and objective delineation of illness severity for patients enrolled in clinical research, performance benchmarking, and protocol development for triage and therapeutic management.
  
  
  OBJECTIVE
  To develop an accurate, validated, and user-friendly model to stratify illness severity by mortality risk in hospitalized dogs.
  
  
  METHODS
  Eight hundred and ten consecutive intensive care unit (ICU) admissions of dogs at a veterinary teaching hospital.
  
  
  METHODS
  Prospective census cohort study. Data on 55 management, physiological, and biochemical variables were collected within 24 hours of admission. Data were randomly divided, with 598 patient records used for logistic regression model construction and 212 for model validation.
  
  
  RESULTS
  Patient mortality was 18.4%. Ten-variable and 5-variable models were developed to provide both a high-performance model and model maximizing accessibility, while maintaining good performance. The 10-variable model contained creatinine, WBC count, albumin, SpO(2) , total bilirubin, mentation score, respiratory rate, age, lactate, and presence of free fluid in a body cavity. Area under the receiver operator characteristic (AUROC) on the construction data set was 0.93, and on the validation data set was 0.91. The 5-variable model contained glucose, albumin, mentation score, platelet count, and lactate. AUROC on the construction data set was 0.87, and on the validation data set was 0.85.
  
  
  CONCLUSIONS
  Two models are presented that enable allocation of an accurate and user-friendly illness severity index for dogs admitted to an ICU. These models operate independent of primary diagnosis, and have been independently validated.
authors.affiliation: Emergency and Critical Care Department, University of Guelph, Guelph, Ontario, Canada. galina@uoguelph.ca
authors.forename: G
authors.initials: G
authors.lastname: Hayes
authors.forename: K
authors.initials: K
authors.lastname: Mathews
authors.forename: G
authors.initials: G
authors.lastname: Doig
authors.forename: S
authors.initials: S
authors.lastname: Kruth
authors.forename: S
authors.initials: S
authors.lastname: Boston
authors.forename: S
authors.initials: S
authors.lastname: Nykamp
authors.forename: Z
authors.initials: Z
authors.lastname: Poljak
authors.forename: C
authors.initials: C
authors.lastname: Dewey
mesh_terms: D000208:Acute Disease; D000818:Animals; D001774:Blood Chemical Analysis / Q000662:veterinary; D015331:Cohort Studies; D004283:Dog Diseases / Q000473:pathology*; D004285:Dogs; D005260:Female; D006762:Hospitals, Animal; D008297:Male; D008954:Models, Biological; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012720:Severity of Illness Index