title: A new algorithm to allow early prediction of mortality in elderly burn patients.
abstract: BACKGROUND
  The elderly are the fastest growing population segment, and particularly susceptible to burns. Predicting outcomes for these patients remains difficult. Our objective was to identify early predictors of mortality in elderly burn patients.
  
  
  METHODS
  Our Burn Center's prospective database was reviewed for burn patients 60+ treated in the past 10 years. Predictor variables were identified by correlative analysis and subsequently entered into a multivariate logistic regression analysis examining survival to discharge.
  
  
  RESULTS
  203 patients of 1343 (15%) were eligible for analysis. The average age was 72 ± 10 (range 60-102) and the average total body surface area (TBSA) burned was 23 ± 18% (range 1-95). Age, TBSA, base deficit, pO(2), respiratory rate, Glasgow Coma Score (GCS), and Revised Trauma Score (RTS, based on systolic blood pressure, respiratory rate, and GCS) all correlated with mortality (p ≤0 .05). Using multiple logistic regression analysis, a model with age, TBSA and RTS was calculated, demonstrating: In this model, β(0) is a constant that equals -8.32.
  
  
  CONCLUSIONS
  Predicting outcomes in elderly burn patients is difficult. A model using age, TBSA, and RTS can, immediately upon patient arrival, help identify patients with decreased chances of survival, further guiding end-of-life decisions.
authors.affiliation: University of Miami Burn Center, Division of Trauma and Surgical Critical Care, DeWitt Daughtry Family Department of Surgery, University of Miami Miller School of Medicine, Miami FL 33101, United States.
authors.forename: James S
authors.initials: JS
authors.lastname: Davis
authors.forename: Angela T
authors.initials: AT
authors.lastname: Prescott
authors.forename: Robin P
authors.initials: RP
authors.lastname: Varas
authors.forename: Olga D
authors.initials: OD
authors.lastname: Quintana
authors.forename: Oscar
authors.initials: O
authors.lastname: Rosales
authors.forename: Louis R
authors.initials: LR
authors.lastname: Pizano
authors.forename: Nicholas
authors.initials: N
authors.lastname: Namias
authors.forename: Carl I
authors.initials: CI
authors.lastname: Schulman
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002056:Burns / Q000401:mortality* / Q000473:pathology / Q000503:physiopathology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D015599:Trauma Severity Indices