title: Multivariate models for predicting survival of patients with trauma from low falls: the impact of gender and pre-existing conditions.
abstract: OBJECTIVE
  To determine if pre-existing conditions significantly improve the ability of current (TRISS and ASCOT) methods for predicting survival of patients with trauma from low falls.
  
  
  METHODS
  Retrospective analysis using logistic regression models to identify significant independent predictors of survival.
  
  
  METHODS
  Eight hospitals affiliated with New York Medical College.
  
  
  METHODS
  A total of 1906 patients with trauma from low falls who were admitted to the eight hospitals between July 1987 and June 1989.
  
  
  RESULTS
  Gender and several pre-existing conditions significantly improved the ability of age and the physiologic and anatomic variables contained in the TRISS and ASCOT methodologies to predict survival for trauma patients suffering from low falls, with males experiencing a lower probability of survival. Odds of survival for patients with these pre-existing conditions ranged from 0.18 to 0.59 times the odds of survival for similar patients without the pre-existing conditions when the TRISS variables were used, and from 0.23 to 0.56 times the odds for similar patients when ASCOT variables were used. Furthermore, some substantial differences were found when hospital performance was assessed with and without the benefit of pre-existing conditions.
  
  
  CONCLUSIONS
  Pre-existing conditions and male gender are significantly related to survival of patients with trauma from low falls, and should be included along with age and the various physiologic and anatomic measures currently being used to predict survival for those patients.
authors.affiliation: Department of Health Policy and Management, School of Public Health, State University of New York, University at Albany 12222, USA.
authors.forename: E L
authors.initials: EL
authors.lastname: Hannan
authors.forename: J
authors.initials: J
authors.lastname: Mendeloff
authors.forename: L S
authors.initials: LS
authors.lastname: Farrell
authors.forename: C G
authors.initials: CG
authors.lastname: Cayten
authors.forename: J G
authors.initials: JG
authors.lastname: Murphy
mesh_terms: D000058:Accidental Falls / Q000401:mortality*; D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D012189:Retrospective Studies; D012737:Sex Factors; D015996:Survival Rate; D014947:Wounds and Injuries / Q000175:diagnosis / Q000401:mortality