title: [Influence of patients' age in the probabilistic models of mortality on admission in general internal medicine wards].
abstract: OBJECTIVE
  The predictive models of in-hospital mortality in the departments of Internal Medicine have not reached a generalized use. Our hypothesis is that the very elderly patients interfere in the models currently in use.
  
  
  METHODS
  In this observational, prospective cohort study, 1,500 patients admitted consecutively in the department of Internal Medicine were analysed. A logistic regression analysis based on the REMS model was used for the whole series and after segmenting it according to if the age of patients was 85 years or less, or more than 85 years.
  
  
  RESULTS
  The global in-hospital mortality of the patients was 12%. Although the REMS model predicted a global mortality of 11.9%, sensitivity and specificity for an individual prediction were not satisfactory because the AUC was only 0.704. When the sample was split according to the age of patients, the model gained precision for the group ≤ 85 years (AUC 0.799), whereas it lost sensitivity and specificity for the group of patients > 85 years (AUC 0.66).
  
  
  CONCLUSIONS
  Age of patients interferes in the general models of prediction of mortality in departments of Internal Medicine. There may be important variables in advanced age not taken into account in the predictive models nowadays available. We think that specific predictive models of in-hospital mortality in Internal Medicine should be designed for patients of advanced age.
authors.affiliation: Servei de Medicina Interna, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.
authors.forename: Esther
authors.initials: E
authors.lastname: Francia
authors.forename: Jordi
authors.initials: J
authors.lastname: Casademont
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003661:Decision Support Techniques; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006757:Hospital Units / Q000706:statistics & numerical data*; D006801:Humans; D007388:Internal Medicine; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011336:Probability; D011446:Prospective Studies; D012372:ROC Curve; D012680:Sensitivity and Specificity