title: Predicting early mortality among elderly patients hospitalised in medical wards via emergency department: the SAFES cohort study.
abstract: OBJECTIVE
  The aim of the study was, by early identification of deleterious prognostic factors that are open to remediation, to be in a position to assign elderly patients to different mortality risk groups to improve management.
  
  
  METHODS
  Prospective multicentre cohort.
  
  
  METHODS
  Nine French teaching hospitals.
  
  
  METHODS
  One thousand three hundred and six (1 306) patients aged 75 and over, hospitalised after having passed through Emergency Department (ED).
  
  
  METHODS
  Patients were assessed using Comprehensive Geriatric Assessment (CGA) tools. A Cox survival analysis was performed to identify prognostic variables for six-week mortality. Receiver Operating Characteristics analysis was used to study the discriminant power of the model. A mortality risk score is proposed to define three risk groups for six-week mortality.
  
  
  RESULTS
  Crude mortality rate after a six week follow-up was 10.6% (n=135). Prognostic factors identified were: malnutrition risk (HR=2.1; 95% CI: 1.1-3.8; p=.02), delirium (HR=1.7; 95% CI: 1.2-2.5; p=.006), and dependency: moderate dependency (HR=4.9; 95% CI: 1.5-16.5; p=.01) or severe dependency (HR=10.3; 95% CI: 3.2-33.1; p < .001). The discriminant power of the model was good: the c-statistic representing the area under the curve was 0.71 (95% IC: 0.67 - 0.75; p < .001). The six-week mortality rate increased significantly (p < .001) across the three risk groups: 1.1% (n=269; 95% CI=0.5-1.7) in the lowest risk group, 11.1% (n=854; 95% CI=9.4-12.9) in the intermediate risk group, and 22.4% (n=125; 95% CI=20.1-24.7) in the highest risk group.
  
  
  CONCLUSIONS
  A simple score has been calculated (using only three variables from the CGA) and a practical schedule proposed to characterise patients according to the degree of mortality risk. Each of these three variables (malnutrition risk, delirium, and dependency) identified as independent prognostic factors can lead to a targeted therapeutic option to prevent early mortality.
authors.affiliation: University of Reims Champagne-Ardenne, Faculty of Medicine, E.A 3797, Reims, F-51095, France.
authors.forename: M
authors.initials: M
authors.lastname: Drame
authors.forename: N
authors.initials: N
authors.lastname: Jovenin
authors.forename: J L
authors.initials: JL
authors.lastname: Novella
authors.forename: P O
authors.initials: PO
authors.lastname: Lang
authors.forename: D
authors.initials: D
authors.lastname: Somme
authors.forename: I
authors.initials: I
authors.lastname: Laniece
authors.forename: T
authors.initials: T
authors.lastname: Voisin
authors.forename: P
authors.initials: P
authors.lastname: Blanc
authors.forename: P
authors.initials: P
authors.lastname: Couturier
authors.forename: J B
authors.initials: JB
authors.lastname: Gauvain
authors.forename: F
authors.initials: F
authors.lastname: Blanchard
authors.forename: D
authors.initials: D
authors.lastname: Jolly
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D015331:Cohort Studies; D015897:Comorbidity; D003693:Delirium / Q000453:epidemiology*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005602:France / Q000453:epidemiology; D015577:Geriatric Assessment; D017052:Hospital Mortality; D006801:Humans; D008297:Male; D044342:Malnutrition / Q000453:epidemiology*; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors