title: Predictors of intensive care unit refusal in French intensive care units: a multiple-center study.
abstract: OBJECTIVE
  To identify factors associated with granting or refusing intensive care unit (ICU) admission, to analyze ICU characteristics and triage decisions, and to describe mortality in admitted and refused patients.
  
  
  METHODS
  Observational, prospective, multiple-center study.
  
  
  METHODS
  Four university hospitals and seven primary-care hospitals in France.
  
  
  METHODS
  None.
  
  
  RESULTS
  Age, underlying diseases (McCabe score and Knaus class), dependency, hospital mortality, and ICU characteristics were recorded. The crude ICU refusal rate was 23.8% (137/574), with variations from 7.1% to 63.1%. The reasons for refusal were too well to benefit (76/137, 55.4%), too sick to benefit (51/137, 37.2%), unit too busy (9/137, 6.5%), and refusal by the family (1/137). In logistic regression analyses, two patient-related factors were associated with ICU refusal: dependency (odds ratio [OR], 14.20; 95% confidence interval [CI], 5.27-38.25; p < .0001) and metastatic cancer (OR, 5.82; 95% CI, 2.22-15.28). Other risk factors were organizational, namely, full unit (OR, 3.16; 95% CI, 1.88-5.31), center (OR, 3.81; 95% CI, 2.27-6.39), phone admission (OR, 0.23; 95% CI, 0.14-0.40), and daytime admission (OR, 0.52; 95% CI, 0.32-0.84). The Standardized Mortality Ratio was 1.41 (95% CI, 1.19-1.69) for immediately admitted patients, 1.75 (95% CI, 1.60-1.84) for refused patients, and 1.03 (95% CI, 0.28-1.75) for later-admitted patients.
  
  
  CONCLUSIONS
  ICU refusal rates varied greatly across ICUs and were dependent on both patient and organizational factors. Efforts to define ethically optimal ICU admission policies might lead to greater homogeneity in refusal rates, although case-mix variations would be expected to leave an irreducible amount of variation across ICUs.
authors.affiliation: Medical-Surgical Intensive Care Unit, Saint Joseph Hospital, Paris, France.
authors.forename: Maité
authors.initials: M
authors.lastname: Garrouste-Orgeas
authors.forename: Luc
authors.initials: L
authors.lastname: Montuclard
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Timsit
authors.forename: Jean
authors.initials: J
authors.lastname: Reignier
authors.forename: Thibault
authors.initials: T
authors.lastname: Desmettre
authors.forename: Philippe
authors.initials: P
authors.lastname: Karoubi
authors.forename: Delphine
authors.initials: D
authors.lastname: Moreau
authors.forename: Laurent
authors.initials: L
authors.lastname: Montesino
authors.forename: Alexandre
authors.initials: A
authors.lastname: Duguet
authors.forename: Sandrine
authors.initials: S
authors.lastname: Boussat
authors.forename: Christophe
authors.initials: C
authors.lastname: Ede
authors.forename: Yannick
authors.initials: Y
authors.lastname: Monseau
authors.forename: Thierry
authors.initials: T
authors.lastname: Paule
authors.forename: Benoit
authors.initials: B
authors.lastname: Misset
authors.forename: Jean
authors.initials: J
authors.lastname: Carlet
mesh_terms: D005260:Female; D005602:France / Q000453:epidemiology; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data; D017052:Hospital Mortality; D006786:Hospitals, Urban / Q000706:statistics & numerical data; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010343:Patient Admission / Q000706:statistics & numerical data*; D011446:Prospective Studies; D016079:Refusal to Treat / Q000706:statistics & numerical data*; D012307:Risk Factors; D016312:Treatment Refusal / Q000706:statistics & numerical data; D014218:Triage / Q000706:statistics & numerical data