title: Predictors of adverse events in patients after discharge from the intensive care unit.
abstract: BACKGROUND
  Patients discharged from the intensive care unit may be at risk of adverse events because of complex care needs.
  
  
  OBJECTIVE
  To identify the types, frequency, and predictors of adverse events that occur in the 72 hours after discharge from an intensive care unit when no evidence of adverse events was apparent before discharge.
  
  
  METHODS
  A predictive cohort study of 300 patients from an adult intensive care unit was undertaken. An internationally accepted protocol for chart audit was used. Frequency of adverse events was calculated, and logistic regression was used to determine independent predictors of adverse events.
  
  
  RESULTS
  A total of 147 adverse events, 17 (11.6%) of which were defined as major, were incurred by 92 patients (30.7%). The 3 most common adverse events, hospital-incurred infection or sepsis (n = 32, 21.8%), hospital-incurred accident or injury (n = 17, 11.6%), and other complication such as deep vein thrombosis, pulmonary edema, or myocardial infarction (n = 17, 11.6%) accounted for 44.9% (n = 66) of all adverse events. Two predictors, respiratory rate less than 10/min or greater than or equal to 25/min and pulse rate exceeding 110/min, were significant independent predictors; requiring a high level of nursing care at the time of discharge was a significant predictor in univariate analysis but not in multivariate analysis.
  
  
  CONCLUSIONS
  Taking, recording, and reporting vital signs are important. Nursing care requirements of patients at discharge from the intensive care unit may be worthy of further investigation in studies of patients after discharge.
authors.affiliation: Research Centre for Clinical and Community Practice Innovation, Griffith University Gold Coast Campus, Queensland, Australia. W.Chaboyer@griffith.edu.au
authors.forename: Wendy
authors.initials: W
authors.lastname: Chaboyer
authors.forename: Lukman
authors.initials: L
authors.lastname: Thalib
authors.forename: Michelle
authors.initials: M
authors.lastname: Foster
authors.forename: Carol
authors.initials: C
authors.lastname: Ball
authors.forename: Brent
authors.initials: B
authors.lastname: Richards
mesh_terms: D018806:APACHE; D000368:Aged; D015331:Cohort Studies; D005260:Female; D006746:Hospital Bed Capacity, 500 and over / Q000706:statistics & numerical data; D006801:Humans; D007362:Intensive Care Units; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D009741:Nursing Staff, Hospital / Q000458:organization & administration; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010360:Patient Transfer / Q000706:statistics & numerical data*; D012307:Risk Factors