title: Predictive ability of the stability and workload index for transfer score to predict unplanned readmissions after ICU discharge.
abstract: OBJECTIVE
  Unplanned readmission of hospitalized patients to an ICU is associated with an increased mortality and hospital length of stay. The ability to identify patients at risk, who would benefit from prolonged ICU treatment, is limited. The aim of this study is to validate a previously published numerical index named the Stability and Workload Index for Transfer in a heterogeneous group of ICU patients.
  
  
  METHODS
  In this retrospective data analysis, the Stability and Workload Index for Transfer score was calculated for all patients, and the ability of the score to predict readmission was compared with the original publication.
  
  
  METHODS
  Four ICUs, one intermediate care unit, and one postanesthesia care unit of the department of anesthesia and intensive care of a university hospital.
  
  
  METHODS
  All consecutive patients treated in one of the units.
  
  
  METHODS
  None.
  
  
  RESULTS
  Unplanned ICU readmissions or unexpected death within 7 days of ICU discharge. The data of 7,175 patients were included in the analysis. Five hundred ninety-six patients were readmitted or died within 7 days of discharge. The patients who are readmitted to the ICU are significantly older and have significantly higher scores that define the severity of disease at the time of admission and discharge of their first ICU stay. The source of admission for the initial ICU stay did not differ (p = 0.055), and the last Glasgow Coma Scale and the last PaO2/FIO2 ratio before discharge from the ICU were higher in patients who did not need a readmission to the ICU. The performance of the Stability and Workload Index for Transfer score is poor with an area under the receiver operator curve of 0.581 (95% CI, 0.556-0.605; p < 0.001).
  
  
  CONCLUSIONS
  Based on the data from our patients, the proposed Stability and Workload Index for Transfer score by Gajic et al is not ideal in aiding the clinician in the decision, if a patient can be discharged safely from the ICU and further research is necessary to define the patients at risk for readmission.
authors: Charité - Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany.
authors: Marc
authors: M
authors: Kastrup
authors: Robert
authors: R
authors: Powollik
authors: Felix
authors: F
authors: Balzer
authors: Susanne
authors: S
authors: Röber
authors: Robert
authors: R
authors: Ahlborn
authors: Vera
authors: V
authors: von Dossow-Hanfstingl
authors: Klaus D
authors: KD
authors: Wernecke
authors: Claudia D
authors: CD
authors: Spies
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001509:Bed Occupancy / Q000706:statistics & numerical data; D001784:Blood Gas Analysis; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration* / Q000706:statistics & numerical data*; D007902:Length of Stay; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012372:ROC Curve; D012189:Retrospective Studies; D016526:Workload / Q000706:statistics & numerical data