title: Can the simple clinical score usefully predict the mortality risk and length of stay for a recently admitted patient?
abstract: OBJECTIVE
  The aim of the present study was to determine whether an aggregate simple clinical score (SCS) has a role in predicting the imminent mortality and in-hospital length of stay (LOS) of newly admitted, acutely unwell General Medical in-patients.
  
  
  METHODS
  Data were collected prospectively from adult patients admitted through an Acute Medical Unit between February and August 2013. Using logistic regression analysis before and after adjustment for age, the SCS was assessed for its association with LOS and mortality, including 30-day mortality, just for those patients for full resuscitation. Changes in sensitivity and specificity after adding SCS to age as a predictor, as well as the change in the net reclassification index, were determined using the predicted probabilities from the logistic regression models.
  
  
  RESULTS
  The SCS was superior to age in predicting mortality of any patient within 30 days. It did not assist in predicting 30-day mortality for those patients who were for full resuscitation. The ability of the SCS to predict long stay (> 72h) remained relatively low (64%) and was inferior to published rates achieved by bedside clinician assessment (74%-82%).
  
  
  CONCLUSIONS
  There was no useful prospective role for the SCS in predicting LOS and mortality of in-patients newly admitted to a General Medicine service.
authors.affiliation: Discipline of Medicine, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia. Email.
authors.forename: Minh T
authors.initials: MT
authors.lastname: Nguyen
authors.affiliation: Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, Sturt Road, Bedford Park, SA 5042, Australia. Email.
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Woodman
authors.affiliation: Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, Sturt Road, Bedford Park, SA 5042, Australia. Email.
authors.forename: Paul
authors.initials: P
authors.lastname: Hakendorf
authors.affiliation: Discipline of Medicine, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia. Email.
authors.forename: Campbell H
authors.initials: CH
authors.lastname: Thompson
authors.affiliation: Department of General Medicine, Royal Adelaide Hospital, North Terrace, Adelaide, SA 5000, Australia. Email.
authors.forename: Jeff
authors.initials: J
authors.lastname: Faunt
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003643:Death; D005260:Female; D005544:Forecasting; D006760:Hospitalization; D006801:Humans; D007902:Length of Stay / Q000639:trends*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment / Q000706:statistics & numerical data