title: PIM2: a revised version of the Paediatric Index of Mortality.
abstract: OBJECTIVE
  To revise the Paediatric Index of Mortality (PIM) to adjust for improvement in the outcome of paediatric intensive care.
  
  
  METHODS
  International, multi-centre, prospective, observational study.
  
  
  METHODS
  Twelve specialist paediatric intensive care units and two combined adult and paediatric units in Australia, New Zealand and the United Kingdom.
  
  
  METHODS
  All children admitted during the study period. In the analysis, 20787 patient admissions of children less than 16 years were included after 220 patients transferred to other ICUs and one patient still in ICU had been excluded.
  
  
  METHODS
  None.
  
  
  RESULTS
  A revised model was developed by forward and backward logistic regression. Variable selection was based on the effect of including or dropping variables on discrimination and fit. The addition of three variables, all derived from the main reason for ICU admission, improved the fit across diagnostic groups. Data from seven units were used to derive a learning model that was tested using data from seven other units. The model fitted the test data well (deciles of risk goodness-of-fit chi(2 )8.14, p=0.42) and discriminated between death and survival well [area under the receiver operating characteristic (ROC) plot 0.90 (0.89-0.92)]. The final PIM2 model, derived from the entire sample of 19638 survivors and 1104 children who died, also fitted and discriminated well [chi(2 )11.56, p=0.17; area 0.90 (0.89-0.91)].
  
  
  CONCLUSIONS
  PIM2 has been re-calibrated to reflect the improvement that has occurred in intensive care outcome. PIM2 estimates mortality risk from data readily available at the time of ICU admission and is therefore suitable for continuous monitoring of the quality of paediatric intensive care.
authors.affiliation: Women's and Children's Hospital, 72 King William Road, SA 5006, North Adelaide, Australia. slatera@wch.sa.gov.au
authors.forename: Anthony
authors.initials: A
authors.lastname: Slater
authors.forename: Frank
authors.initials: F
authors.lastname: Shann
authors.forename: Gale
authors.initials: G
authors.lastname: Pearson
mesh_terms: D000328:Adult; D017677:Age Distribution; D000704:Analysis of Variance; D001315:Australia / Q000453:epidemiology; D015982:Bias; D002648:Child; D002675:Child, Preschool; D003953:Diagnosis-Related Groups / Q000706:statistics & numerical data; D016002:Discriminant Analysis; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015278:Intensive Care Units, Pediatric / Q000592:standards / Q000706:statistics & numerical data* / Q000639:trends; D016015:Logistic Models; D009520:New Zealand / Q000453:epidemiology; D017063:Outcome Assessment, Health Care; D010343:Patient Admission; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011787:Quality of Health Care; D012372:ROC Curve; D012307:Risk Factors; D012720:Severity of Illness Index; D016019:Survival Analysis; D006113:United Kingdom / Q000453:epidemiology