Intensive Care Medicine

, Volume 29, Issue 2, pp 278–285

PIM2: a revised version of the Paediatric Index of Mortality

  • Anthony Slater
  • Frank Shann
  • Gale Pearson
  • for the PIM Study Group
Neonatal and Pediatric Intensive Care

Abstract

Objective

To revise the Paediatric Index of Mortality (PIM) to adjust for improvement in the outcome of paediatric intensive care.

Design

International, multi-centre, prospective, observational study.

Setting

Twelve specialist paediatric intensive care units and two combined adult and paediatric units in Australia, New Zealand and the United Kingdom.

Patients

All children admitted during the study period. In the analysis, 20,787 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.

Interventions

None.

Measurements and 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 χ2 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 19,638 survivors and 1,104 children who died, also fitted and discriminated well [χ2 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.

Keywords

Paediatric Intensive care Mortality prediction models Outcome assessment Logistic regression 

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • Anthony Slater
    • 1
  • Frank Shann
    • 2
  • Gale Pearson
    • 3
  • for the PIM Study Group
  1. 1.Women's and Children's HospitalNorth AdelaideAustralia
  2. 2.Royal Children's HospitalParkvilleAustralia
  3. 3.Birmingham Children's HospitalBirmingham UK

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