European Journal of Pediatrics

, Volume 173, Issue 1, pp 1–13

Use of risk stratification indices to predict mortality in critically ill children

  • Maria Grazia Sacco Casamassima
  • Jose H. Salazar
  • Dominic Papandria
  • James Fackler
  • Kristin Chrouser
  • Emily F. Boss
  • Fizan Abdullah
Review

DOI: 10.1007/s00431-013-1987-6

Cite this article as:
Sacco Casamassima, M.G., Salazar, J.H., Papandria, D. et al. Eur J Pediatr (2014) 173: 1. doi:10.1007/s00431-013-1987-6

Abstract

The complexity and high cost of neonatal and pediatric intensive care has generated increasing interest in developing measures to quantify the severity of patient illness. While these indices may help improve health care quality and benchmark mortality across hospitals, comprehensive understanding of the purpose and the factors that influenced the performance of risk stratification indices is important so that they can be compared fairly and used most appropriately. In this review, we examined 19 indices of risk stratification used to predict mortality in critically ill children and critically analyzed their design, limitations, and purposes. Some pediatric and neonatal models appear well-suited for institutional benchmarking purposes, with relatively brief data acquisition times, limited potential for treatment-related bias, and reliance on diagnostic variables that permit adjustment for case mix. Other models are more suitable for use in clinical trials, as they rely on physiologic variables collected over an extended period, to better capture the interaction between organ systems function and specific therapeutic interventions in acutely ill patients. Irrespective of their clinical or research applications, risk stratification indices must be periodically recalibrated to adjust for changes in clinical practice in order to remain valid outcome predictors in pediatric intensive care units. Longitudinal auditing, education, training, and guidelines development are also critical to ensure fidelity and reproducibility in data reporting. Conclusion: Risk stratification indices are valid tools to describe intensive care unit population and explain differences in mortality.

Keywords

Mortality risk predictors Pediatrics Quality of care Risk stratification indices Scoring system 

Abbreviations

APACHE

Acute Physiologic and Chronic Health Evaluation

ANZNN

Australian and New Zealand Neonatal Network

CRIB

Critical Risk Index for Baby

ECMO

Extracorporeal membrane oxygenation

GCS

Glasgow Coma Scale

ICU

Intensive care unit

NECOSUR

Neonatal del Cono Sur Network

NICHHD

National Institute of Child Health and Human Development

PEMOD

Pediatric multiple organ dysfunction

PELOD

Pediatric logistic organ dysfunction

PICU

Pediatric intensive care unit

PIM

Pediatric Index of Mortality

P-MODS

Pediatric multiple organ dysfunction score

PSI

Physiologic Stability Index for Pediatric Patients

PRISM III

Pediatric Risk of Mortality III

ROC

Receiver operating characteristics

SMR

Standard mortality ratio

SNAP

Score for Neonatal Acute Physiology

VLBW

Very low birth weight

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Maria Grazia Sacco Casamassima
    • 1
  • Jose H. Salazar
    • 1
  • Dominic Papandria
    • 1
  • James Fackler
    • 2
  • Kristin Chrouser
    • 3
  • Emily F. Boss
    • 4
  • Fizan Abdullah
    • 1
    • 5
  1. 1.Center for Pediatric Surgical Clinical Trials and Outcomes Research, Division of Pediatric SurgeryJohns Hopkins University School of MedicineBaltimoreUSA
  2. 2.Anesthesiology/Critical Care MedicineJohns Hopkins University School of MedicineBaltimoreUSA
  3. 3.Johns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  4. 4.Department of Otolaryngology—Head and Neck Surgery, Division of Pediatric OtolaryngologyJohns Hopkins University School of MedicineBaltimoreUSA
  5. 5.Division of Pediatric Surgery, Bloomberg Children’s CenterJohns Hopkins HospitalBaltimoreUSA