Literature DB >> 23525543

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

Maria Grazia Sacco Casamassima1, Jose H Salazar, Dominic Papandria, James Fackler, Kristin Chrouser, Emily F Boss, Fizan Abdullah.   

Abstract

UNLABELLED: 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.

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Year:  2013        PMID: 23525543     DOI: 10.1007/s00431-013-1987-6

Source DB:  PubMed          Journal:  Eur J Pediatr        ISSN: 0340-6199            Impact factor:   3.183


  50 in total

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2.  Review of the methodologies and applications of scoring systems in neonatal and pediatric intensive care.

Authors:  James P. Marcin; Murray M. Pollack
Journal:  Pediatr Crit Care Med       Date:  2000-07       Impact factor: 3.624

3.  Assessing mortality risk in very low birthweight infants: a comparison of CRIB, CRIB-II, and SNAPPE-II.

Authors:  L Gagliardi; A Cavazza; A Brunelli; M Battaglioli; D Merazzi; F Tandoi; D Cella; G F Perotti; M Pelti; I Stucchi; F Frisone; A Avanzini; R Bellù
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  2004-09       Impact factor: 5.747

4.  Why do pediatric intensive care units improve over time?*.

Authors:  Bernhard Frey
Journal:  Crit Care Med       Date:  2012-07       Impact factor: 7.598

5.  A new score for predicting neonatal very low birth weight mortality risk in the NEOCOSUR South American Network.

Authors:  Guillermo Marshall; Jose L Tapia; Ivonne D'Apremont; Carlos Grandi; Claudia Barros; Angelica Alegria; Jane Standen; Ruben Panizza; Liliana Roldan; Gabriel Musante; Aldo Bancalari; Enrique Bambaren; Jose Lacarruba; Maria E Hubner; Jorge Fabres; Marcelo Decaro; Gonzalo Mariani; Isabel Kurlat; Agustina Gonzalez
Journal:  J Perinatol       Date:  2005-09       Impact factor: 2.521

6.  Validation of pediatric index of mortality 2 (PIM2) in a single pediatric intensive care unit of Argentina.

Authors:  Pablo G Eulmesekian; Augusto Pérez; Pablo G Minces; Hilario Ferrero
Journal:  Pediatr Crit Care Med       Date:  2007-01       Impact factor: 3.624

7.  Prenatal predictors of mortality in very preterm infants cared for in the Australian and New Zealand Neonatal Network.

Authors:  N Evans; J Hutchinson; J M Simpson; D Donoghue; B Darlow; D Henderson-Smart
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  2006-07-28       Impact factor: 5.747

8.  The CRIB score.

Authors:  W Tarnow-Mordi; G Parry
Journal:  Lancet       Date:  1993-11-27       Impact factor: 79.321

9.  The suitability of the Pediatric Index of Mortality (PIM), PIM2, the Pediatric Risk of Mortality (PRISM), and PRISM III for monitoring the quality of pediatric intensive care in Australia and New Zealand.

Authors:  Anthony Slater; Frank Shann
Journal:  Pediatr Crit Care Med       Date:  2004-09       Impact factor: 3.624

10.  Hospital-reported medical errors in premature neonates.

Authors:  David E Kanter; Wendy Turenne; Anthony D Slonim
Journal:  Pediatr Crit Care Med       Date:  2004-03       Impact factor: 3.624

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  3 in total

1.  Real-Time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality.

Authors:  Hargobind S Khurana; Robert H Groves; Michael P Simons; Mary Martin; Brenda Stoffer; Sherri Kou; Richard Gerkin; Eric Reiman; Sairam Parthasarathy
Journal:  Am J Med       Date:  2016-03-24       Impact factor: 4.965

2.  Comparison of Performance of the Pediatric Index of Mortality (PIM)-2 and PIM-3 Scores in the Pediatric Intensive Care Unit of a High Complexity Institution.

Authors:  Deyanira Quiñónez-López; Daniela Patino-Hernandez; César A Zuluaga; Ángel A García; Oscar M Muñoz-Velandia
Journal:  Indian J Crit Care Med       Date:  2020-11

Review 3.  A systematic review of neonatal treatment intensity scores and their potential application in low-resource setting hospitals for predicting mortality, morbidity and estimating resource use.

Authors:  Jalemba Aluvaala; Gary S Collins; Michuki Maina; James A Berkley; Mike English
Journal:  Syst Rev       Date:  2017-12-07
  3 in total

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