Literature DB >> 15665184

Reliability of PRISM and PIM scores in paediatric intensive care.

J G van Keulen1, K H Polderman, R J B J Gemke.   

Abstract

AIMS: To assess the reliability of mortality risk assessment using the Paediatric Risk of Mortality (PRISM) score and the Paediatric Index of Mortality (PIM) in daily practice.
METHODS: Twenty seven physicians from eight tertiary paediatric intensive care units (PICUs) were asked to assess the severity of illness of 10 representative patients using the PRISM and PIM scores. Physicians were divided into three levels of experience: intensivists (>3 years PICU experience, n = 12), PICU fellows (6-30 months of PICU experience, n = 6), and residents (<6 months PICU experience, n = 9). This represents all large PICUs and about half of the paediatric intensivists and PICU fellows working in the Netherlands.
RESULTS: Individual scores and predicted mortality risks for each patient varied widely. For PRISM scores the average intraclass correlation (ICC) was 0.51 (range 0.32-0.78), and the average kappa score 0.6 (range 0.28-0.87). For PIM scores the average ICC was 0.18 (range 0.08-0.46) and the average kappa score 0.53 (range 0.32-0.88). This variability occurred in both experienced and inexperienced physicians. The percentage of exact agreement ranged from 30% to 82% for PRISM scores and from 28 to 84% for PIM scores.
CONCLUSION: In daily practice severity of illness scoring using the PRISM and PIM risk adjustment systems is associated with wide variability. These differences could not be explained by the physician's level of experience. Reliable assessment of PRISM and PIM scores requires rigorous specific training and strict adherence to guidelines. Consequently, assessment should probably be performed by a limited number of well trained professionals.

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Year:  2005        PMID: 15665184      PMCID: PMC1720273          DOI: 10.1136/adc.2003.046722

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  10 in total

1.  Intra-observer variability in APACHE II scoring.

Authors:  K H Polderman; H M Christiaans; J P Wester; J J Spijkstra; A R Girbes
Journal:  Intensive Care Med       Date:  2001-09       Impact factor: 17.440

2.  Inter-observer variability in APACHE II scoring: effect of strict guidelines and training.

Authors:  K H Polderman; E M Jorna; A R Girbes
Journal:  Intensive Care Med       Date:  2001-08       Impact factor: 17.440

3.  Accuracy and reliability of APACHE II scoring in two intensive care units Problems and pitfalls in the use of APACHE II and suggestions for improvement.

Authors:  K H Polderman; A R Girbes; L G Thijs; R J Strack van Schijndel
Journal:  Anaesthesia       Date:  2001-01       Impact factor: 6.955

4.  Interobserver variability in the use of APACHE II scores.

Authors:  K H Polderman; L G Thijs; A R Girbes
Journal:  Lancet       Date:  1999-01-30       Impact factor: 79.321

5.  Pediatric risk of mortality (PRISM) score.

Authors:  M M Pollack; U E Ruttimann; P R Getson
Journal:  Crit Care Med       Date:  1988-11       Impact factor: 7.598

6.  Paediatric index of mortality (PIM): a mortality prediction model for children in intensive care.

Authors:  F Shann; G Pearson; A Slater; K Wilkinson
Journal:  Intensive Care Med       Date:  1997-02       Impact factor: 17.440

7.  The Pediatric Risk of Mortality III--Acute Physiology Score (PRISM III-APS): a method of assessing physiologic instability for pediatric intensive care unit patients.

Authors:  M M Pollack; K M Patel; U E Ruttimann
Journal:  J Pediatr       Date:  1997-10       Impact factor: 4.406

8.  PIM2: a revised version of the Paediatric Index of Mortality.

Authors:  Anthony Slater; Frank Shann; Gale Pearson
Journal:  Intensive Care Med       Date:  2003-01-23       Impact factor: 17.440

9.  Frequency of variable measurement in 16 pediatric intensive care units: influence on accuracy and potential for bias in severity of illness assessment.

Authors:  M M Pollack; K M Patel; U Ruttimann; T Cuerdon
Journal:  Crit Care Med       Date:  1996-01       Impact factor: 7.598

10.  Comparative assessment of pediatric intensive care: a national multicenter study. Pediatric Intensive Care Assessment of Outcome (PICASSO) Study Group.

Authors:  R J Gemke; G J Bonsel
Journal:  Crit Care Med       Date:  1995-02       Impact factor: 7.598

  10 in total
  13 in total

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

Authors:  Toshihiro Imamura; Satoshi Nakagawa; Ran D Goldman; Takeo Fujiwara
Journal:  Intensive Care Med       Date:  2012-01-20       Impact factor: 17.440

2.  Effect of training and strict guidelines on the reliability of risk adjustment systems in paediatric intensive care.

Authors:  Jolanda G van Keulen; Reinoud J B J Gemke; Kees H Polderman
Journal:  Intensive Care Med       Date:  2005-07-06       Impact factor: 17.440

3.  The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance.

Authors:  Bekele Afessa; Mark T Keegan; Ognjen Gajic; Rolf D Hubmayr; Steve G Peters
Journal:  Intensive Care Med       Date:  2005-10-05       Impact factor: 17.440

4.  Comparison of Severity Scoring Systems in a Pediatric Intensive Care Unit in India: A Single-Center Prospective, Observational Cohort Study.

Authors:  Vinayak K Patki; Sandeep Raina; Jennifer V Antin
Journal:  J Pediatr Intensive Care       Date:  2016-06-29

5.  [Value of three scoring systems in evaluating the prognosis of children with severe sepsis].

Authors:  Li-Bing Zhou; Jiao Chen; Xiao-Chen DU; Shui-Yan Wu; Zhen-Jiang Bai; Hai-Tao Lyu
Journal:  Zhongguo Dang Dai Er Ke Za Zhi       Date:  2019-09

6.  Prospective evaluation of clinical scoring systems in infants with bronchiolitis admitted to the intensive care unit.

Authors:  S Rödl; B Resch; N Hofer; I Marschitz; G Madler; E Eber; G Zobel
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2012-04-21       Impact factor: 3.267

7.  Use of a Mortality Prediction Model in Children on Mechanical Ventilation: A 5-Year Experience in a Tertiary University Hospital.

Authors:  Waleed H Albuali; Amal A Algamdi; Elham A Hasan; Mohammad H Al-Qahtani; Abdullah A Yousef; Mohammad A Al Ghamdi; Dalal K Bubshait; Mohammed S Alshahrani; Faisal O AlQurashi; Talal A Bou Shahmah; Bassam H Awary
Journal:  J Multidiscip Healthc       Date:  2020-11-11

Review 8.  Use of risk stratification indices to predict mortality in critically ill children.

Authors:  Maria Grazia Sacco Casamassima; Jose H Salazar; Dominic Papandria; James Fackler; Kristin Chrouser; Emily F Boss; Fizan Abdullah
Journal:  Eur J Pediatr       Date:  2013-03-23       Impact factor: 3.183

9.  Critically ill newborns with multiple organ dysfunction: assessment by NEOMOD score in a tertiary NICU.

Authors:  J Janota; J Simak; Z Stranak; T Matthews; T Clarke; D Corcoran
Journal:  Ir J Med Sci       Date:  2008-01-25       Impact factor: 1.568

Review 10.  Vitamin D deficiency in surgical congenital heart disease: prevalence and relevance.

Authors:  James Dayre McNally; Kusum Menon
Journal:  Transl Pediatr       Date:  2013-07
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