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Les scores de gravité généraux et de dysfonctions d’organes en réanimation pédiatrique : quoi de neuf en 2016 ?

Severity of illness and organ dysfunction scoring in pediatric intensive care unit: What news in 2016?

  • Mise au Point / Update
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Médecine Intensive Réanimation

Résumé

Les scores de gravité généraux et de dysfonctions d’organes (DO) sont de plus en plus utilisés dans les services de réanimation adultes et pédiatriques. Cette utilisation est justifiée par la nécessaire évaluation objective de la gravité et du niveau des DO des patients durant le séjour en réanimation. En réanimation pédiatrique, les scores de gravité généraux sont établis, indépendamment du diagnostic, en prenant en compte l’hétérogénéité des populations en termes d’âge notamment. Ces scores permettent d’évaluer la gravité dans les premières heures après l’admission en réanimation. Deux « systèmes » de scores de gravité généraux pédiatriques ont été proposés pour la population allant du nouveau-né (prématurés exclus) à l’adolescent : le système Pediatric Index of Mortality (PIM), le PIM3 étant la dernière version établie en 2013 et le système Pediatric Risk of Mortality (PRISM), le PRISM IV, dont la dernière version date de 2016. Les scores de DO, prenant en compte des paramètres physiologiques reflétant les principales DO, ont été développés et validés pour décrire les DO durant le séjour en réanimation. Le système de score de DO pédiatrique le plus utilisé est le Pediatric Logistic Organ Dysfunction (PELOD), dont la dernière version (PELOD-2) date de 2013. L’objectif de cette revue est : 1) de donner un état des lieux actualisé des scores de gravité généraux et des DO en réanimation pédiatrique ; 2) d’expliciter les moyens de mesure de la performance et de l’adaptation des scores ; 3) de donner l’utilité, les limites et les perspectives des scores en réanimation pédiatrique.

Abstract

Severity of illness and organ dysfunction scoring systems are increasingly used in adult and pediatric intensive care unit (PICU) to characterize disease severity and degree of organ dysfunction. In PICU, severity of illness scores are developed independently of diagnosis, taking into account the age of the different populations. Severity of illness scores were developed to better describe the severity of illness at baseline of groups of critically ill patients. Two systems are available: the pediatric index of mortality (PIM)—latest version PIM3 published in 2013, and the Pediatric RISk of Mortality (PRISM) system, which should be used in critically ill neonates, infants, children, or adolescents, (excluding premature infants)—latest version PRISM IV published in 2016. Organ dysfunction scores were developed to better describe the severity of illness during stay in the PICU. The Pediatric Logistic Organ Dysfunction score is the most commonly used pediatric organ dysfunction score—latest version PELOD-2 published in 2013. The purpose of this review is to provide an update about severity of illness and organ dysfunction scoring systems in PICU, to describe tools to evaluate performance and customization, and then discuss utility, limits and perspectives for scoring systems in PICU.

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Références

  1. Vincent JL, Bruzzi de Carvalho F (2010) Severity of illness. Semin Respir Crit Care Med 31:31–8

    Article  PubMed  Google Scholar 

  2. Lacroix J, Cotting J, Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network (2005) Severity of illness and organ dysfunction scoring in children. Pediatr Crit Care Med 6: S126–S34

    Article  PubMed  Google Scholar 

  3. Marcin JP, Pollack MM (2007) Review of the acuity scoring systems for the pediatric intensive care unit and their use in quality improvement. J Intensive Care Med 22:131–40

    Article  PubMed  Google Scholar 

  4. Martinot A, Leclerc F, Hue V, et al (1995) Les scores de gravité généraux en réanimation pédiatrique. Réanimation Urgences 4:335–63

    Article  Google Scholar 

  5. Bakhshi-Raiez F, Peek N, Bosman RJ, de Jonge E, de Keizer NF (2007) The impact of different prognostic models and their customization on institutional comparison of intensive care units. Crit Care Med 35:2553–60

    Article  PubMed  Google Scholar 

  6. Pollack MM, Holubkov R, Funai T, et al (2016) The Pediatric Risk of Mortality Score: update 2015. Pediatr Crit Care Med 17:2–9

    Article  PubMed  PubMed Central  Google Scholar 

  7. Leteurtre S, Duhamel A, Grandbastien B, et al (2010) Daily estimation of the severity of multiple organ dysfunction syndrome in critically ill children. CMAJ 182:1181–7

    Article  PubMed  PubMed Central  Google Scholar 

  8. Straney L, Clements A, Parslow RC, et al (2013) Pediatric index of mortality 3: an updated model for predicting mortality in pediatric intensive care. Pediatr Crit Care Med 14:673–81

    Article  PubMed  Google Scholar 

  9. Wilkinson JD, Pollack MM, Ruttimann UE, Glass NL, Yeh TS (1986) Outcome of pediatric patients with multiple organ system failure. Crit Care Med 14:271–4

    Article  CAS  PubMed  Google Scholar 

  10. Proulx F, Fayon M, Farrell CA, Lacroix J, Gauthier M (1996) Epidemiology of sepsis and multiple organ dysfunction syndrome in children. Chest 109:1033–7

    Article  CAS  PubMed  Google Scholar 

  11. Leteurtre S, Martinot A, Duhamel A, et al (2003) Validation of the pediatric logistic organ dysfunction (PELOD) score: prospective, observational, multicentre study. Lancet 362:192–7

    Article  PubMed  Google Scholar 

  12. Leteurtre S, Duhamel A, Grandbastien B, Lacroix J, Leclerc F (2006) Pediatric logistic organ dysfunction (PELOD) score. Lancet 367:897

    Article  PubMed  Google Scholar 

  13. Ferreira FL, Bota DP, Bross A, Mélot C, Vincent JL (2001) Serial evaluation of the SOFA score to predict outcome in critically ill patients. JAMA 286:1754–8

    Article  CAS  PubMed  Google Scholar 

  14. Villeneuve A, Joyal JS, Proulx F, Ducruet T, Poitras N, Lacroix J (2016) Multiple organ dysfunction syndrome in critically ill children: clinical value of two lists of diagnostic criteria. Ann Intensive Care 6:40

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Vincent JL, Moreno R (2010) Clinical review: scoring systems in the critically ill. Crit Care 14:207

    Article  PubMed  PubMed Central  Google Scholar 

  16. Yeh TS, Pollack MM, Ruttimann UE, Holbrook PR, Fields AI (1984) Validation of a physiologic stability index for use in critically ill infants and children. Pediatr Res 18:445–51

    Article  CAS  PubMed  Google Scholar 

  17. Pollack MM, Ruttimann UE, Getson PR (1988) Pediatric risk of mortality (PRISM) score. Crit Care Med 16:1110–6

    Article  CAS  PubMed  Google Scholar 

  18. Pollack MM, Patel KM, Ruttimann UE (1996) PRISM III: an updated Pediatric Risk of Mortality Score. Crit Care Med 24:743–52

    Article  CAS  PubMed  Google Scholar 

  19. VPS PICU. In: http://www.myvps.org/. https://www.myvps.org/

  20. Pollack MM, Dean JM, Butler J, et al (2013) The ideal time interval for critical care severity-of-illness assessment. Pediatr Crit Care Med 14:448–53

    Article  PubMed  PubMed Central  Google Scholar 

  21. Shann F, Pearson G, Slater A, Wilkinson K (1997) Pediatric index of mortality (PIM): a mortality prediction model for children in intensive care. Intensive Care Med 23:201–7

    Article  CAS  PubMed  Google Scholar 

  22. Slater A, Shann F, Pearson G, Pediatric Index of Mortality (PIM) Study Group (2003) PIM2: a revised version of the Pediatric Index of Mortality. Intensive Care Med 29:278–85

    Article  PubMed  Google Scholar 

  23. Wolfler A, Osello R, Gualino J, et al (2016) The importance of mortality risk assessment: Validation of the Pediatric Index of Mortality 3 Score. Pediatr Crit Care Med 17:251–6

    Article  PubMed  Google Scholar 

  24. Gulla KM, Sachdev A (2016) Illness severity and organ dysfunction scoring in pediatric intensive care unit. Indian J Crit Care Med 20:27–35

    Article  PubMed  PubMed Central  Google Scholar 

  25. Leteurtre S, Martinot A, Duhamel A, et al (1999) Development of a pediatric multiple organ dysfunction score: use of two strategies. Med Decis Making 19:399–410

    Article  CAS  PubMed  Google Scholar 

  26. Garcia PCR, Eulmesekian P, Branco RG, et al (2010) External validation of the pediatric logistic organ dysfunction score. Intensive Care Med 36:116–22

    Article  PubMed  Google Scholar 

  27. Leteurtre S, Duhamel A, Salleron J, et al (2013) PELOD-2: an update of the Pediatric Logistic Organ Dysfunction Score. Crit Care Med 41:1761–73

    Article  PubMed  Google Scholar 

  28. Leteurtre S, Duhamel A, Deken V, Lacroix J, Leclerc F; Groupe Francophone de Réanimation et Urgences Pédiatriques (2015) Daily estimation of the severity of organ dysfunctions in critically ill children by using the PELOD-2 score. Crit Care 19:324

    Article  PubMed  PubMed Central  Google Scholar 

  29. Graciano AL, Balko JA, Rahn DS, Ahmad N, Giroir BP (2005) The Pediatric Multiple Organ Dysfunction Score (P-MODS): development and validation of an objective scale to measure the severity of multiple organ dysfunction in critically ill children. Crit Care Med 33:1484–91

    Article  PubMed  Google Scholar 

  30. Shann F (2002) Are we doing a good job: PRISM, PIM and all that. Intensive Care Med 28:105–7

    Article  CAS  PubMed  Google Scholar 

  31. Keegan MT, Gajic O, Afessa B (2011) Severity of illness scoring systems in the intensive care unit. Crit Care Med 39:163–9

    Article  PubMed  Google Scholar 

  32. Deeks JJ, Altman DG (1999) Sensitivity and specificity and their confidence intervals cannot exceed 100%. BMJ 318:193–4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lemeshow S, Hosmer DW (1982) A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 115:92–106

    CAS  PubMed  Google Scholar 

  34. Peek N, Arts DG, Bosman RJ, van der Voort PH, de Keizer NF (2007) External validation of prognostic models for critically ill patients required substantial sample sizes. J Clin Epidemiol 60:491–501

    Article  CAS  PubMed  Google Scholar 

  35. Murphy-Filkins R, Teres D, Lemeshow S, Hosmer DW (1996) Effect of changing patient mix on the performance of an intensive care unit severity-of-illness model: how to distinguish a general from a specialty intensive care unit. Crit Care Med 24:1968–73

    Article  CAS  PubMed  Google Scholar 

  36. Pearson GA, Stickley J, Shann F (2001) Calibration of the pediatric index of mortality in UK pediatric intensive care units. Arch Dis Child 84:125–8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Tibby SM, Murdoch IA (2002) Calibration of the pediatric index of mortality score for UK pediatric intensive care. Arch Dis Child 86:65; author reply 65–66

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Minne L, Abu-Hanna A, de Jonge E (2008) Evaluation of SOFA-based models for predicting mortality in the ICU: a systematic review. Crit Care 12:R161

    Article  PubMed  PubMed Central  Google Scholar 

  39. Metnitz PG, Lang T, Vesely H, Valentin A, Le Gall JR (2000) Ratios of observed to expected mortality are affected by differences in case mix and quality of care. Intensive Care Med 26:1466–72

    Article  CAS  PubMed  Google Scholar 

  40. Metnitz B, Schaden E, Moreno R, et al (2009) Austrian validation and customization of the SAPS 3 Admission Score. Intensive Care Med 35:616–22

    Article  PubMed  Google Scholar 

  41. Kramer AA, Higgins TL, Zimmerman JE (2014) Comparison of themortality probability admission model III, national quality forum, and acute physiology and chronic health evaluation IV hospital mortality models: implications for national benchmarking. Crit Care Med 42:544–53

    Article  PubMed  Google Scholar 

  42. Wolfler A, Silvani P, Musicco M, Salvo I; Italian Pediatric Sepsis Study (SISPe) Group (2007) Pediatric Index of Mortality 2 score in Italy: a multicenter, prospective, observational study. Intensive Care Med 33:1407–13

    Article  PubMed  Google Scholar 

  43. Vincent JL, Opal SM, Marshall JC (2010) Ten reasons why we should NOT use severity scores as entry criteria for clinical trials or in our treatment decisions. Crit Care Med 38:283–7

    Article  PubMed  Google Scholar 

  44. Lacroix J, Hébert PC, Hutchison JS, et al (2007) Transfusion strategies for patients in pediatric intensive care units. N Engl J Med 356:1609–19

    Article  CAS  PubMed  Google Scholar 

  45. Bernard GR, Vincent JL, Laterre PF, et al (2001) Efficacy and safety of recombinant human activated protein C for severe sepsis. N Engl J Med 344:699–709

    Article  CAS  PubMed  Google Scholar 

  46. Glance LG, Osler T, Shinozaki T (2000) Effect of varying the case mix on the standardized mortality ratio and W statistic: a simulation study. Chest 117:1112–7

    Article  CAS  PubMed  Google Scholar 

  47. Leteurtre S, Grandbastien B, Leclerc F, et al (2012) International comparison of the performance of the pediatric index of mortality (PIM) 2 score in two national data sets. Intensive Care Med 38:1372–80

    Article  PubMed  Google Scholar 

  48. Kramer AA, Higgins TL, Zimmerman JE (2015) Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ? Crit Care Med 43:261–9

    Article  PubMed  Google Scholar 

  49. Namachivayam P, Shann F, Shekerdemian L, et al (2010) Three decades of pediatric intensive care: Who was admitted, what happened in intensive care, and what happened afterward. Pediatr Crit Care Med 11:549–55

    Article  PubMed  Google Scholar 

  50. Epstein D, Wong CF, Khemani RG, et al (2011) Race/ethnicity is not associated with mortality in the PICU. Pediatrics 127: e588–e97

    Article  PubMed  Google Scholar 

  51. Pollack MM, Holubkov R, Funai T, et al (2015) Simultaneous prediction of new morbidity, mortality, and survival without new morbidity from pediatric intensive care: a new paradigm for outcomes assessment. Crit Care Med 43:1699–709

    Article  PubMed  PubMed Central  Google Scholar 

  52. Pollack MM, Holubkov R, Glass P, et al (2009) Functional Status Scale: new pediatric outcome measure. Pediatrics 124:e18–e28

    Article  PubMed  PubMed Central  Google Scholar 

  53. Aspesberro F, Mangione-Smith R, Zimmerman JJ (2015) Health-related quality of life following pediatric critical illness. Intensive Care Med 41:1235–46

    Article  PubMed  Google Scholar 

  54. Varni JW, Seid M, Kurtin PS (2001) PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations. Med Care 39:800–12

    Article  CAS  PubMed  Google Scholar 

  55. Tessier S, Vuillemin A, Lemelle JL, Briançon S (2009) Propriétés psychométriques du questionnaire générique français « Pediatric Quality of Life Inventory Version 4.0 » (PedsQLTM 4.0). Eur Rev Appl Psychol 59:291–300

    Article  Google Scholar 

  56. Ravens-Sieberer U, Auquier P, Erhart M, et al (2007) The KIDSCREEN-27 quality of life measure for children and adolescents: psychometric results from a cross-cultural survey in 13 European countries. Qual Life Res 16:1347–56

    Article  PubMed  Google Scholar 

  57. PICANet. http://www.picanet.org.uk/

  58. Straney LD, Clements A, Alexander J, Slater A (2010) Measuring efficiency in Australian and New Zealand pediatric intensive care units. Intensive Care Med 36:1410–6

    Article  PubMed  Google Scholar 

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Leteurtre, S., Lampin, ME., Grandbastien, B. et al. Les scores de gravité généraux et de dysfonctions d’organes en réanimation pédiatrique : quoi de neuf en 2016 ?. Méd. Intensive Réa 25, 604–618 (2016). https://doi.org/10.1007/s13546-016-1220-5

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  • DOI: https://doi.org/10.1007/s13546-016-1220-5

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