Skip to main content

The Changing Prognostic Determinants in the Critically III Patient

  • Conference paper
Intensive Care Medicine
  • 946 Accesses

Abstract

The science and art of risk stratification appeared in early 1953, when Virginia Apgar [1] published a simple physiological scoring tool to evaluate the newborn child. This system, still commonly used worldwide, evaluates only two physiologic systems: Cardiopulmonary and central nervous system (CNS) function. Several years later, in the early 1980s, several researchers applied the same concept to critically ill patients, through the introduction of the acute physiology and chronic health evaluation (APACHE) and the simplified acute physiological score (SAPS), both physiologically based classification systems [2, 3]. These instruments, named general severity scores, are tools that aim at stratifying patients based on their severity, assigning to each patient an increasing score as their severity of illness increases. Initially designed to be applicable to individual patients, it became apparent very early after their introduction that both systems could in fact be used only in large heterogeneous groups of critically ill patients.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Apgar V (1953) A proposal for a new method of evaluation of the newborn infant. Anesth Analg 32:260–267

    Article  CAS  Google Scholar 

  2. Knaus WA, Zimmerman JE, Wagner DP, Draper EA, Lawrence DE (1981) APACHE — acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med 9:591–597

    Article  PubMed  CAS  Google Scholar 

  3. Le Gall JR, Loirat P, Alperovitch A (1983) Simplified acute physiological score for intensive care patients. Lancet 2:741

    Article  PubMed  Google Scholar 

  4. Knaus WA, Draper EA, Wagner DP, Zimmerman JE (1985) APACHE II: a severity of disease classification system. Crit Care Med 13:818–829

    Article  PubMed  CAS  Google Scholar 

  5. Lemeshow S, Teres D, Pastides H, et al (1985) A method for predicting survival and mortality of ICU patients using objectively derived weights. Crit Care Med 13:519–525

    Article  PubMed  CAS  Google Scholar 

  6. Le Gall JR, Lemeshow S, Saulnier F (1993) A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 270:2957–2963

    Article  PubMed  Google Scholar 

  7. Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J (1993) Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. JAMA 270:2478–2486

    Article  PubMed  CAS  Google Scholar 

  8. Knaus WA, Wagner DP, Draper EA, et al (1991) The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 100:1619–1636

    PubMed  CAS  Google Scholar 

  9. Suter P, Armagandis A, Beaufils F, et al (1994) Predicting outcome in ICU patients: consensus conference organized by the ESICM and the SRLF. Intensive Care Med 20:390–397

    Article  Google Scholar 

  10. Moreno R, Matos R (2000) The “new” scores: what problems have been fixed, and what remain. Curr Opin Crit Care 6:158–165

    Article  Google Scholar 

  11. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR (2001) Epidemiology of severe sepsis in the United States: analysis of incidence, outcome and associated costs of care. Crit Care Med 29:1303–1310

    Article  PubMed  CAS  Google Scholar 

  12. Martin GS, Mannino DM, Eaton S, Moss M (2003) The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 348:1546–1554

    Article  PubMed  Google Scholar 

  13. Bernard GR, Vincent J-L, 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  PubMed  CAS  Google Scholar 

  14. Ely EW, Laterre P-F, Angus DC, et al (2003) Drotrecogin alfa (activated) administration across clinically important subgroups of patients with severe sepsis. Crit Care Med 31:12–19

    Article  PubMed  CAS  Google Scholar 

  15. Moreno R, Apolone G (1997) The impact of different customization strategies in the performance of a general severity score. Crit Care Med 25:2001–2008

    Article  PubMed  CAS  Google Scholar 

  16. Zhu B-P, Lemeshow S, Hosmer DW, Klarm J, Avrunin J, Teres D (1996) Factors affecting the performance of the models in the mortality probability model and strategies of customization: a simulation study. Crit Care Med 24:57–63

    Article  PubMed  CAS  Google Scholar 

  17. Le Gall JR, Lemeshow S, Leleu G, et al (1995) Customized probability models for early severe sepsis in adult intensive care patients. JAMA 273:644–650

    Article  PubMed  Google Scholar 

  18. Apolone G, D’Amico R, Bertolini G, et al (1996) The performance of SAPS II in a cohort of patients admitted in 99 Italian ICUs: results from the GiViTI. Intensive Care Med 22:1368–1378

    Article  PubMed  CAS  Google Scholar 

  19. Rivera-Fernandez R, Vazquez-Mata G, Bravo M, et al (1998) The Apache III prognostic system: customized mortality predictions for Spanish ICU patients. Intensive Care Med 24: 574–581

    Article  PubMed  CAS  Google Scholar 

  20. Zimmerman JE, Wagner DP, Draper EA, Wright L, Alzola C, Knaus WA (1998) Evaluation of acute physiology and chronic health evaluation III predictions of hospital mortality in an independent database. Crit Care Med 26:1317–1326

    Article  PubMed  CAS  Google Scholar 

  21. Zimmerman JE, Kramer AA, McNair DS, Malila FM (2006) Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients. Crit Care Med 34:1297–1310

    Article  PubMed  Google Scholar 

  22. Metnitz PG, Valentin A, Vesely H, et al (1999) Prognostic performance and customization of the SAPS II: results of a multicenter Austrian study. Intensive Care Med 25:192–197

    Article  PubMed  CAS  Google Scholar 

  23. Moreno R, Apolone G, Reis Miranda D (1998) Evaluation of the uniformity of fit of general outcome prediction models. Intensive Care Med 24:40–47

    Article  PubMed  CAS  Google Scholar 

  24. Le Galll J-R, Neumann A, Hemery F, et al (2005) Mortality prediction using SAPS II: an update for French intensive care units. Crit Care 9:R645–R652

    Article  Google Scholar 

  25. Aegerter P, Boumendil A, Retbi A, Minvielle E, Dervaux B, Guidet B (2005) SAPS II revisited. Intensive Care Med 31:416–423

    Article  PubMed  Google Scholar 

  26. Harrison DA, Brady AR, Parry GJ, Carpenter JR, Rowan K (2006) Recalibration of risk prediction models in a large multicenter cohort of admissions to adult, general critical care units in the United Kingdom. Crit Care Med 34:1378–1388

    Article  PubMed  Google Scholar 

  27. Rowan KM, Kerr JH, Major E, McPherson K, Short A, Vessey MP (1993) Intensive Care Society’s APACHE II study in Britain and Ireland — II: Outcome comparisons of intensive care units after adjustment for case mix by the American APACHE II method. BMJ 307:977–981

    Article  PubMed  CAS  Google Scholar 

  28. Metnitz PG, Moreno RP, Almeida E, et al (2005) SAPS 3. From evaluation of the patient to evaluation of the intensive care unit. Part 1: Objectives, methods and cohort description. Intensive Care Med 31:1336–1344

    Article  PubMed  Google Scholar 

  29. Moreno RP, Metnitz PG, Almeida E, et al (2005) SAPS 3. From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med 31:1345–1355

    Article  PubMed  Google Scholar 

  30. Moreno R, Metnitz P, Jordan B, Einfalt J, Bauer P (2006) SAPS 3 28 days score: a prognostic model to estimate patient survival during the first 28 days in the ICU. Intensive Care Med 32:S203 (abst)

    Article  Google Scholar 

  31. Rothen H, Stricker K, Einfalt J, Metnitz P, Moreno R, Takala J (2006) Variability in outcome and resource use in ICU’S. Intensive Care Med 32:S138 (abst)

    Google Scholar 

  32. Zimmerman JE, Kramer AA, McNair DS, Malila FM, Shaffer VL (2006) Intensive care unit length of stay: Benchmarking based on Acute Physiology and Chronic Health Evaluation (APACHE) IV. Crit Care Med 34:2517–2529

    Article  PubMed  Google Scholar 

  33. Higgins T, Teres D, Copes W, Nathanson B, Stark M, Kramer A (2005) Preliminary update of the Mortality Prediction Model (MPM0). Crit Care 9:S97 (abst)

    Article  Google Scholar 

  34. Harrison D, Parry G, Carpenter J, Short A, Rowan K (2006). A new risk prediction model: the Intensive Care National Audit & Research Centre (ICNARC) model. Intensive Care Med 32:S204 (abst)

    Google Scholar 

  35. Niskanen M, Kari A, Halonen P (1996) Five-year survival after intensive care — comparison of 12,180 patients with the general population. Crit Care Med 24:1962–1967

    Article  PubMed  CAS  Google Scholar 

  36. Bion JF (2000) Susceptibility to critical illness: reserve, response and therapy. Intensive Care Med 26:S57–S63

    Article  PubMed  Google Scholar 

  37. Villar J, Flores C, Méndez-Alvarez S (2003) Genetic susceptibility to acute lung injury. Crit Care Med 31:S272–S275

    Article  PubMed  Google Scholar 

  38. Villar J, Maca-Meyer N, Pérez-Méndez L, Flores C (2004) Bench-to-bedside review: Understanding genetic predisposition to sepsis. Crit Care 8:180–189

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Science + Business Media Inc.

About this paper

Cite this paper

Moreno, R., Jordan, B., Metnitz, P. (2007). The Changing Prognostic Determinants in the Critically III Patient. In: Vincent, JL. (eds) Intensive Care Medicine. Springer, New York, NY. https://doi.org/10.1007/978-0-387-49518-7_81

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-49518-7_81

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-49517-0

  • Online ISBN: 978-0-387-49518-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics