Skip to main content

Predicting outcome in ICU patients

Intensive Care Medicine volume 20, pages 390–397 (1994)Cite this article

Conclusions

Considerable time and energy has been invested in the conception, modelling and evaluation of sophisticated severity scoring systems for ICU patients. These systems are created to enhance the precise estimation of hospital mortality for large ICU patient populations. Their current low sensitivity precludes their use for predicting out-come for individual ICU patients. However, severity scores can already be valuable for predicting mortality in groups of general ICU patients, and are very useful in the clinical trial setting.

Outcome of ICU therapy, however, should incorporate more than mortality. Morbidity, disability and quality of life should also be taken into account; these factors were not taken into consideration in the design of the currently available severity scoring systems.

At present, the severity scores have a very limited or no role in clinical decision-making for an individual patient, because they are based on a number of physiological and disease-oriented variables collected during the first 24 h after ICU admission. Future developments and subsequent validation of the dynamic process of clinical, physiological and organ-specific variables could improve the sensitivity and the value of severity scoring. Further collaborative developmental work in this field should be encouraged and supported across Europe and North America.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

References

  • Baker SP, O'Neil B, Haddon W, Long WB (1974) The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma 14:187–196

    Google Scholar 

  • Beaufils FR, Roze JC, Azema D, Hamoir GF, Bloc D, Floret D, Stopfkuchen H, De Jong De Vos Van Steenwijk CCE, Van der Voort E, Mar Molinero F (1987) Evaluation of pediatric intensive care in Europe. A collaborative study by the European Club of Pediatric Intensive Care. Intensive Care Med 13:65–75

    Google Scholar 

  • Bowling A (1991) Measuring health: a review of quality of life measurement scales. Open Univ Press, Milton Keynes, Philadelphia

    Google Scholar 

  • Boyd O, Grounds RM (1993) Physiological scoring systems and audit. Lancet 341:1573–1574

    Google Scholar 

  • Chang RWS (1989) Individual outcome prediction models for intensive care units. Lancet II:143–146

    Google Scholar 

  • Chang RWS, Jacobs S, Lee B (1988) Predicting outcome among intensive care unit patients using computerised trend analysis of daily APACHE II scores corrected for organ system failure. Intensive Care Med 14:558–566

    Google Scholar 

  • Christiansen C, Cottrell JJ, Murakami J, Mackesy ME, Fetzer B, Elstein AS (1993) Forecasting survival in the medical intensive care unit: A comparison of clinical prognoses with formal estimates. Methods of Information in Medicine 32:302–308

    Google Scholar 

  • Cullen DJ, Civetta JM, Briggs BA, Ferrara LC (1974) Therapeutic intervention scoring system: a method for quantitative comparison of patient care. Crit Care Med 2:57–60

    Google Scholar 

  • Elebute ER, Stoner HB (1983) The grading of sepsis. Br J Surg 70:29–31

    Google Scholar 

  • Guyatt GH, Feeney DH, Patrick DL (1993) Measuring health-related quality of life. Ann Intern Med 118:622–629

    Google Scholar 

  • Kassirer JP (1993) The quality of care and the quality of measuring it. N Engl J Med 329:1263–1265

    Google Scholar 

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

    Google Scholar 

  • Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Sirio CA, Murphy DJ, Lotring T, Damiano A, Harrell FE Jr (1991) The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 100:1619–1936

    Google Scholar 

  • Le Gall JR, Loirat P, Alperovitch A et al (1984) A simplified acute physiological score for ICU patients. Crit Care Med 12:975–977

    Google Scholar 

  • Le Gall JR, Lemeshow S, Saulnier F and the study participants (1993) Development of the SAPS II system from a European/North American multicenter study. JAMA 270:2957–2963

    Google Scholar 

  • Lemeshow S, Teres D, Avrunin JS, Pastides H (1988) Predicting the outcome of intensive care unit patients. JAMA 83:348–356

    Google Scholar 

  • Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J and the study participants for data set I (1993) Mortality probability models (MPM II) based on an international cohort of intensive care unit patients. JAMA 270:2478–2486

    Google Scholar 

  • Murray LS, Teasdale GM, Murray GD, Jennett B, Miller JD, Pickard JD, Shaw MDM, Achilles J, Bailey S, Jones P, Kelly D, Lacey J (1993) Does prediction of outcome alter patient management? Lancet 341:1487–1491

    Google Scholar 

  • Pollack MM, Ruttiman UE, Getson PR (1988) Pediatric risk of mortality (PRISM) score. Crit Care Med 16:1110–1116

    Google Scholar 

  • Price HL, Matthew DJ (1989) Evaluation of pediatric intensive care scoring systems. Intensive Care Med 15:79–83

    Google Scholar 

  • Ranson JHC, Rifkind KM, Roses DF, Kink SD, Eng K, Spencer FC (1974) Prognosis signs and the role of operative management in acute pancreatitis. Surg Gynecol Obstet 139:69–81

    Google Scholar 

  • Selker HP (1993) Systems for comparing actual and predicted mortality rates: Characteristics to promote cooperation in improving hospital care. Ann Intern Med 118:820–822

    Google Scholar 

  • Schuster DP (1992) Predicting outcome after ICU admission. The art and science of assessing risk. Chest 102:1861–1870

    Google Scholar 

  • Sirio CA, Tajimi KT, Tase C (1992) An initial comparison of intensive care in Japan and the United States. Crit Care Med 20:1207–1215

    Google Scholar 

  • Teasdale G, Jennett B (1974) Assessment of coma and impaired consciousness. Lancet II:81–84

    Google Scholar 

  • Wasson JH, Sox HC, Neff RK, Goldman L (1985) Clinical prediction rules. Applications and methodological standards. N Engl J Med 313:793–799

    Google Scholar 

Download references

Authors
  1. P. Suter
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Armaganidis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. F. Beaufils
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. X. Bonfill
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. H. Burchardi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. D. Cook
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A. Fagot-Largeault
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. L. Thijs
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. S. Vesconi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. J. R. Le Gall
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. R. Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

2nd European Consensus Conference in Intensive Care Medicine. Held in Paris, France, December 9–10, 1993

This conference was organized and held according to methodologic principles set forth by the “Agence Nationale pour le Développement et l'Evaluation Médicale” (ANDEM), which has given it its approval. However, conclusions and recommendations expressed herein are made under the responsibility of the jury, and do not imply endorsement by ANDEM

Invited experts: B. Jennett (Glasgow, UK), L. Dragsted (Herlev, DK), P. Minaire (St. Etienne, F), W. Knaus (Washington, USA), A. Mulley (Boston, USA), J.L. Vincent (Brussels, B), Ph. Loirat (Suresnes, F), S. Jacobs (Riyadh, Saudi Arabia), F. Nicolas (Nantes, F), J. Pfenninger (Berne, CH), D. Reis-Miranda (Groningen, NL), M. Smithies (London, UK), S. Lemeshow (Amherst, USA), D. Teres (Springfield, USA), R.J. Kahn (Brussels, B)

The text of the experts will be published in “Réanimation, Urgences” (Arnette ed., Paris) together with the French version of this Consensus Summary

This conference has been organized with the help of the following pharmaceutical companies: Bayer, Institut Beaufour, Institut Beecham, Glaxo, Hoechst, Iris (Servier), Lederle, Pfizer, Roche, Specia

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Suter, P., Armaganidis, A., Beaufils, F. et al. Predicting outcome in ICU patients. Intensive Care Med 20, 390–397 (1994). https://doi.org/10.1007/BF01720917

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01720917

Keywords

  • North America
  • Dynamic Process
  • Future Development
  • Severity Score
  • Hospital Mortality