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Evaluating Critical Care pp 51–68Cite as

Severity of Illness

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Part of the book series: Update in Intensive Care Medicine ((UICMSOFT,volume 35))

As a direct result of the polio epidemics of the 1950s, critical care medicine developed in the Western world. This new field of medical practice was supported over the following decades by rapid developments in monitoring and therapeutic technologies, by a growing body of knowledge about the physiopathological alterations of the critically ill patient, and by the appearance of new therapeutic strategies. Soon, the intensive care unit (ICU) transformed itself from a small and marginal place in the hospital, where critically ill patients were monitored and treated, to a full hospital department, responsible for the consumption of a growing proportion of the health care budget.

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References

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

    Article  CAS  Google Scholar 

  2. 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

    Article  PubMed  CAS  Google Scholar 

  3. 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 

  4. Knaus WA, Draper EA, Wagner DP, et al (1982) Evaluating outcome from intensive care: A preliminary multihospital comparison. Crit Care Med 10:491–496

    Article  PubMed  CAS  Google Scholar 

  5. 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 

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

    Article  PubMed  CAS  Google Scholar 

  7. 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 

  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

    Article  PubMed  CAS  Google Scholar 

  9. 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  CAS  Google Scholar 

  10. 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 

  11. Lemeshow S, Klar J, Teres D, et al (1994) Mortality probability models for patients in the intensive care unit for 48 or 72 hours: a prospective, multicenter study. Crit Care Med 22:1351–1358

    Article  PubMed  CAS  Google Scholar 

  12. Knaus WA, Draper EA, Wagner DP, Zimmerman JE (1985) Prognosis in acute organ-system failure. Ann Surg 202:685–693

    Article  PubMed  CAS  Google Scholar 

  13. Bernard G (1997) The Brussels score. Sepsis 1:43–44

    Article  Google Scholar 

  14. Marshall JC, Cook DA, Christou NV, Bernard GR, Sprung CL, Sibbald WJ (1995) Multiple organ dysfunction score: a reliable descriptor of a complex clinical outcome. Crit Care Med 23:1638–1652

    Article  PubMed  CAS  Google Scholar 

  15. Le Gall JR, Klar J, Lemeshow S, et al (1996) The logistic organ dysfunction system. A new way to assess organ dysfunction in the intensive care unit. JAMA 276:802–810

    Article  PubMed  CAS  Google Scholar 

  16. Vincent J-L, Moreno R, Takala J, et al (1996) The SOFA (Sepsis-related organ failure assessment) score to describe organ dysfunction/failure. Intensive Care Med 22:707–710

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  18. Chamion HR, Sacco WJ, Copes WS, Gann DS, Gennarelli TA, Flanagan ME (1989) A revision of the trauma score. J Trauma 29:623–629

    Article  Google Scholar 

  19. Boyd C, Toison M, Copes W (1987) Evaluating trauma care: the TRISS method. J Trauma 27:370–378

    Article  PubMed  CAS  Google Scholar 

  20. Champion HR, Copes WS, Sacco WJ, et al (1996) Improved predictions from a severity characterization of trauma (ASCOT) over trauma and injury severity score (TRISS): results of an independent evaluation. J Trauma 40:42–49

    Article  PubMed  CAS  Google Scholar 

  21. Agarwal N, Pitchumoni CS (1991) Assessment of severity in acute pancreatitis. Am J Gastroenterol 86:1385–1391

    PubMed  CAS  Google Scholar 

  22. Ranson JHC, Rifkind KM, Roses DF, et al (1974) Prognostic signs and the role of operative management in acute pancreatitis. Surg Gynecol Obstet 139:69–81

    PubMed  CAS  Google Scholar 

  23. Osborne DH, Imrie CW, Carter DC (1981) Biliary surgery in the same admission for gallstone-associated acute pancreatitis. Br J Surg 68:758–761

    Article  PubMed  CAS  Google Scholar 

  24. Fan ST, Choi TK, Wong J (1989) Prediction of severity of acute pancreatitis: an alternative approach. Gut 30:1591–1595

    Article  PubMed  CAS  Google Scholar 

  25. Tran DD, Cuesta MA (1992) Evaluation of severity in patients with acute pancreatitis. Am J Gastroenterol 87:604–608

    PubMed  CAS  Google Scholar 

  26. Bradley EL (1993) A clinically based classification system for acute pancreatitis. Arch Surg 128:586–590

    Article  PubMed  Google Scholar 

  27. Niederau C, Luthen R, Heise JW, Becker H (1993) Prognosis of acute pancreatitis. In: Beger HG, Buchler M, Malfertheiner P (eds) Standards in Pancreatic Surgery, Springer-Verlag, Berlin pp76–91

    Chapter  Google Scholar 

  28. Tran DD, Cuesta MA, Schneider AJ, Wesdorp RI (1993) Prevalence and prediction of multiple organ system failure and mortality in acute pancreatitis. J Crit Care 8:145–153

    Article  PubMed  CAS  Google Scholar 

  29. Balthazar EJ, Ranson JHC, Naidich DP, Megibaw AJ, Caccavale R, Cooper MM (1985) Acute pancreatitis: prognostic value of CT. Radiology 156:767–772

    PubMed  CAS  Google Scholar 

  30. Larvin M, McMahon MJ (1989) APACHE-II score for assessment and monitoring of acute pancreatitis. Lancet 2:201–205

    Article  PubMed  CAS  Google Scholar 

  31. Wilson C, Heath DI, Imrie CW (1990) Prediction of outcome in acute pancreatitis: a comparative study of APACHE II, clinical assessment and multiple factor scoring systems. Br J Surg 77:1260–1264

    Article  PubMed  CAS  Google Scholar 

  32. Arnell TD, de Virgilio C, Chang L, Bongard F, Stabile BE (1996) Admission factors can predict the need for ICU monitoring in gallstone pancreatitis. Dig Surg 14283–14298

    Google Scholar 

  33. Brisinda G, Maria G, Ferrante A, Civello IM (1999) Evaluation of prognostic factors in patients with acute pancreatitis. Hepatogastroenterology 46:1990–1997

    PubMed  CAS  Google Scholar 

  34. Armengol-Carrasco M, Oller B, Escudero LE, et al (1999) Specific prognostic factors for secondary pancreatic infection in severe acute pancreatitis. Dig Surg 16:125–129

    Article  PubMed  CAS  Google Scholar 

  35. Williams M, Simms H (1999) Prognostic usefulness of scoring systems in critically ill patients with severe acute pancreatitis. Crit Care Med 27:901–907

    Article  PubMed  CAS  Google Scholar 

  36. Matos R, Moreno R, Fevereiro T (2000) Severity evaluation in acute pancreatitis: the role of SOFA score and general severity scores. Crit Care 4:S138 (abst)

    Google Scholar 

  37. Dragsted L, Jorgensen J, Jensen NH, et al (1989) Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias. Crit Care Med 17:418–422

    Article  PubMed  CAS  Google Scholar 

  38. Tunnell RD, Millar BW, Smith GB (1998) The effect of lead time bias on severity of illness scoring, mortality prediction and standardised mortality ratio in intensive care — a pilot study. Anaesthesia 53:1045–1053

    Article  PubMed  CAS  Google Scholar 

  39. Lundberg JS, Perl TM, Wiblin T, et al (1998) Septic shock: an analysis of outcomes for patients with onset on hospital wards versus intensive care units. Crit Care Med 26:1020–1024

    Article  PubMed  CAS  Google Scholar 

  40. 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 

  41. 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 

  42. 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 

  43. Abizanda Campos R, Balerdi B, Lopez J, et al (1994) Fallos de prediccion de resultados mediante APACHE II. Analisis de los errores de prediction de mortalidad en pacientes criticos. Med Clin Bare 102:527–531

    Google Scholar 

  44. Fery-Lemmonier E, Landais P, Kleinknecht D, Brivet F (1995) Evaluation of severity scoring systems in the ICUs: translation, conversion and definitions ambiguities as a source of interobserver variability in APACHE II, SAPS, and OSE Intensive Care Med 21:356–360

    Article  Google Scholar 

  45. Rowan K (1996) The reliability of case mix measurements in intensive care. Curr Opin Crit Care 2:209–213

    Article  Google Scholar 

  46. Bosman RJ, Oudemane van Straaten HM, Zandstra DF (1998) The use of intensive care information systems alters outcome prediction. Intensive Care Med 24:953–958

    Article  PubMed  CAS  Google Scholar 

  47. Damiano AM, Bergner M, Draper EA, Knaus WA, Wagner DP (1992) Reliability of a measure of severity of illness: acute physiology and chronic health evaluation -II. J Clin Epidemiol 45:93–101

    Article  PubMed  CAS  Google Scholar 

  48. Goldhill DR, Sumner A (1998) APACHE II, data accuracy and outcome prediction. Anaesthesia 53:937–943

    Article  PubMed  CAS  Google Scholar 

  49. Polderman KH, Thijs LG, Girbes AR (1999) Interobserver variability in the use of APACHE II scores. Lancet 353:380

    Article  PubMed  CAS  Google Scholar 

  50. Chen LM, Martin CM, Morrison TL, Sibbald WJ (1999) Interobserver variability in data collection of the APACHE II score in teaching and community hospitals. Crit Care Med 27:1999–2004

    Article  PubMed  CAS  Google Scholar 

  51. Gattinoni L, Brazzi L, Pelosi P, et al (1995) A trial of goal orientated hemodynamic therapy in critically ill patients. N Engl J Med 333:1025–1032

    Article  PubMed  CAS  Google Scholar 

  52. Galbân C, Montejo JC, Masejo A, et al (2000) An immune-enhancing enteral diet reduces mortality rate and episodes of bacteremia in septic intensive care unit patients. Crit Care Med 28:643–648

    Article  PubMed  Google Scholar 

  53. Moreno R, Estrada H, Miranda I, Massa L (1994) SAPS II over time: a preliminary study. Clin Intensive Care 5:S122 (abst)

    Google Scholar 

  54. Wagner DP, Knaus WA, Harrel Jr. FE, Zimmerman JE, Watts C (1994) Daily prognostic estimates for critically ill adults in intensive care units: results from a prospective, multicenter, inception cohort analysis. Crit Care Med 22:1359–1372

    Article  PubMed  CAS  Google Scholar 

  55. Chang RW (1989) Individual outcome prediction models for intensive care units. Lancet i:143–146

    Google Scholar 

  56. Jacobs S, Arnold A, Clyburn PA, Willis BA (1992) The Riyadh intensive care program applied to a mortality analysis of a teaching hospital intensive care unit. Anaesthesia 47:775–780

    Article  PubMed  CAS  Google Scholar 

  57. Perkins HS, Jonsen AR, Epstein WV (1986) Providers as predictors: using outcome predictions in intensive care. Crit Care Med 14:105–110

    Article  PubMed  CAS  Google Scholar 

  58. Silverstein MD (1988) Predicting instruments and clinical judgement in critical care. JAMA 260:1758–1759

    Article  PubMed  CAS  Google Scholar 

  59. Dawes RM, Faust D, Mechl PE (1989) Clinical versus actuarial judgement. Science 243:1668–74.

    Article  PubMed  CAS  Google Scholar 

  60. Kleinmuntz B (1990) Why we still use our heads instead of formulas: toward an integrative approach. Psychol Bull 107:296–310

    Article  PubMed  CAS  Google Scholar 

  61. McClish DK, Powell SH (1989) How well can physicians estimate mortality in a medical intensive care unit? Med Decis Making 9:125–132

    Article  PubMed  CAS  Google Scholar 

  62. Poses RM, Bekes C, Winkler RL, Scott WE, Copare F J (1990) Are two (inexperienced) heads better than one (experienced) head? Averaging house officers prognostic judgement for critically ill patients. Arch Intern Med 150:1874–1878

    Article  PubMed  CAS  Google Scholar 

  63. Poses RM, Bekes C, Copare FJ, et al (1989) The answer to “what are my chances, doctor?” depends on whom is asked: prognostic disagreement and inaccuracy for critically ill patients. Crit Care Med 17:827–833

    Article  PubMed  CAS  Google Scholar 

  64. Winkler RL, Poses RM (1993) Evaluating and combining physicians probabilities of survival in an intensive care unit. Manag Sci 39:1526–1543

    Article  Google Scholar 

  65. Marcin JP, Pollack MM, Patel KM, Ruttimann UE (1998) Decision support issues using a physiology based score. Intensive Care Med 24:1299–1304

    Article  PubMed  CAS  Google Scholar 

  66. Chang RWS, Lee B, Jacobs S, Lee B (1989) Accuracy of decisions to withdraw therapy in critically ill patients: clinical judgement versus a computer model. Crit Care Med 17:1091–1097

    Article  PubMed  CAS  Google Scholar 

  67. Knaus WA, Rauss A, Alperovitch A, et al (1990) Do objective estimates of chances for survival influence decisions to withhold or withdraw treatment? Med Decis Making 10:163–171

    Article  PubMed  CAS  Google Scholar 

  68. Zimmerman JE, Wagner DP, Draper EA, Knaus WA (1994) Improving intensive care unit discharge decisions: supplementary physician judgment with predictions of next day risk for life support. Crit Care Med 22:1373–1384

    Article  PubMed  CAS  Google Scholar 

  69. Branner AL, Godfrey LJ, Goetter WE (1989) Prediction of outcome from critical illness: a comparison of clinical judgement with a prediction rule. Arch Intern Med 149:1083–1086

    Article  Google Scholar 

  70. Kruse JA, Thill-Baharozin MC, Carlson RW (1988) Comparison of clinical assessment with APACHE II for predicting mortality risk in patients admitted to a medical intensive care unit. JAMA 260:1739–1742

    Article  PubMed  CAS  Google Scholar 

  71. Marks RJ, Simons RS, Blizzard RA, et al (1991) Predicting outcome in intensive therapy units — a comparison of APACHE II with subjective assessments. Intensive Care Med 17:159–163

    Article  PubMed  CAS  Google Scholar 

  72. Knaus WA, Wagner DP, Lynn J (1991) Short-term mortality predictions for critically ill hospitalized adults: science and ethics. Science 254:389–394

    Article  PubMed  CAS  Google Scholar 

  73. Lemeshow S, Klar J, Teres D (1995) Outcome prediction for individual intensive care patients: useful, misused, or abused ? Intensive Care Med 21:770–776

    Article  PubMed  CAS  Google Scholar 

  74. 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 

  75. Murray LS, Teasdale GM, Murray GD, et al (1993) Does prediction of outcome alter patient management?. Lancet 341:1487–1491

    Article  PubMed  CAS  Google Scholar 

  76. Knaus WA, Harreil FE, Lynn J, et al (1995) The SUPPORT prognostic model. Objective estimates for seriously ill hospitalized adults. Study to understand prognoses and preferences for outcomes and risks of treatments. Ann Intern Med 122:191–203

    PubMed  CAS  Google Scholar 

  77. Bellamy PE (1997) Why did prognosis presentation not work in the SUPPORT study? Curr Opin Crit Care 3:188–191

    Article  Google Scholar 

  78. Henning RJ, McClish D, Daly B, et al (1987) Clinical characteristics and resource utilization of ICU patients: implementation for organization of intensive care. Crit Care Med 15:264–269

    Article  PubMed  CAS  Google Scholar 

  79. Wagner DP, Knaus WA, Draper EA (1987) Identification of low-risk monitor admissions to medical-surgical ICUs. Chest 92:423–428

    Article  PubMed  CAS  Google Scholar 

  80. Wagner DP, Knaus WA, Draper EA, et al (1983) Identification of low-risk monitor patients within a medical-surgical ICU. Med Care 21:425–433

    Article  PubMed  CAS  Google Scholar 

  81. Zimmerman JE, Wagner DP, Knaus WA, Williams JF, Kolakowski D, Draper EA (1995) The use of risk predictors to identify candidates for intermediate care units. Implications for intensive care unit utilization. Chest 108:490–499

    Article  PubMed  CAS  Google Scholar 

  82. Zimmerman JE, Wagner DP, Sun X, Knaus WA, Draper EA (1996) Planning patient services for intermediate care units: insights based on care for intensive care unit low-risk monitor admissions. Crit Care Med 24:1626–1632

    Article  PubMed  CAS  Google Scholar 

  83. Strauss MJ, LoGerfo JP, Yeltatzie JA, Temkin N, Hudson LD (1986) Rationing of intensive care unit services. An everyday occurrence. JAMA 255:1143–1146

    Article  PubMed  CAS  Google Scholar 

  84. Civetta JM, Hudson-Civetta JA, Nelson LD (1990) Evaluation of APACHE II for cost containment and quality assurance. Ann Surg 212:266–276

    Article  PubMed  CAS  Google Scholar 

  85. Moreno R, Reis Miranda D (1998) Nursing staff in intensive care in Europe. The mismatch between planning and practice. Chest 113:752–758

    Article  PubMed  CAS  Google Scholar 

  86. Knaus WA, Wagner DP, Zimmerman JE, Draper EA (1993) Variations in mortality and length of stay in Intensive Care Units. Ann Intern Med 118:753–761

    PubMed  CAS  Google Scholar 

  87. Zimmerman JE, Shortell SM, Knaus WA, et al (1993) Value and cost of teaching hospitals: a prospective, multicenter, inception cohort study. Crit Care Med 21:1432–1442

    Article  PubMed  CAS  Google Scholar 

  88. Rapoport J, Teres D, Lemeshow S, Gehlbach S (1994) A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study. Crit Care Med 22:1385–1391

    Article  PubMed  CAS  Google Scholar 

  89. Teres D, Rapoport J (1991) Identifying patients with high risk of high cost. Chest 99:530–531

    Article  PubMed  CAS  Google Scholar 

  90. Esserman L, Belkora J, Lenert L (1995) Potentially ineffective care. A new outcome to assess the limits of critical care. JAMA 274:1544–1551

    Article  PubMed  CAS  Google Scholar 

  91. Rapoport J, Teres D, Lemeshow S (1998) Can futility be defined numerically? Crit Care Med 26:1781–1782.

    Article  PubMed  CAS  Google Scholar 

  92. Chang RW, Jacobs S, Lee B (1986) Use of APACHE II severity of disease classification to identify intensive-care-unit patients who would not benefit from total parenteral nutrition. Lancet i:1483–1486

    Google Scholar 

  93. Atkinson S, Bihari D, Smithies M, Daly K, Mason R, McColl I (1994) Identification of futility in intensive care. Lancet 344:1203–1206

    Article  PubMed  CAS  Google Scholar 

  94. Shaughnessy TE, Mickler TA (1995) Does acute physiology and chronic health evaluation (APACHE II) scoring predict need for prolonged support after coronary revascularization? Anaesth Analg 81:24–29

    CAS  Google Scholar 

  95. Cerra FB, Negro F, Abrams J (1990) APACHE II score does not predict multiple organ failure or mortality in post-operative surgical patients. Arch Surg 125:519–522

    Article  PubMed  CAS  Google Scholar 

  96. Rapoport J, Teres D, Lemeshow S, Avrunin JS, Haber R (1990) Explaining variability of cost using a severity of illness measure for ICU patients. Med Care 28:338–348

    Article  PubMed  CAS  Google Scholar 

  97. Oye RK, Bellamy PF (1991) Patterns of resource consumption in medical intensive care. Chest 99:695–689

    Article  Google Scholar 

  98. Glance LG, Osier T, SWhinozaki T (1998) Intensive care unit prognostic scoring systems to predict death: a cost-effectiveness analysis. Crit Care Med 26:1842–1849

    Article  PubMed  CAS  Google Scholar 

  99. Patel PA, Grant BJ (1999) Application of mortality prediction systems to individual intensive care units. Intensive Care Med 25:977–982

    Article  PubMed  CAS  Google Scholar 

  100. Knaus WA, Draper EA, Wagner DP, Zimmerman JE (1986) An evaluation of outcome from intensive care in major medical centers. Ann Intern Med 104:410–418

    PubMed  CAS  Google Scholar 

  101. Hosmer DW, Lemeshow S (1995) Confidence interval estimates of an index of quality performance based on logistic regression estimates. Stat Med 14:2161–2172

    Article  PubMed  CAS  Google Scholar 

  102. Knaus WA, Le Gall JR, Wagner DP, et al (1982) A comparison of intensive care in the U.S.A. and France. Lancet i:642–646

    Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  104. 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. Br Med J 307:977–981

    Article  CAS  Google Scholar 

  105. Rapoport J, Teres D, Barnett R, et al (1995) A comparison of intensive care unit utilization in Alberta and western Massachusetts. Crit Care Med 23:1336–1346

    Article  PubMed  CAS  Google Scholar 

  106. Wong DT, Crofts SL, Gomez M, McGuire GP, Byrick RJ (1995) Evaluation of predictive ability of APACHE II system and hospital outcome in Canadian intensive care unit patients. Crit Care Med 23:1177–1183

    Article  PubMed  CAS  Google Scholar 

  107. Moreno R, Reis Miranda D, Fidler V, Van Schilfgaarde R (1998) Evaluation of two outcome predictors on an independent database. Crit Care Med 26:50–61

    Article  PubMed  CAS  Google Scholar 

  108. Bastos PG, Sun X, Wagner DP, Knaus WA, Zimmerman JE, The Brazil APACHE III Study Group (1996) Application of the APACHE III prognostic system in Brazilian intensive care units: a prospective multicenter study. Intensive Care Med 22:564–570

    Article  PubMed  CAS  Google Scholar 

  109. Moreno R, Morais P (1997) Outcome prediction in intensive care: results of a prospective, multicentre, Portuguese study. Intensive Care Med 23:177–186

    Article  PubMed  CAS  Google Scholar 

  110. Le Gall JR, Loirat P, Nicolas F, et al (1983) Utilisation d’un indice de gravité dans huit services de réanimation multidisciplinaire. Presse Médicale 12:1757–1761

    CAS  Google Scholar 

  111. Zimmerman JE, Rousseau DM, Duffy J, et al (1994) Intensive care at two teaching hospitals: an organizational case study. Am J Crit Care 3:129–138

    PubMed  CAS  Google Scholar 

  112. Goldhill DR, Sumner A (1998) Outcome of intensive care patients in a group of British intensive care units. Crit Care Med 26:1337–1345

    Article  PubMed  CAS  Google Scholar 

  113. 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 

  114. Chisakuta AM, Alexander JP (1990) Audit in Intensive Care. The APACHE II classification of severity of disease. Ulster Med J 59:161–167

    PubMed  CAS  Google Scholar 

  115. Marsh HM, Krishan I,Naessens JM, et al (1990) Assessment of prediction of mortality by using the APACHE II scoring system in intensive care units. Mayo Clin Proc 65:1549–1557

    Article  PubMed  CAS  Google Scholar 

  116. Turner JS, Mudaliar YM, Chang RW, Morgan CJ (1991) Acute physiology and chronic health evaluation (APACHE II) scoring in a cardiothoracic intensive care unit. Crit Care Med 19:1266–1269

    PubMed  CAS  Google Scholar 

  117. Oh TE, Hutchinson R, Short S, Buckley T, Lin E, Leung D (1993) Verification of the acute physiology and chronic health evaluation scoring system in a Hong Kong intensive care unit. Crit Care Med 21:698–705

    Article  PubMed  CAS  Google Scholar 

  118. Parikh CR, Karnad DR (1999) Quality, cost, and outcome of intensive care in a public hospital in Bombay, India. Crit Care Med 27:1754–1759

    Article  PubMed  CAS  Google Scholar 

  119. Zimmerman JE, Shortell SM, Rousseau DM, et al (1993) Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective, multicenter study. Crit Care Med 21:1443–1451

    Article  PubMed  CAS  Google Scholar 

  120. Shortell SM, Zimmerman JE, Rousseau DM, et al (1994) The performance of intensive care units: does good management make a difference? Med Care 32:508–525

    Article  PubMed  CAS  Google Scholar 

  121. Reis Miranda D, Ryan DW, Schaufeli WB, Fidler V (1997) Organization and management of intensive care: a prospective study in 12 European countries. Springer-Verlag, Heidelberg.

    Google Scholar 

  122. Randolph AG, Guyatt GH, Carlet J, for the Evidence Based Medicine in Critical Care Group (1998) Understanding articles comparing outcomes among intensive care units to rate quality of care. Crit Care Med 26:773–781

    Article  PubMed  CAS  Google Scholar 

  123. Teres D, Lemeshow S (1993) Using severity measures to describe high performance intensive care units. Crit Care Clin 9:543–554

    PubMed  CAS  Google Scholar 

  124. Goldstein H, Spiegelhalter DJ (1996) League tables and their limitations: statistical issues in comparisons of institutional performance. J R Stat Soc A 159:385–443

    Article  Google Scholar 

  125. Castella X, Gilabert J, Torner F, Torres C (1991) Mortality prediction models in intensive care: Acute Physiology and Chronic Health Evaluation II and Mortality Prediction Model compared. Crit Care Med 19:191–197

    Article  PubMed  CAS  Google Scholar 

  126. 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 

  127. Nouira S, Belghith M, Elatrous S, et al (1998) Predictive value of severity scoring systems: comparison of four models in Tunisian adult intensive care units. Crit Care Med 26:852–859

    Article  PubMed  CAS  Google Scholar 

  128. Hadorn DC, Keeler EB, Rogers WH, Brook RH (1993) Assessing the performance of mortality prediction models. RAND/UCLA/Harvard Center for Health Care Financing Policy Research, Santa Monica

    Google Scholar 

  129. 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 

  130. Dybowski R, Weller P, Chang R (1996) Prediction of outcome in critically ill patients using artificial neural network, synthesised by genetic algorithm. Lancet 347:1146–1150

    Article  PubMed  CAS  Google Scholar 

  131. Wong LS, Young JD (1999) A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks. Anaesthesia 54:1048–1054

    Article  PubMed  CAS  Google Scholar 

  132. Green J, Wintfeld N (1995) Report cards on cardiac surgeons: assessing New York State’s approach. N Engl J Med 332:1229–1232

    Article  PubMed  CAS  Google Scholar 

  133. Lemeshow S, Teres D, Avrunin JS, Pastides H (1987) A comparison of methods to predict mortality of intensive care unit patients. Crit Care Med 15:715–722

    Article  PubMed  CAS  Google Scholar 

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  1. R. Moreno
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Editors and Affiliations

  1. Critical Care, University of Toronto, Canada

    William J. Sibbald MD, FRCPC, FCCHSE (Professor of Medicine, Physician-in-Chief) (Professor of Medicine, Physician-in-Chief)

  2. Department of Medicine, Sunnybrook and Women’s College, Health Sciences Centre, M4N 3M5, Toronto, Ontario, Canada

    William J. Sibbald MD, FRCPC, FCCHSE (Professor of Medicine, Physician-in-Chief) (Professor of Medicine, Physician-in-Chief)

  3. Department of Anesthesia and Intensive Care Medicine, University of Birmingham, Queen Elizabeth Hospital, B15 27H, Birmingham, UK

    Julian F. Bion FRCP, FRCA, MD (Reader and Regional Advisor in Intensive Care Medicine) (Reader and Regional Advisor in Intensive Care Medicine)

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© 2002 Springer Science+Business Media New York

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Moreno, R. (2002). Severity of Illness. In: Sibbald, W.J., Bion, J.F. (eds) Evaluating Critical Care. Update in Intensive Care Medicine, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56719-3_5

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  • DOI: https://doi.org/10.1007/978-3-642-56719-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42606-6

  • Online ISBN: 978-3-642-56719-3

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