Skip to main content
SpringerLink
Log in

Application of the APACHE III prognostic system in Brazilian intensive care units: A prospective multicenter study

  • Original
  • Published:
Intensive Care Medicine Aims and scope Submit manuscript

Abstract

Objective

To compare patients and their outcomes at ten Brazilian intensive care units (ICUs) with those reported from the United States.

Design

Prospective multicenter inception cohort study.

Setting

Ten Brazilian adult medical-surgical ICUs.

Patients

1734 consecutive adult ICU admissions.

Measurements and results

We used demographic, clinical and physiologic information and the APACHE III prognostic system to predict risk of hospital death for 1734 ICU admissions. We then divided the observed by the predicted hospital death rate to calculate standardized mortality ratios (SMRs) for patient groups and each ICU. Hospital mortality for Brazilian patients (34%) was double that found in the United States (17%,p<0.01). Discrimination of survivors from non-survivors using APACHE III was good (area under a receiver operating characteristic curve=0.82), but the predicted risk of death was significantly (p<0.0001) lower than observed outcome (SMR=1.67). Three of the ten Brazilian ICUs, however, had SMRs of 1.01 to 1.1 and no significant difference between observed and predicted outcomes; the remaining seven ICUs had significatly higher SMRs, ranging from 1.50 to 2.30.

Conclusion

The APACHE III prognostic system was a good discriminator of hospital mortality for ICU admissions at 10 Brazilian ICUs. There was substantial and significant variation, however, in SMRs among the Brazilian ICUs, which suggests that further evaluations of international differences in intensive care using a common risk assessment system should be performed and factors associated with variations in risk-adjusted mortality scrutinized.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Banta HD (1986) Medical technology and developing countries: the case of Brazil. Int J Health Serv 16: 363–373

    Google Scholar 

  2. Perry S, Marx ES (1992) What technologies for health care in developing countries? World Health Forum 13: 356–361

    Google Scholar 

  3. Jenett B (1984) Inappropriate use of intensive care. BMJ 289: 1709–1711

    Google Scholar 

  4. Chernow B (1993) The practice of critical care-describing who we are, evaluating what we do, and computing the cost. Crit Care Med 21: 1413–1415

    Google Scholar 

  5. Knaus WA, Douglas DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Serio CA, Murphy DJ, Lotring T, Damiano A, Harrell FE, (1991) The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults. Chest 100: 1619–1636

    Google Scholar 

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

    Google Scholar 

  7. Gemke RJBJ, Bonsel GJ, van Vught AJ (1994) Effectiveness and efficiency of a Dutch pediatric intensive care unit: validity and application of the pediatric risk of mortality score. Crit Care Med 22: 1477–1484

    Google Scholar 

  8. LeGall 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

    Google Scholar 

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

    Google Scholar 

  10. Zimmerman JE, Wagner DP, Knaus WA, Willaims JF, Kolakowski D, Draper EA (1995) The use of risk predictions to identify candidates for intermediate care units. Chest 108: 490–499

    Google Scholar 

  11. Knaus WA, Harrell FE, Fisher CJ, Wagner DP, Opal SM, Sadoff JC, Draper EA, Walawander CA, Conboy K, Grasela TH (1993) The clinical evaluation of new drugs for sepsis: a prospective study design based on survival analysis. JAMA 270: 1233–1241

    Google Scholar 

  12. Knaus WA, Draper EA, Wagner DP, Zimmerman JE (1985) APACHE II: a severity of disease classification system. Crit Care Med 13: 818–828

    Google Scholar 

  13. Dragsted L, Jorgensen J, Jensen NH, Bonsing E, Jacobsen E, Knaus WA, Qvist J (1989) Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias. Crit Care Med 17: 418–422

    Google Scholar 

  14. Zimmerman JE, Knaus WA, Judson JA, Havill JH, Trubuhovich RV, Draper EA, Wagner DP (1988) Patient selection for intensive care: a comparison of New Zealand and United States hospitals. Crit Care Med 16: 318–326

    Google Scholar 

  15. Jacobs S, Chang RWS, Lee B, Lee B (1988) Audit of intensive care: a 30 month experience using the APACHE II severity of disease classification system. Intensive Care Med 14: 567–574

    Google Scholar 

  16. 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

    Google Scholar 

  17. Rowan KM, Kerr JH, Major E, McPherson, Short A, Vessey MP (1994) Intensive Care Society's acute physiology and chronic health evaluation (APACHE II) study in Britain and Ireland: a prospective, multicenter, cohort study comparing two methods for predicting outcome for adult intensive care patients. Crit Care Med 22: 1392–1401

    Google Scholar 

  18. Milani R, Rocha AS (1989) Prognostic accuracy and efficacy of treatment at intensive care units evaluated by the APACHE II system. Rev Hosp Clin Fac Med Sao Paulo 44: 149–152

    Google Scholar 

  19. Turner JS, Potgieter PD, Linton DM (1989) Systems of scoring severity of illness in intensive care. S Afr Med J 76: 17–20

    Google Scholar 

  20. Joshua N, Jena GP, Mletelwa NV (1989) Multidisciplinary intensive care unit at Cecilia Makiwane Hospital, Mdantsane, Ciskei. S Afr Med J 75: 286–289

    Google Scholar 

  21. Dougnac A (1989) Severity evaluation system: APACHE II, SAPS: national experience in a unit of medical intensive therapy. Rev Med Chil 117: 1357–1362

    Google Scholar 

  22. Hernandez JFR, Brito AE, Galende MLQ, Prendes PN, Pena MS, Correa NP (1990) Dies años de atencion al paciente critico. I. Comparacion de 2 grupos de pacientes ingresados al principio y final de la última década. Rev Bras Terap Intensiva 2: 7–9

    Google Scholar 

  23. Hernandez JFR, Brito AE, Galende MLQ, Prendes PN, Pena MS, Correa NP (1990) Dies años de atencion al paciente critico. II. Comparacion de 2 grupos de pacientes ingresados al principio y final de la última década. Rev Bras Terap Intensiva 2: 10–12

    Google Scholar 

  24. Teoh GS (1991) APACHE II: preliminary report on 100 intensive care unit cases in university hospital, Kuala Lumpur. Med J Malaysia 46: 72–81

    Google Scholar 

  25. Sirio CA, Tajimi K, Tase C, Knaus WA, Wagner DP, Hirasawa H, Sakanishi N, Katsuya H, Taenaka N (1992) An initial comparison of intensive care in Japan and United States. Crit Care Med 20: 1207–1215

    Google Scholar 

  26. 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

    Google Scholar 

  27. 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

    Google Scholar 

  28. Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143: 29–36

    Google Scholar 

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

    Google Scholar 

  30. Hanley JA, McNeil BJ (1983) A method of comparing areas under receiver operator characteristics curves derived from the same cases. Radiology 148: 839–843

    Google Scholar 

  31. 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

    Google Scholar 

  32. Castella X, Artigas A, Bion J, Kari A, The European/North America Severity Study Group (1995) A comparison of severity of illness scoring systems for intensive care unit patients: results of a multicenter, multinational study. Crit Care Med 23: 1327–1335

    Google Scholar 

  33. Kruse JA, Carlson RW (1993) Severity of illness scoring: east meets west. Crit Care Med 21: 647–649

    Google Scholar 

  34. Haines A (1993) Health care in Brazil. BMJ 306: 503–506

    Google Scholar 

  35. Park RE, Brook RH, Kosecoff J, Keesey J, Rubenstein L, Keeler E (1990) Explaining variations in hospital death rates: randomness, severity of illness, quality of care. JAMA 264: 484–490

    Google Scholar 

Download references

Author information

Author notes

  1. P. G. Bastos, X. Sun, D. P. Wagner, W. A. Knaus & J. E. Zimmerman

    Present address: ICU Research Unit, The George Washington University Medical Center, 901 23rd Street, N.W., 20037, Washington, DC, USA

Authors and Affiliations

  1. Hospital de Ipanema, 22411, Rio de Janeiro, Brazil

    P. G. Bastos, X. Sun, D. P. Wagner, W. A. Knaus & J. E. Zimmerman

Authors
  1. P. G. Bastos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. X. Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D. P. Wagner
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. W. A. Knaus
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. E. Zimmerman
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Supported by the Agency for Health Care Policy and Research (HSO7137); The John A. Hartford Foundation (87267); The Department of Anesthesiology, The George Washington University Medical Center, The National Council of Scientific and Technology Development (CNPq), Brazil (No. 202321/98.4); and APACHE Medical Systems Inc

A complete list of study hospitals and participants appears at the end of this article

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bastos, P.G., Sun, X., Wagner, D.P. et al. Application of the APACHE III prognostic system in Brazilian intensive care units: A prospective multicenter study. Intensive Care Med 22, 564–570 (1996). https://doi.org/10.1007/BF01708097

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01708097

Key words

Search

Navigation