Critical care outcome prediction equation (COPE) for adult intensive care

Critical Care and Resuscitation

Volumn 10, Issue 1, 2008, Pages 35-41

  Duke, Graeme J ^a   Santamaria, John ^b   Shann, Frank ^c   Stow, Peter ^d   Pilcher, David ^e   Ernest, David ^f   George, Carol ^g  

^a NORTHERN HOSPITAL   (Australia)

^b ST VINCENT S HOSPITAL   (Australia)

^c ROYAL CHILDREN'S HOSPITAL   (Australia)

^d GEELONG HOSPITAL   (Australia)

^e ALFRED HOSPITAL   (Australia)

^f BOX HILL HOSPITAL   (Australia)

^g Australian and New Zealand Intensive Care Sociey Adult Patient Database   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84861535614     PISSN: 14412772     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. Knaus WA, Draper EA, Zimmerman JE, et al. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991; 100: 1916-36.
2. Australian and New Zealand Intensive Care Society Adult Patient Database [website]. Available at: http://www.anzics.com.au (accessed Nov 2007).
3. Australian Council on Healthcare Standards. Intensive care indicators, clinical indicator users’ manual version 3 for use in 2007. Available at: http://www.achs.org.au (accessed Nov 2007).
4. Moreno RP, Metnitz PGH, Almeida E, et al. SAPS 3. From evaluation of the patient to evaluation of the intensive care unit. Intensive Care Med 2005; 31: 1345-55.
5. Lemeshow S, Teres D, Klar J, et al. Mortality probability models (MPM II) based on an international cohort of intensive care patients. JAMA 1993; 270: 2478-86.
6. Duke G, Santamaria J, Shann F, Stow P. Outcome-based clinical indicators for intensive care medicine. Anaesth Intensive Care 2005; 33: 303-10.
7. Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patient. Crit Care Med 2006; 34: 1297-310.
8. Speigelhalter D, Grigg O, Kinsman R, Treasure T. Risk-adjusted sequential probability ratio tests: applications to Bristol, Shipman, and adult cardiac surgery. Int J Qual Health Care 2003; 15: 7-13.
9. Victorian Admitted Episodes Database (VAED) data definitions. Available at: http://www.health.vic.gov.au/hosdata/datafields.htm (accessed Nov 2007).
10. Managing patient safety in public hospitals. Victorian Auditor General report, March 2005. Availab le at: http:// www.audit.vic.gov.au/reports_par/agp10206.html (accessed Nov 2007).
11. Aylin P, Bottle A, Majeed A. Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models. BMJ 2007; 334: 1044-51.
12. Scott IA, Ward M. Public reporting of hospital outcomes based on administrative data: risks and opportunities. Med J Aust 2006; 184: 571–5.
13. International statistical classification of diseases. 10th revision. Australian modification, 4th ed. Sydney: National Centre for Classification in Health, 2004.
14. Harrison DA, Brady AR, Parry GJ, et al. 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 2006; 34: 1378-88.
15. Cook DA. Methods to assess performance of models estimating risk of death in intensive care patients: a review. Anaesth Intensive Care 2006; 34: 164-75.
16. Hosmer DW, Lemeshow S. Applied logistic regression. 2nd ed. New York: John Wiley, 2000.
17. Bertolini G, D’Amico R, Nardi D, et al. One model, several results: the paradox of the Hosmer–Lemeshow goodness-of-fit test for the logistic regression model. J Epidemiol Biostat 2000; 5: 251-3.