Estimating long-term survival of critically ill patients: the PREDICT model

Ho, Kwok M., Knuiman, Matthew, Finn, Judith and Webb, Steven A. (2008) Estimating long-term survival of critically ill patients: the PREDICT model. PLoS One, 3 9: e3226.1-e3226.8. doi:10.1371/journal.pone.0003226


Author Ho, Kwok M.
Knuiman, Matthew
Finn, Judith
Webb, Steven A.
Title Estimating long-term survival of critically ill patients: the PREDICT model
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2008-09-17
Sub-type Article (original research)
DOI 10.1371/journal.pone.0003226
Open Access Status DOI
Volume 3
Issue 9
Start page e3226.1
End page e3226.8
Total pages 8
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Language eng
Formatted abstract
Background: Long-term survival outcome of critically ill patients is important in assessing effectiveness of new treatments and making treatment decisions. We developed a prognostic model for estimation of long-term survival of critically ill patients.

Methodology and Principal Findings: This was a retrospective linked data cohort study involving 11,930 critically ill patients who survived more than 5 days in a university teaching hospital in Western Australia. Older age, male gender, comorbidities, severe acute illness as measured by Acute Physiology and Chronic Health Evaluation II predicted mortality, and more days of vasopressor or inotropic support, mechanical ventilation, and hemofiltration within the first 5 days of intensive care unit admission were associated with a worse long-term survival up to 15 years after the onset of critical illness. Among these seven pre-selected predictors, age (explained 50% of the variability of the model, hazard ratio [HR] between 80 and 60 years old = 1.95) and co-morbidity (explained 27% of the variability, HR between Charlson co-morbidity index 5 and 0 = 2.15) were the most important determinants. A nomogram based on the pre-selected predictors is provided to allow estimation of the median survival time and also the 1-year, 3-year, 5-year, 10-year, and 15-year survival probabilities for a patient. The discrimination (adjusted c-index = 0.757, 95% confidence interval 0.745-0.769) and calibration of this prognostic model were acceptable.

Significance: Age, gender, co-morbidities, severity of acute illness, and the intensity and duration of intensive care therapy can be used to estimate long-term survival of critically ill patients. Age and co-morbidity are the most important determinants of long-term prognosis of critically ill patients.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Nursing, Midwifery and Social Work Publications
 
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Created: Thu, 31 Jul 2014, 14:18:31 EST by Vicki Percival on behalf of School of Nursing, Midwifery and Social Work