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Published (Version of Record)CC BY V4.0, Open Access
Journal article
Estimating long-term survival of critically ill patients: The PREDICT model
PLoS ONE, Vol.3(9), e3226
2008
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, co-morbidities, 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.
Details
- Title
- Estimating long-term survival of critically ill patients: The PREDICT model
- Authors/Creators
- J.A. Gold (Author/Creator)K.M. Ho (Author/Creator) - Royal Perth HospitalM.W. Knuiman (Author/Creator) - The University of Western AustraliaJ. Finn (Author/Creator) - Faculty (United Kingdom)S.A.R. Webb (Author/Creator) - School of Medicine and Pharmacology
- Publication Details
- PLoS ONE, Vol.3(9), e3226
- Publisher
- Public Library of Science
- Identifiers
- 991005543830307891
- Copyright
- © 2008 Ho et al
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 1 Clinical & Life Sciences
- 1.154 Assisted Ventilation
- 1.154.1088 Intensive Care
- Web Of Science research areas
- Critical Care Medicine
- ESI research areas
- Clinical Medicine