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

QR Code

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

Bibliographic Details
Main Authors:	Ho, K., Knuiman, M., Finn, Judith, Webb, S.
Format:	Journal Article
Published:	Public Library of Science 2008
Online Access:	http://hdl.handle.net/20.500.11937/45249

Similar Items

Effect of length of stay in intensive care unit on hospital and long-term mortality of critically ill adult patients
by: Williams, Teresa, et al.
Published: (2010)

Determinants of long-term survival after intensive care
by: Williams, Teresa, et al.
Published: (2008)

Challenges and possible solutions for long-term follow-up of patients surviving critical illness
by: Williams, T., et al.
Published: (2011)

Effect of an episode of critical illness on subsequent hospitalisation: A linked data study
by: Williams, T., et al.
Published: (2010)

The effect of socioeconomic status on outcomes for seriously ill patients: A linked data cohort study
by: Ho, K., et al.
Published: (2008)

Changes in case-mix and outcomes of critically ill patients in an Australian tertiary intensive care unit
by: Williams, Teresa, et al.
Published: (2010)

Procalcitonin clearance for early prediction of survival in critically ill patients with severe sepsis
by: Mat Nor, Mohd Basri, et al.
Published: (2014)

The effect of evidence-based medication use on long-term survival in patients hospitalised for heart failure in Western Australia
by: Teng, T.H., et al.
Published: (2010)

Long-term survival among OHCA patients who survive to 30 days: Does initial arrest rhythm remain a prognostic determinant?
by: Majewski, David, et al.
Published: (2021)

Relative long-term survival in out-of-hospital cardiac arrest: Is it really improving?
by: Majewski, David, et al.
Published: (2020)

Predicting Long-Term Survival Without Major Disability for Infants Born Preterm
by: Bourke, J., et al.
Published: (2019)

Stories of survival: exploring long-term psychosocial well-being in childhood survivors of acute life threatening critical illness: a multiple-case study
by: Manning, Joseph
Published: (2015)

Long-term psychosocial impact reported by childhood critical illness survivors: a systematic review
by: Manning, Joseph C., et al.
Published: (2014)

Predicting long-term survival after coronary artery bypass graft surgery
by: Karim, M., et al.
Published: (2018)

Long-Term employee illness and frustration of the contract of employment
by: Guthrie, Rob, et al.
Published: (2007)

Variation in risk and mortality of acute kidney injury in critically ill patients: A multicenter study
by: Srisawat, N., et al.
Published: (2015)

Using patient admission characteristics alone to predict mortality of critically ill patients: A comparison of 3 prognostic scores
by: Ho, K., et al.
Published: (2016)

Estimation of plasma insulin and endogenous insulin secretion in critically ill patients using ICING model
by: Jamaludin, Ummu Kulthum, et al.
Published: (2016)

Estimation of Plasma Insulin and Endogenous Insulin Secretion in Critically Ill Patients Using ICING Model
by: Ummu Kulthum, Jamaludin, et al.
Published: (2017)

Mortality prediction in critically ill patients using machine learning score
by: Dzaharudin, Fatimah, et al.
Published: (2020)

Mortality prediction in critically ill patients using machine learning score
by: Fatimah, Dzaharudin, et al.
Published: (2020)

The ability of early warning scores (EWS) to detect critical illness in the prehospital setting: A systematic review
by: Williams, Teresa, et al.
Published: (2016)

Validity of predictive equations for estimation of resting energy expenditure among mechanically ventilated critically ill patients: Preliminary findings
by: Tah, Pei Chien, et al.
Published: (2017)

Eccentric exercise and the critically ill patient
by: Mitchell, W. Kyle, et al.
Published: (2017)

Interleukin-6-to-albumin ratio for mortality prediction in critically ill elderly patients
by: Yang, Lim Kai
Published: (2024)

Model of nurses' perception of the critically ill patients' transition experience
by: Mohamed Ludin, Malaysia
Published: (2019)

Debriefing to improve outcomes from critical illness: a systematic review and meta-analysis
by: Couper, K., et al.
Published: (2013)

Estimates of glomerular filtration rate in the critically ill with sepsis
by: Md Ralib, Azrina, et al.
Published: (2017)

Validating a lower urine output criteria in predicting death in critically ill patients
by: Md Ralib, Azrina, et al.
Published: (2017)

Factors predictive of the need for renal replacement therapy in critically ill patients with rhabdomyolysis and their outcome
by: Wei, Tan Chee
Published: (2020)

Nutritional management of the critically ill obese patient
by: Mat Nor, Mohd Basri, et al.
Published: (2018)

Acute kidney injury and the critically ill patient
by: Davies, Hugh, et al.
Published: (2012)

Nutritional management of the critically ill obese patient
by: Mat Nor, Mohd Basri, et al.
Published: (2018)

Estimating dead space ventilation: a computational modelling approach towards evaluation of clinical estimates of dead space fraction in critically ill patients
by: Naeem, Usra
Published: (2018)

Long-term survival of elderly patients undergoing percutaneous coronary intervention for myocardial infarction complicated by cardiogenic shock
by: Lim, H., et al.
Published: (2015)

Estimating a logistic Weibull mixture models with long-term survivors.
by: Abu Bakar, Mohd Rizam, et al.
Published: (2006)

025 Estimates of glomerular filtration rate in the critically ill with sepsis
by: Azrina, M. Ralib, et al.
Published: (2017)

Transition in the critically ill patients: Malaysian nurses’ perspective
by: Mohamed Ludin, Salizar, et al.
Published: (2010)

Estimation of plasma insulin and endogenous insulin secretion in critically ill patients using intensive control insulin-nutrition-glucose model
by: Jamaludin, Ummu Kulthum, et al.
Published: (2017)

Long-term survival following the development of heart failure in an elderly hypertensive population.
by: Sahle, B., et al.
Published: (2017)