Literature DB >> 17900487

Severity of illness and organ failure assessment in adult intensive care units.

Bekele Afessa1, Ognjen Gajic, Mark T Keegan.   

Abstract

The critical care community has been using severity and organ failure assessment tools for over 2 decades. The major adult severity assessment models are Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score, and Mortality Probability Model. All three recent versions of these models perform well in predicting hospital mortality. Sequential Organ Failure Assessment score is the most used tool for assessment of multiple organ failure. These tools have been used extensively in clinical research involving critically ill patients and for benchmarking and the measurement of performance improvement. Their roles as clinical decision support tools at the bedside await future studies because of their unknown or poor performance at the individual patient level.

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Year:  2007        PMID: 17900487     DOI: 10.1016/j.ccc.2007.05.004

Source DB:  PubMed          Journal:  Crit Care Clin        ISSN: 0749-0704            Impact factor:   3.598


  40 in total

1.  Comparison of APACHE III, APACHE IV, SAPS 3, and MPM0III and influence of resuscitation status on model performance.

Authors:  Mark T Keegan; Ognjen Gajic; Bekele Afessa
Journal:  Chest       Date:  2012-10       Impact factor: 9.410

Review 2.  The emerging field of quantitative blood metabolomics for biomarker discovery in critical illnesses.

Authors:  Natalie J Serkova; Theodore J Standiford; Kathleen A Stringer
Journal:  Am J Respir Crit Care Med       Date:  2011-06-16       Impact factor: 21.405

3.  Red cell distribution width: the crystal ball in the hands of intensivists?

Authors:  Xiaobo Yang; Bin Du
Journal:  J Thorac Dis       Date:  2014-02       Impact factor: 2.895

4.  Utility of the Richmond Agitation-Sedation Scale in evaluation of acute neurologic dysfunction in the intensive care unit.

Authors:  Vrinda Trivedi; Vivek N Iyer
Journal:  J Thorac Dis       Date:  2016-05       Impact factor: 2.895

5.  Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

Authors:  Xuejian Li; Youqing Wang
Journal:  J Clin Monit Comput       Date:  2015-09-21       Impact factor: 2.502

6.  Validation of the APACHE IV model and its comparison with the APACHE II, SAPS 3, and Korean SAPS 3 models for the prediction of hospital mortality in a Korean surgical intensive care unit.

Authors:  Hannah Lee; Yoon-Jung Shon; Hyerim Kim; Hyesun Paik; Hee-Pyoung Park
Journal:  Korean J Anesthesiol       Date:  2014-08-26

7.  The impact of delirium on the prediction of in-hospital mortality in intensive care patients.

Authors:  Mark van den Boogaard; Sanne Ae Peters; Johannes G van der Hoeven; Pieter C Dagnelie; Pieter Leffers; Peter Pickkers; Lisette Schoonhoven
Journal:  Crit Care       Date:  2010-08-03       Impact factor: 9.097

8.  An in-hospital mortality equation for mechanically ventilated patients in intensive care units.

Authors:  Takeshi Umegaki; Masaji Nishimura; Kimitaka Tajimi; Kiyohide Fushimi; Hiroshi Ikai; Yuichi Imanaka
Journal:  J Anesth       Date:  2013-03-09       Impact factor: 2.078

9.  Plasma CC16 levels are associated with development of ALI/ARDS in patients with ventilator-associated pneumonia: a retrospective observational study.

Authors:  Rogier M Determann; Julian L Millo; Sam Waddy; Rene Lutter; Chris S Garrard; Marcus J Schultz
Journal:  BMC Pulm Med       Date:  2009-12-03       Impact factor: 3.317

10.  APACHE III outcome prediction in patients admitted to the intensive care unit after liver transplantation: a retrospective cohort study.

Authors:  Mark T Keegan; Bhargavi Gali; James Y Findlay; Julie K Heimbach; David J Plevak; Bekele Afessa
Journal:  BMC Surg       Date:  2009-07-29       Impact factor: 2.102

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