Literature DB >> 18787441

Outcome prediction in critical care: the ICNARC model.

David A Harrison1, Kathryn M Rowan.   

Abstract

PURPOSE OF REVIEW: To describe the background to, rationale for, and structure and performance of the Intensive Care National Audit & Research Centre risk prediction model. RECENT
FINDINGS: The Intensive Care National Audit & Research Centre model was published in 2007 as a new risk prediction model, predicting risk of death before ultimate discharge from acute hospital for all admissions to adult, general critical care units in the UK. It was developed using a high-quality clinical database of over 200,000 admissions to 163 critical care units and prospectively validated in over 30,000 admissions to 20 different units. The Intensive Care National Audit & Research Centre model was designed to address limitations of preexisting models, particularly exclusion of certain patient groups, and varying effects of physiological derangement in different underlying conditions.
SUMMARY: The Intensive Care National Audit & Research Centre model performs well in comparison with preexisting models when evaluated in independent validation data from UK critical care units. The use of interactions between the physiology score and diagnostic category produces better fit within individual diagnostic groups. The elimination of model exclusion criteria, for example age less than 16 years, means that the model compares the observed and expected outcomes for all patients admitted to a critical care unit providing a fairer method for comparative audit.

Entities:  

Mesh:

Year:  2008        PMID: 18787441     DOI: 10.1097/MCC.0b013e328310165a

Source DB:  PubMed          Journal:  Curr Opin Crit Care        ISSN: 1070-5295            Impact factor:   3.687


  6 in total

1.  Is the volume of mechanically ventilated admissions to UK critical care units associated with improved outcomes?

Authors:  Jason Shahin; D A Harrison; K M Rowan
Journal:  Intensive Care Med       Date:  2014-02-07       Impact factor: 17.440

2.  The ideal time interval for critical care severity-of-illness assessment.

Authors:  Murray M Pollack; J Michael Dean; Jerry Butler; Richard Holubkov; Allan Doctor; Kathleen L Meert; Christopher J L Newth; Robert A Berg; Frank Moler; Heidi Dalton; David L Wessel; John Berger; Rick E Harrison; Joseph A Carcillo; Thomas P Shanley; Carol E Nicholson
Journal:  Pediatr Crit Care Med       Date:  2013-06       Impact factor: 3.624

3.  Arterial hyperoxia and in-hospital mortality after resuscitation from cardiac arrest.

Authors:  Rinaldo Bellomo; Michael Bailey; Glenn M Eastwood; Alistair Nichol; David Pilcher; Graeme K Hart; Michael C Reade; Moritoki Egi; D James Cooper
Journal:  Crit Care       Date:  2011-03-08       Impact factor: 9.097

4.  External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland.

Authors:  David A Harrison; Nazir I Lone; Catriona Haddow; Moranne MacGillivray; Angela Khan; Brian Cook; Kathryn M Rowan
Journal:  BMC Anesthesiol       Date:  2014-12-15       Impact factor: 2.217

5.  Age influences the predictive value of Acute Physiology and Chronic Health Evaluation II and Intensive Care National Audit and Research Centre scoring models in patients admitted to Intensive Care Units after in-hospital cardiac arrest.

Authors:  D N S Senaratne; T Veenith
Journal:  Indian J Crit Care Med       Date:  2015-03

6.  Why should we not use APACHE II for performance measurement and benchmarking?

Authors:  Marcio Soares; Dave A Dongelmans
Journal:  Rev Bras Ter Intensiva       Date:  2017-09-04
  6 in total

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