Literature DB >> 26482428

Evaluation of illness severity scoring systems and risk prediction in vascular intensive care admissions.

M Dover1, Wael Tawfick2, Niamh Hynes3, Sherif Sultan4.   

Abstract

INTRODUCTION: This study examines the predictive value of intensive care unit (ICU) scoring systems in a vascular ICU population.
METHODS: From April 2005 to September 2011, we examined 363 consecutive ICU admissions. Simplified Acute Physiology Score II (SAPS II), Acute Physiology and Chronic Health Evaluation II (APACHE II), APACHE IV, Multiple Organ Dysfunction Score (MODS), organ dysfunctions and/or infection (ODIN), mortality prediction model (MPM) and physiologic and operative severity score for the enumeration of mortality and morbidity (POSSUM) were calculated. The Glasgow Aneurysm Score (GAS) was calculated for patients with aneurysm-related admissions.
RESULTS: Overall mortality for complex vascular intervention was 11.6%. At admission, the areas under the receiver operating characteristic curve (AUCs) was 0.884 for SAPS II, 0.894 for APACHE II, 0.895 for APACHE IV, 0.902 for MODS, 0.891 for ODIN and 0.903 for MPM. At 24 h, model discrimination was best for POSSUM (AUC = 0.906) and MPM (AUC = 0.912).
CONCLUSION: The good discrimination of these scoring systems indicates their value as an adjunct to clinical assessment but should not be used on an individual basis as a clinical decision-making tool.
© The Author(s) 2015.

Entities:  

Keywords:  Illness severity score; clinical audit; complex major vascular intervention; intensive care

Mesh:

Year:  2015        PMID: 26482428     DOI: 10.1177/1708538115604089

Source DB:  PubMed          Journal:  Vascular        ISSN: 1708-5381            Impact factor:   1.285


  2 in total

1.  Low interferon-gamma release in response to phytohemagglutinin predicts the high severity of diseases.

Authors:  Xing He; Li-Ying Liu; Xiao-Kun Ji; Ya-Bin Xian; Yong-Jun Yan; Hui-Juan Xu; Li Sha; Chun-Li Pu; Jun-Yan Zhou; Chun-Yan Yuan; Mei Yang; Song-Guo Zheng
Journal:  Medicine (Baltimore)       Date:  2019-05       Impact factor: 1.817

2.  To develop a regional ICU mortality prediction model during the first 24 h of ICU admission utilizing MODS and NEMS with six other independent variables from the Critical Care Information System (CCIS) Ontario, Canada.

Authors:  Raymond Kao; Fran Priestap; Allan Donner
Journal:  J Intensive Care       Date:  2016-02-29
  2 in total

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