Literature DB >> 31767191

Comparative influence of Acute Illness Severity and comorbidity on mortality.

Richard Conway1, Declan Byrne2, Deirdre O'Riordan2, Bernard Silke2.   

Abstract

BACKGROUND: The extent to which illness severity and comorbidity determine the outcome of an emergency medical admission is uncertain. We aim to quantitate the relative effect of these factors on mortality.
METHODS: We evaluated all emergency medical admission to our institution between 2002 and 2018. We derived an Acute Illness Severity Score (AISS) and Comorbidity Score from admission data and International Classification of Diseases codings. We employed a multivariable logistic regression model to relate both to 30-day in-hospital mortality.
RESULTS: There were 113,807 admissions in 58,126 patients. Both AISS, Odds Ratio (OR) 4.4 (95%CI 3.5, 5.5), and Comorbidity Score, OR 1.91 (95%CI 1.67, 2.18), independently predicted 30-day in-hospital mortality. The two highest AISS risk groups encompassed 46.5% of admissions with predicted mortality of 5.9% (95%CI 5.7%, 6.1%) and 14.4% (95%CI 13.9%, 14.8%) respectively. Comorbidity Score >=10 occurred in 17.9% of admissions with a predicted mortality of 13.3%. AISS and Comorbidity Score interacted to adversely influence mortality; the threshold effect for Comorbidity Score was reduced at high levels of AISS.
CONCLUSION: High AISS and Comorbidity Scores were predictive of 30-day in-hospital mortality and relatively common in emergency medical admissions. There is a strong interaction between the two scores.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  AISS comorbidity; Demographics; Interactions; Mortality outcomes

Year:  2019        PMID: 31767191     DOI: 10.1016/j.ejim.2019.11.014

Source DB:  PubMed          Journal:  Eur J Intern Med        ISSN: 0953-6205            Impact factor:   4.487


  2 in total

1.  Regional Disparity of Medical Resources and Its Effect on Mortality Rates in China.

Authors:  Kuang-Cheng Chai; Ying-Bin Zhang; Ke-Chiun Chang
Journal:  Front Public Health       Date:  2020-02-04

Review 2.  Machine learning techniques for mortality prediction in emergency departments: a systematic review.

Authors:  Amin Naemi; Thomas Schmidt; Marjan Mansourvar; Mohammad Naghavi-Behzad; Ali Ebrahimi; Uffe Kock Wiil
Journal:  BMJ Open       Date:  2021-11-02       Impact factor: 2.692

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.