The impact of frailty on death, discharge destination and modelling accuracy in patients receiving organ support on the intensive care unit

Author:

Georgiou Andy1ORCID,Turner Nicholas2,Serrano Ruiz Alfredo1,Wadman Harry1ORCID,Saunsbury Emma1,Laver Stephen1,Maybin Rob1

Affiliation:

1. Intensive Care Unit, Royal United Hospital Bath NHS Foundation Trust, Bath, UK

2. Bristol Randomised Trials Collaboration, University of Bristol, Bristol, UK

Abstract

Background This study aims to identify any effect of frailty in altering the risk of death or poor outcome already associated with receipt of organ support on ICU. It also aims to assess the performance of mortality prediction models in frail patients. Methods All admissions to a single ICU over 1-year were prospectively allocated a Clinical Frailty Score (CFS). Logistic regression analysis was used to investigate the effect of frailty on death or poor outcome (death/discharge to a medical facility). Logistic regression analysis, area under the Receiver Operator Curve (AUROC) and Brier scores were used to investigate the ability of two mortality prediction models, ICNARC and APACHE II, to predict mortality in frail patients. Results Of 849 patients, 700 (82%) patients were not frail, and 149 (18%) were frail. Frailty was associated with a stepwise increase in the odds of death or poor outcome (OR for each point rise of CFS = 1.23 ([1.03–1.47]; p = .024) and 1.32 ([1.17–1.48]; p = <.001) respectively). Renal support conferred the greatest odds of death and poor outcome, followed by respiratory support, then cardiovascular support (which increased the odds of death but not poor outcome). Frailty did not modify the odds already associated with organ support. The mortality prediction models were not modified by frailty (AUROC p = .220 and .437 respectively). Inclusion of frailty into both models improved their accuracy. Conclusions Frailty was associated with increased odds of death and poor outcome, but did not modify the risk already associated with organ support. Inclusion of frailty improved mortality prediction models.

Funder

National Institute of Academic Anaesthesia

Publisher

SAGE Publications

Subject

Critical Care and Intensive Care Medicine,Critical Care Nursing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3