Research progress of prediction model for prognosis of critically ill elderly patients
Received:January 17, 2017  Revised:February 26, 2017
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DOI:10.11915/j.issn.1671-5403.2017.07.127
Key words:frailty syndrome  frailty index  clinical frailty scale  prediction model
Author NameAffiliationE-mail
DONG Jia-Hui Department of Geriatric Intensive Care Medicine, Guangdong Provincial Key Laboratory of Geriatric Infection and Organ Function Support Guangzhou Key Laboratory of Geriatric Infection and Organ Function Support, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou 510010, China  
SUN Jie Department of Geriatric Intensive Care Medicine, Guangdong Provincial Key Laboratory of Geriatric Infection and Organ Function Support Guangzhou Key Laboratory of Geriatric Infection and Organ Function Support, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou 510010, China  
ZENG An School of Computers, Guangdong University of Technology, Guangzhou 510000, China  
GUO Zhen-Hui Department of Geriatric Intensive Care Medicine, Guangdong Provincial Key Laboratory of Geriatric Infection and Organ Function Support Guangzhou Key Laboratory of Geriatric Infection and Organ Function Support, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou 510010, China micugzh@126.com 
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Abstract:
      Although Acute Physiology And Chronic Health Evaluation (APACHE) and Simplified Acute Physiology Score (SAPS) show good predictive effect on critically ill patients, they may have predictive data migration or poor population calibration when being used in the elderly critically ill patients. However, the established special prediction models for elderly are not of enough accuracy and reliability. So, frailty syndrome has become the key point in geriatric comprehensive assessment. Current studies showed that frailty index (FI) and clinical frailty scale (CFS) can be used as the objective models to assess frailty syndrome, and have become hotspot in the studies on predictive assessment for critically ill elderly. This article reviewed the development process and research progress of these predictive models, with a view of clinicians for better application.
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