Literature DB >> 25435482

Using what you get: dynamic physiologic signatures of critical illness.

Andre L Holder1, Gilles Clermont2.   

Abstract

The development and resolution of cardiopulmonary instability take time to become clinically apparent, and the treatments provided take time to have an impact. The characterization of dynamic changes in hemodynamic and metabolic variables is implicit in physiologic signatures. When primary variables are collected with high enough frequency to derive new variables, this data hierarchy can be used to develop physiologic signatures. The creation of physiologic signatures requires no new information; additional knowledge is extracted from data that already exist. It is possible to create physiologic signatures for each stage in the process of clinical decompensation and recovery to improve outcomes.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cardiopulmonary instability; Data hierarchy; Fused parameter; Machine learning; Physiologic signature

Mesh:

Year:  2015        PMID: 25435482      PMCID: PMC4476532          DOI: 10.1016/j.ccc.2014.08.007

Source DB:  PubMed          Journal:  Crit Care Clin        ISSN: 0749-0704            Impact factor:   3.598


  122 in total

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  6 in total

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