Literature DB >> 28779703

Decision support system facilitates rapid decreases in pressure support and appropriate inspiratory muscle workloads in adults with respiratory failure.

Carl G Tams1, Ali Ataya2, Neil R Euliano3, Paul Stephan4, A Daniel Martin5, Hassan Alnuaimat6, Andrea Gabrielli7.   

Abstract

PURPOSE: A commercially available decision support system (DSS) provides guidance for setting inspiratory pressure support (PS) to maintain work of breathing (WOB/min), breathing frequency (f), and tidal volume (VT) in proper clinical ranges (VentAssist™). If these values are outside the proper clinical range patients may suffer fatigue, atrophy, hypoventilation, hyperventilation, volutrauma, or VT deficiency. The purpose of our study was to evaluate the increase of the percentage of breaths in the targeted clinical ranges when the DSS guidance for setting the PS was followed.
MATERIALS AND METHODS: The study included 43 intubated adults with respiratory failure in an academic medical intensive care unit. Each of the patients had received ventilatory support for >24h with no weaning trials attempted. Clinicians switched the ventilator to PS then proceeded to utilize the guidance recommended by the DSS for setting PS for 21 patients (intervention group); while the clinicians caring for the remaining 23 patients did not have access to the DSS (control group).
RESULTS: The use of a DSS to set PS level increased the percentage of breaths in the targeted clinical range [28% to 48%, p value<0.0001]. An unexpected result was that while following the DSS 18 of the 21 patients were rapidly weaned to minimal ventilator settings within 46±38min; however, when the DSS was not available weaning to minimal ventilator settings lasted 21±12h [p value<0.0001].
CONCLUSIONS: The DSS is successful at assisting clinicians on how to set PS specific to a patient's individual demands (VT and f) while accounting for their breathing effort (WOB/min). The DSS appears to promote rapid weaning of PS to minimal ventilator settings when appropriate.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Decision support; Mechanical ventilation; Weaning

Mesh:

Year:  2017        PMID: 28779703     DOI: 10.1016/j.jcrc.2017.07.047

Source DB:  PubMed          Journal:  J Crit Care        ISSN: 0883-9441            Impact factor:   3.425


  2 in total

1.  Transparent decision support for mechanical ventilation using visualization of clinical preferences.

Authors:  Stephen Edward Rees; Savino Spadaro; Francesca Dalla Corte; Nilanjan Dey; Jakob Bredal Brohus; Gaetano Scaramuzzo; David Lodahl; Robert Ravnholt Winding; Carlo Alberto Volta; Dan Stieper Karbing
Journal:  Biomed Eng Online       Date:  2022-01-24       Impact factor: 2.819

2.  Prognostic factors associated with mortality in mechanically ventilated patients in the intensive care unit: A single-center, retrospective cohort study of 905 patients.

Authors:  Jianfeng Liang; Zhiyong Li; Haishan Dong; Chang Xu
Journal:  Medicine (Baltimore)       Date:  2019-10       Impact factor: 1.817

  2 in total

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