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Patient-ventilator asynchronies: types, outcomes and nursing detection skills
Background: Mechanical ventilation is often employed as partial ventilatory support where both the patient and the ventilator work together. The ventilator settings should be adjusted to maintain a harmonious patient–ventilator interaction. However, this balance is often altered by many factors able...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mattioli 1885
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502136/ https://www.ncbi.nlm.nih.gov/pubmed/30539927 http://dx.doi.org/10.23750/abm.v89i7-S.7737 |
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author | Enrico, Bulleri Cristian, Fusi Stefano, Bambi Luigi, Pisani |
author_facet | Enrico, Bulleri Cristian, Fusi Stefano, Bambi Luigi, Pisani |
author_sort | Enrico, Bulleri |
collection | PubMed |
description | Background: Mechanical ventilation is often employed as partial ventilatory support where both the patient and the ventilator work together. The ventilator settings should be adjusted to maintain a harmonious patient–ventilator interaction. However, this balance is often altered by many factors able to generate a patient ventilator asynchrony (PVA). The aims of this review were: to identify PVAs, their typologies and classifications; to describe how and to what extent their occurrence can affect the patients’ outcomes; to investigate the levels of nursing skill in detecting PVAs. Methods: Literature review performed on Cochrane Library, Medline and CINAHL databases.Results:1610 records were identified;43 records were included after double blind screening. PVAs have been classified with respect to the phase of the respiratory cycle or based on the circumstance of occurrence. There is agreement on the existence of 7 types of PVAs: ineffective effort, double trigger, premature cycling, delayed cycling, reverse triggering, flow starvation and auto-cycling. PVAs can be identified through the ventilator graphics monitoring of pressure and flow waveforms. The influence on patient outcomes varies greatly among studies but PVAs are mostly associated with poorer outcomes. Adequately trained nurses can learn and retain how to correctly detect PVAs. Conclusions: Since its challenging interpretation and the potential advantages of its implementation, ventilator graphics monitoring can be classified as an advanced competence for ICU nurses. The knowledge and skills to adequately manage PVAs should be provided by specific post-graduate university courses. |
format | Online Article Text |
id | pubmed-6502136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Mattioli 1885 |
record_format | MEDLINE/PubMed |
spelling | pubmed-65021362019-05-08 Patient-ventilator asynchronies: types, outcomes and nursing detection skills Enrico, Bulleri Cristian, Fusi Stefano, Bambi Luigi, Pisani Acta Biomed Original Article: Technical Skills and Tools Background: Mechanical ventilation is often employed as partial ventilatory support where both the patient and the ventilator work together. The ventilator settings should be adjusted to maintain a harmonious patient–ventilator interaction. However, this balance is often altered by many factors able to generate a patient ventilator asynchrony (PVA). The aims of this review were: to identify PVAs, their typologies and classifications; to describe how and to what extent their occurrence can affect the patients’ outcomes; to investigate the levels of nursing skill in detecting PVAs. Methods: Literature review performed on Cochrane Library, Medline and CINAHL databases.Results:1610 records were identified;43 records were included after double blind screening. PVAs have been classified with respect to the phase of the respiratory cycle or based on the circumstance of occurrence. There is agreement on the existence of 7 types of PVAs: ineffective effort, double trigger, premature cycling, delayed cycling, reverse triggering, flow starvation and auto-cycling. PVAs can be identified through the ventilator graphics monitoring of pressure and flow waveforms. The influence on patient outcomes varies greatly among studies but PVAs are mostly associated with poorer outcomes. Adequately trained nurses can learn and retain how to correctly detect PVAs. Conclusions: Since its challenging interpretation and the potential advantages of its implementation, ventilator graphics monitoring can be classified as an advanced competence for ICU nurses. The knowledge and skills to adequately manage PVAs should be provided by specific post-graduate university courses. Mattioli 1885 2018 /pmc/articles/PMC6502136/ /pubmed/30539927 http://dx.doi.org/10.23750/abm.v89i7-S.7737 Text en Copyright: © 2018 ACTA BIO MEDICA SOCIETY OF MEDICINE AND NATURAL SCIENCES OF PARMA http://creativecommons.org/licenses/by-nc-sa/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License |
spellingShingle | Original Article: Technical Skills and Tools Enrico, Bulleri Cristian, Fusi Stefano, Bambi Luigi, Pisani Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title | Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title_full | Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title_fullStr | Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title_full_unstemmed | Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title_short | Patient-ventilator asynchronies: types, outcomes and nursing detection skills |
title_sort | patient-ventilator asynchronies: types, outcomes and nursing detection skills |
topic | Original Article: Technical Skills and Tools |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502136/ https://www.ncbi.nlm.nih.gov/pubmed/30539927 http://dx.doi.org/10.23750/abm.v89i7-S.7737 |
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