Automated versus non-automated weaning for reducing the duration of mechanical ventilation for critically ill adults and children: a cochrane systematic ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Louise Rose, Marcus J Schultz, Chris R Cardwell, Philippe Jouvet, Danny F McAuley, Bronagh Blackwood

ABSTRACT

INTRODUCTION: Automated weaning systems may improve adaptation of mechanical support for a patient's ventilatory needs and facilitate systematic and early recognition of their ability to breathe spontaneously and the potential for discontinuation of ventilation. Our objective was to compare mechanical ventilator weaning duration for critically ill adults and children when managed with automated systems versus non-automated strategies. Secondary objectives were to determine differences in duration of ventilation, intensive care unit (ICU) and hospital length of stay (LOS), mortality, and adverse events. METHODS: Electronic databases were searched to 30 September 2013 without language restrictions. We also searched conference proceedings; trial registration websites; and article reference lists. Two authors independently extracted data and assessed risk of bias. We combined data using random-effects modelling. RESULTS: We identified 21 eligible trials totalling 1,676 participants. Pooled data from 16 trials indicated that automated systems reduced the geometric mean weaning duration by 30% (95% confidence interval (CI) 13% to 45%), with substantial heterogeneity (I(2) = 87%, P <0.00001). Reduced weaning duration was found with mixed or medical ICU populations (42%, 95% CI 10% to 63%) and Smartcare/PS (28%, 95% CI 7% to 49%) but not with surgical populations or using other systems. Automated systems reduced ventilation duration with no heterogeneity (10%, 95% CI 3% to 16%) and ICU LOS (8%, 95% CI 0% to 15%). There was no strong evidence of effect on mortality, hospital LOS, reintubation, self-extubation and non-invasive ventilation following extubation. Automated systems reduced prolonged mechanical ventilation and tracheostomy. Overall quality of evidence was high. CONCLUSIONS: Automated systems may reduce weaning and ventilation duration and ICU stay. Due to substantial trial heterogeneity an adequately powered, high quality, multi-centre randomized controlled trial is needed. More... »

PAGES

48

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13054-015-0755-6

DOI

http://dx.doi.org/10.1186/s13054-015-0755-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051447499

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25887887


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    "description": "INTRODUCTION: Automated weaning systems may improve adaptation of mechanical support for a patient's ventilatory needs and facilitate systematic and early recognition of their ability to breathe spontaneously and the potential for discontinuation of ventilation. Our objective was to compare mechanical ventilator weaning duration for critically ill adults and children when managed with automated systems versus non-automated strategies. Secondary objectives were to determine differences in duration of ventilation, intensive care unit (ICU) and hospital length of stay (LOS), mortality, and adverse events.\nMETHODS: Electronic databases were searched to 30 September 2013 without language restrictions. We also searched conference proceedings; trial registration websites; and article reference lists. Two authors independently extracted data and assessed risk of bias. We combined data using random-effects modelling.\nRESULTS: We identified 21 eligible trials totalling 1,676 participants. Pooled data from 16 trials indicated that automated systems reduced the geometric mean weaning duration by 30% (95% confidence interval (CI) 13% to 45%), with substantial heterogeneity (I(2)\u2009=\u200987%, P <0.00001). Reduced weaning duration was found with mixed or medical ICU populations (42%, 95% CI 10% to 63%) and Smartcare/PS (28%, 95% CI 7% to 49%) but not with surgical populations or using other systems. Automated systems reduced ventilation duration with no heterogeneity (10%, 95% CI 3% to 16%) and ICU LOS (8%, 95% CI 0% to 15%). There was no strong evidence of effect on mortality, hospital LOS, reintubation, self-extubation and non-invasive ventilation following extubation. Automated systems reduced prolonged mechanical ventilation and tracheostomy. Overall quality of evidence was high.\nCONCLUSIONS: Automated systems may reduce weaning and ventilation duration and ICU stay. Due to substantial trial heterogeneity an adequately powered, high quality, multi-centre randomized controlled trial is needed.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13054-015-0755-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13054-015-0755-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13054-015-0755-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13054-015-0755-6'


 

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