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Open Access 01-12-2016 | Research

Automatic detection of ventilatory modes during invasive mechanical ventilation

Authors: Gastón Murias, Jaume Montanyà, Encarna Chacón, Anna Estruga, Carles Subirà, Rafael Fernández, Bernat Sales, Candelaria de Haro, Josefina López-Aguilar, Umberto Lucangelo, Jesús Villar, Robert M. Kacmarek, Lluís Blanch

Published in: Critical Care | Issue 1/2016

Abstract

Background

Expert systems can help alleviate problems related to the shortage of human resources in critical care, offering expert advice in complex situations. Expert systems use contextual information to provide advice to staff. In mechanical ventilation, it is crucial for an expert system to be able to determine the ventilatory mode in use. Different manufacturers have assigned different names to similar or even identical ventilatory modes so an expert system should be able to detect the ventilatory mode. The aim of this study is to evaluate the accuracy of an algorithm to detect the ventilatory mode in use.

Methods

We compared the results of a two-step algorithm designed to identify seven ventilatory modes. The algorithm was built into a software platform (BetterCare® system, Better Care SL; Barcelona, Spain) that acquires ventilatory signals through the data port of mechanical ventilators. The sample analyzed compared data from consecutive adult patients who underwent >24 h of mechanical ventilation in intensive care units (ICUs) at two hospitals. We used Cohen’s kappa statistics to analyze the agreement between the results obtained with the algorithm and those recorded by ICU staff.

Results

We analyzed 486 records from 73 patients. The algorithm correctly labeled the ventilatory mode in 433 (89 %). We found an unweighted Cohen’s kappa index of 84.5 % [CI (95 %) = (80.5 %: 88.4 %)].

Conclusions

The computerized algorithm can reliably identify ventilatory mode.

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Title: Automatic detection of ventilatory modes during invasive mechanical ventilation
Authors: Gastón Murias
Jaume Montanyà
Encarna Chacón
Anna Estruga
Carles Subirà
Rafael Fernández
Bernat Sales
Candelaria de Haro
Josefina López-Aguilar
Umberto Lucangelo
Jesús Villar
Robert M. Kacmarek
Lluís Blanch
Publication date: 01-12-2016
Publisher: BioMed Central
Published in: Critical Care / Issue 1/2016
Electronic ISSN: 1364-8535
DOI: https://doi.org/10.1186/s13054-016-1436-9

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Automatic detection of ventilatory modes during invasive mechanical ventilation

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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