Automatic detection of ventilatory modes during invasive mechanical ventilation

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.

Document Type

Article

Document version

Accepted version

Language

English

Subject (CDU)

61 - Medical sciences

Keywords

Respiració artificial

Assistència mèdica

Pacients

Algoritmes

Respiración artificial

Asistencia médica

Enfermos

Algoritmos

Mechanical ventilation (Therapy)

Medical care

Algorithms

Patients

Publisher

Springer Nature

Collection

20;

Is part of

Critical Care

Recommended citation

Murias, Gastón; Montanyà, Jaume; Chacón, Encarna [et al.]. Automatic detection of ventilatory modes during invasive mechanical ventilation. Critical Care, 2016, vol. 20, p. 1-7. Disponible en: <https://ccforum.biomedcentral.com/articles/10.1186/s13054-016-1436-9#Ack1>. Fecha de acceso: 29 dic. 2019. DOI: 10.1186/s13054-016-1436-9.

Note

This work was funded by projects PI09/91074 and PI13/02204, integrated in the Plan Nacional de R+D+I and co-funded by the ISCIII- Subdirección General de Evaluación y el Fondo Europeo de Desarrollo Regional (FEDER). CIBER Enfermedades Respiratorias, Fundación Mapfre, Fundació Parc Taulí, Plan Avanza TSI-020302-2008-38, MCYIN and MITYC (Spain). Role of the sponsors: no funding organization or sponsor was involved in the design or conduct of the study, in the collection, management, analysis, or interpretation of the data, or in the preparation, review, or approval of the manuscript.

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