Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals

"Asynchrony due to reverse-triggering (RT) may appear in ARDS patients. The objective of this study is to validate an algo-rithm developed to detect these alterations in patient–ventilator interaction. We developed an algorithm that uses flow and airway pressure signals to classify breaths as n...

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Autores principales: Rodríguez, Pablo Oscar, Tiribelli, Norberto, Gogniat, Emiliano, Plotnikow, Gustavo A., Fredes, Sebastián, Fernández Ceballos, Ignacio, Pratto, Romina A., Madorno, Matías, Ilutovich, Santiago, San Román, Eduardo, Bonelli, Ignacio, Guaymas, María, Raimondi, Alejandro C., Maskin, Luis Patricio, Setten, Mariano
Formato: Ponencias en Congresos acceptedVersion
Lenguaje:Inglés
Publicado: 2020
Materias:
TRASTORNOS DE LA RESPIRACION
RESPIRACION ARTIFICIAL
ALGORITMOS
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1916
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1916
record_format dspace
spelling I32-R138-123456789-19162022-12-07T14:13:55Z Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals Rodríguez, Pablo Oscar Tiribelli, Norberto Gogniat, Emiliano Plotnikow, Gustavo A. Fredes, Sebastián Fernández Ceballos, Ignacio Pratto, Romina A. Madorno, Matías Ilutovich, Santiago San Román, Eduardo Bonelli, Ignacio Guaymas, María Raimondi, Alejandro C. Maskin, Luis Patricio Setten, Mariano TRASTORNOS DE LA RESPIRACION RESPIRACION ARTIFICIAL ALGORITMOS "Asynchrony due to reverse-triggering (RT) may appear in ARDS patients. The objective of this study is to validate an algo-rithm developed to detect these alterations in patient–ventilator interaction. We developed an algorithm that uses flow and airway pressure signals to classify breaths as normal, RT with or without breath stacking (BS) and patient initiated double-triggering (DT). The diagnostic performance of the algorithm was validated using two datasets of breaths, that are classified as stated above. The first dataset classification was based on visual inspection of esophageal pressure (Pes) signal from 699 breaths recorded from 11 ARDS patients. The other classification was obtained by vote of a group of 7 experts (2 physicians and 5 respiratory therapists, who were trained in ICU), who evaluated 1881 breaths gathered from recordings from 99 sub-jects. Experts used airway pressure and flow signals for breaths classification. The RT with or without BS represented 19% and 37% of breaths in Pes dataset while their frequency in the expert’s dataset were 3% and 12%, respectively. The DT was very infrequent in both datasets. Algorithm classification accuracy was 0.92 (95% CI 0.89–0.94, P < 0.001) and 0.96 (95% CI 0.95–0.97, P < 0.001), in comparison with Pes and experts’ opinion. Kappa statistics were 0.86 and 0.84, respectively. The algorithm precision, sensitivity and specificity for individual asynchronies were excellent. The algorithm yields an excellent accuracy for detecting clinically relevant asynchronies related to RT." 2020-03-26T14:32:13Z 2020-03-26T14:32:13Z 2019 Ponencias en Congresos info:eu-repo/semantics/acceptedVersion 1387-1307 http://ri.itba.edu.ar/handle/123456789/1916 en info:eu-repo/semantics/altIdentifier/doi/10.1007/s10877-019-00444-3 application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic TRASTORNOS DE LA RESPIRACION
RESPIRACION ARTIFICIAL
ALGORITMOS
spellingShingle TRASTORNOS DE LA RESPIRACION
RESPIRACION ARTIFICIAL
ALGORITMOS
Rodríguez, Pablo Oscar
Tiribelli, Norberto
Gogniat, Emiliano
Plotnikow, Gustavo A.
Fredes, Sebastián
Fernández Ceballos, Ignacio
Pratto, Romina A.
Madorno, Matías
Ilutovich, Santiago
San Román, Eduardo
Bonelli, Ignacio
Guaymas, María
Raimondi, Alejandro C.
Maskin, Luis Patricio
Setten, Mariano
Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
topic_facet TRASTORNOS DE LA RESPIRACION
RESPIRACION ARTIFICIAL
ALGORITMOS
description "Asynchrony due to reverse-triggering (RT) may appear in ARDS patients. The objective of this study is to validate an algo-rithm developed to detect these alterations in patient–ventilator interaction. We developed an algorithm that uses flow and airway pressure signals to classify breaths as normal, RT with or without breath stacking (BS) and patient initiated double-triggering (DT). The diagnostic performance of the algorithm was validated using two datasets of breaths, that are classified as stated above. The first dataset classification was based on visual inspection of esophageal pressure (Pes) signal from 699 breaths recorded from 11 ARDS patients. The other classification was obtained by vote of a group of 7 experts (2 physicians and 5 respiratory therapists, who were trained in ICU), who evaluated 1881 breaths gathered from recordings from 99 sub-jects. Experts used airway pressure and flow signals for breaths classification. The RT with or without BS represented 19% and 37% of breaths in Pes dataset while their frequency in the expert’s dataset were 3% and 12%, respectively. The DT was very infrequent in both datasets. Algorithm classification accuracy was 0.92 (95% CI 0.89–0.94, P < 0.001) and 0.96 (95% CI 0.95–0.97, P < 0.001), in comparison with Pes and experts’ opinion. Kappa statistics were 0.86 and 0.84, respectively. The algorithm precision, sensitivity and specificity for individual asynchronies were excellent. The algorithm yields an excellent accuracy for detecting clinically relevant asynchronies related to RT."
format Ponencias en Congresos
acceptedVersion
author Rodríguez, Pablo Oscar
Tiribelli, Norberto
Gogniat, Emiliano
Plotnikow, Gustavo A.
Fredes, Sebastián
Fernández Ceballos, Ignacio
Pratto, Romina A.
Madorno, Matías
Ilutovich, Santiago
San Román, Eduardo
Bonelli, Ignacio
Guaymas, María
Raimondi, Alejandro C.
Maskin, Luis Patricio
Setten, Mariano
author_facet Rodríguez, Pablo Oscar
Tiribelli, Norberto
Gogniat, Emiliano
Plotnikow, Gustavo A.
Fredes, Sebastián
Fernández Ceballos, Ignacio
Pratto, Romina A.
Madorno, Matías
Ilutovich, Santiago
San Román, Eduardo
Bonelli, Ignacio
Guaymas, María
Raimondi, Alejandro C.
Maskin, Luis Patricio
Setten, Mariano
author_sort Rodríguez, Pablo Oscar
title Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
title_short Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
title_full Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
title_fullStr Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
title_full_unstemmed Automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ARDS patients using flow and pressure signals
title_sort automatic detection of reverse‑triggering related asynchronies during mechanical ventilation in ards patients using flow and pressure signals
publishDate 2020
url http://ri.itba.edu.ar/handle/123456789/1916
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