Literature DB >> 18091543

Detecting ineffective triggering in the expiratory phase in mechanically ventilated patients based on airway flow and pressure deflection: feasibility of using a computer algorithm.

Chang-Wen Chen1, Wei-Chieh Lin, Chih-Hsin Hsu, Kuo-Sheng Cheng, Chien-Shun Lo.   

Abstract

OBJECTIVE: Ineffective triggering (IT) is the most common manifestation of patient-ventilator asynchrony in mechanically ventilated patients. IT in the expiratory phase (ITE) accounts for the majority of IT and is associated with characteristic features of flow and airway pressure deflection, caused by ineffective effort from the patient. The purpose of this study was to quantify the characteristics of flow and airway pressure deflections of ITE and, using a computerized algorithm, to evaluate their usefulness in the detection of ITEs.
DESIGN: Prospective, clinical study.
SETTING: Medical intensive care unit in a 1,000-bed university hospital. PATIENTS: A total of 14 mechanically ventilated adult patients with patient-ventilator asynchrony.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: We analyzed 5,899 breaths and found that 1,831 were ITEs. The average values for maximum flow deflection (F(def)) and maximum airway pressure deflection (P(def)) in ITEs were 13.94 +/- 8.0 L/min and 1.91 +/- 0.97 cm H2O. With a starting value of 0.1 L/min for F(def) and 0.01 cm H2O for P(def), the area under the receiver operating characteristics curve of F(def) and P(def) for the detection of ITEs was 0.98 and 0.97, respectively. Sensitivity and specificity for the detection of ITEs were 91.5% and 96.2% for F(def), respectively, for a cutoff value of 5.45 L/min, and 93.3% and 92.9% for Pdef, for a cutoff value of 0.45 cm H2O.
CONCLUSION: We conclude that accurately detecting and quantifying ITEs is feasible using a computerized algorithm based on F(def) and P(def). Such a computerized estimation of patient-ventilator interaction might be helpful for adjusting ventilator settings in an intensive care unit.

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Year:  2008        PMID: 18091543     DOI: 10.1097/01.CCM.0000299734.34469.D9

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  18 in total

1.  Validation of the Better Care® system to detect ineffective efforts during expiration in mechanically ventilated patients: a pilot study.

Authors:  Lluis Blanch; Bernat Sales; Jaume Montanya; Umberto Lucangelo; Oscar Garcia-Esquirol; Ana Villagra; Encarna Chacon; Anna Estruga; Massimo Borelli; Ma Jose Burgueño; Joan C Oliva; Rafael Fernandez; Jesus Villar; Robert Kacmarek; Gastón Murias
Journal:  Intensive Care Med       Date:  2012-05       Impact factor: 17.440

2.  Ineffective efforts during mechanical ventilation: the brain wants, the machine declines.

Authors:  Dimitris Georgopoulos
Journal:  Intensive Care Med       Date:  2012-05       Impact factor: 17.440

3.  The Impact of a Training Intervention on Detection of Patient-Ventilator Asynchronies in Nursing Students.

Authors:  Francesco Gravante; Franco Crisci; Luigi Palmieri; Luciano Cecere; Cristian Fusi; Enrico Bulleri; Luigi Pisani; Stefano Bambi
Journal:  Acta Biomed       Date:  2022-05-12

4.  The Association Between Ventilator Dyssynchrony, Delivered Tidal Volume, and Sedation Using a Novel Automated Ventilator Dyssynchrony Detection Algorithm.

Authors:  Peter D Sottile; David Albers; Carrie Higgins; Jeffery Mckeehan; Marc M Moss
Journal:  Crit Care Med       Date:  2018-02       Impact factor: 7.598

5.  Patient-ventilator dyssynchrony: clinical significance and implications for practice.

Authors:  Karen G Mellott; Mary Jo Grap; Cindy L Munro; Curtis N Sessler; Paul A Wetzel
Journal:  Crit Care Nurse       Date:  2009-09-01       Impact factor: 1.708

6.  Automatic detection of patient-ventilator asynchrony by spectral analysis of airway flow.

Authors:  Guillermo Gutierrez; Guillermo J Ballarino; Hulya Turkan; Juan Abril; Lucy De La Cruz; Connor Edsall; Binu George; Susan Gutierrez; Vinayak Jha; Jalil Ahari
Journal:  Crit Care       Date:  2011-07-12       Impact factor: 9.097

Review 7.  State-of-the-art sensor technology in Spain: invasive and non-invasive techniques for monitoring respiratory variables.

Authors:  Christian Domingo; Lluis Blanch; Gaston Murias; Manel Luján
Journal:  Sensors (Basel)       Date:  2010-05-05       Impact factor: 3.576

8.  On the imperfect synchrony between patient and ventilator.

Authors:  Paolo Navalesi
Journal:  Crit Care       Date:  2011-08-18       Impact factor: 9.097

9.  Transcutaneous electromyographic respiratory muscle recordings to quantify patient-ventilator interaction in mechanically ventilated children.

Authors:  Alette A Koopman; Robert G T Blokpoel; Leo A van Eykern; Frans H C de Jongh; Johannes G M Burgerhof; Martin C J Kneyber
Journal:  Ann Intensive Care       Date:  2018-01-24       Impact factor: 6.925

10.  Monitoring Patient/Ventilator Interactions: Manufacturer's Perspective.

Authors:  Gerard Evers; Carl Van Loey
Journal:  Open Respir Med J       Date:  2009-03-12
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