Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level

Dimitrios Ververidis, Mark van Gils, Christina Passath, Jukka Takala, Lukas Brander

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)

Abstract

Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P aw ) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P aw and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA AL ). We aimed to develop and validate a mathematical algorithm to identify NAVA AL . Paw , Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P aw peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P aw peaks and Vt. The beginning of the P aw and Vt plateaus, and thus NAVA AL , was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA AL visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H 2 O/μV. NAVA AL identified by our model was below the range of visually estimated NAVA AL in two instances and was above in one instance. We conclude that our model identifies NAVA AL in most instances with acceptable accuracy for application in clinical routine and research.
Original languageEnglish
Pages (from-to)2598-2606
JournalIEEE Transactions on Biomedical Engineering
Volume58
Issue number9
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

Fingerprint

Diaphragms
Polynomials
Graphical user interfaces
Unloading
Muscle
Derivatives
Feedback

Cite this

Ververidis, Dimitrios ; van Gils, Mark ; Passath, Christina ; Takala, Jukka ; Brander, Lukas. / Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level. In: IEEE Transactions on Biomedical Engineering. 2011 ; Vol. 58, No. 9. pp. 2598-2606.
@article{1ec5bc1a806e4f8db211846f6854c871,
title = "Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level",
abstract = "Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P aw ) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H 2 O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P aw and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA AL ). We aimed to develop and validate a mathematical algorithm to identify NAVA AL . Paw , Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P aw peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P aw peaks and Vt. The beginning of the P aw and Vt plateaus, and thus NAVA AL , was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA AL visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H 2 O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H 2 O/μV. NAVA AL identified by our model was below the range of visually estimated NAVA AL in two instances and was above in one instance. We conclude that our model identifies NAVA AL in most instances with acceptable accuracy for application in clinical routine and research.",
author = "Dimitrios Ververidis and {van Gils}, Mark and Christina Passath and Jukka Takala and Lukas Brander",
year = "2011",
doi = "10.1109/TBME.2011.2159790",
language = "English",
volume = "58",
pages = "2598--2606",
journal = "IEEE Transactions on Biomedical Engineering",
issn = "0018-9294",
publisher = "Institute of Electrical and Electronic Engineers IEEE",
number = "9",

}

Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level. / Ververidis, Dimitrios; van Gils, Mark; Passath, Christina; Takala, Jukka; Brander, Lukas.

In: IEEE Transactions on Biomedical Engineering, Vol. 58, No. 9, 2011, p. 2598-2606.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level

AU - Ververidis, Dimitrios

AU - van Gils, Mark

AU - Passath, Christina

AU - Takala, Jukka

AU - Brander, Lukas

PY - 2011

Y1 - 2011

N2 - Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P aw ) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H 2 O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P aw and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA AL ). We aimed to develop and validate a mathematical algorithm to identify NAVA AL . Paw , Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P aw peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P aw peaks and Vt. The beginning of the P aw and Vt plateaus, and thus NAVA AL , was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA AL visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H 2 O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H 2 O/μV. NAVA AL identified by our model was below the range of visually estimated NAVA AL in two instances and was above in one instance. We conclude that our model identifies NAVA AL in most instances with acceptable accuracy for application in clinical routine and research.

AB - Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P aw ) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H 2 O/μV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P aw and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA AL ). We aimed to develop and validate a mathematical algorithm to identify NAVA AL . Paw , Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P aw peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P aw peaks and Vt. The beginning of the P aw and Vt plateaus, and thus NAVA AL , was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA AL visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H 2 O/μV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H 2 O/μV. NAVA AL identified by our model was below the range of visually estimated NAVA AL in two instances and was above in one instance. We conclude that our model identifies NAVA AL in most instances with acceptable accuracy for application in clinical routine and research.

U2 - 10.1109/TBME.2011.2159790

DO - 10.1109/TBME.2011.2159790

M3 - Article

VL - 58

SP - 2598

EP - 2606

JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

SN - 0018-9294

IS - 9

ER -