A multichannel model-based methodology for extubation readiness decision of patients on weaning trials.

Full Abstract

Discontinuation of mechanical ventilation is a challenging task that involves a number of subtle clinical issues. The gradual removal of the respiratory support (referred to as weaning) should be performed as soon as autonomous respiration can be sustained. However, the prediction rate of successful extubation is still below 25% based on previous studies. Construction of an automatic system that provides information on extubation readiness is thus desirable. Recent works have demonstrated that the breathing pattern variability is a useful extubation readiness indicator, with improving performance when multiple respiratory signals are jointly processed. However, the existing methods for predictor extraction present several drawbacks when length-limited time series are to be processed in heterogeneous groups of patients. In this paper, we propose a model-based methodology for automatic readiness prediction. It is intended to deal with multichannel, nonstationary, short records of the breathing pattern. Results on experimental data yield an 87.27% of successful readiness prediction, which is in line with the best figures reported in the literature. A comparative analysis shows that our methodology overcomes the shortcomings of so far proposed methods when applied to length-limited records on heterogeneous groups of patients.

Author information

Author/s: Casaseca-de-la-Higuera, Pablo (P); Simmross-Wattenberg, Federico (F); Martín-Fernández, Marcos (M); Alberola-López, Carlos (C);

Affiliation: Laboratory of Image Processing, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, 47011 Valladolid, Spain. casaseca(-atsign-)lpi.tel.uva.es

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: IEEE transactions on bio-medical engineering (IEEE Trans Biomed Eng), published in United States. (Language: eng)

Reference: 2009-Jul; vol 56 (issue 7) : pp 1849-63

Dates: Created 2009/06/16; Completed 2009/09/18;

PMID: 19362908, status: MEDLINE (last retrieval date: 9/18/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.