Literature DB >> 20090286

Computerized lung acoustic monitoring can help to differentiate between various chest radiographic densities in critically ill patients.

Shaul Lev1, Yael A Glickman, Ilya Kagan, Maury Shapiro, Osnat Moreh-Rahav, David Dahan, Jonathan Cohen, Milana Grinev, Pierre Singer.   

Abstract

BACKGROUND: Complementary bedside lung monitoring modalities are often sought in order to assist in the differentiation between several lung opacities in the intensive care unit (ICU).
OBJECTIVES: To evaluate the use of computerized lung acoustic monitoring as a complementary approach in the differentiation between various chest radiographic densities in critically ill patients.
METHODS: Lung vibration intensity was assessed in 82 intensive care patients using vibration response imaging. Patients were classified according to their primary findings on chest radiography (CXR): consolidation (n = 35), congestion (n = 10), pleural effusion (n = 15), atelectasis/hypoinflation (n = 10) and normal findings (n = 12). Sixty patients were mechanically ventilated and 22 patients were spontaneously breathing.
RESULTS: Significantly elevated vibration intensity was detected in patients with consolidation, as opposed to pleural effusion, atelectasis and normal CXR (p < 0.01, Mann-Whitney U test). Vibration intensity was also increased for congestion, but this increase was not significant. The positive predictive value of CXR lung opacity in combination with increased vibration intensity to detect consolidations and/or congestions was 95% (20/21). Furthermore, vibration intensity was significantly higher in mechanically ventilated patients compared to spontaneously breathing patients (p = 0.001, Mann-Whitney U test). Differences related to gender, age and body position were not significant.
CONCLUSIONS: Computerized lung acoustic monitoring at the bedside was found to be a useful, readily available, noninvasive, adjunctive tool in the differentiation between various CXR densities in critically ill patients.
Copyright © 2010 S. Karger AG, Basel.

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Year:  2010        PMID: 20090286     DOI: 10.1159/000274382

Source DB:  PubMed          Journal:  Respiration        ISSN: 0025-7931            Impact factor:   3.580


  2 in total

Review 1.  Acoustic Methods for Pulmonary Diagnosis.

Authors:  Adam Rao; Emily Huynh; Thomas J Royston; Aaron Kornblith; Shuvo Roy
Journal:  IEEE Rev Biomed Eng       Date:  2018-10-29

2.  Vibration response imaging: protocol for a systematic review.

Authors:  Marc P Berry; Luigi Camporota; George Ntoumenopoulos
Journal:  Syst Rev       Date:  2013-09-25
  2 in total

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