Automated Lung Sound Analysis in Patients With Pneumoni

Murphy, Raymond L. H.; Vyshedskiy, Andrey; Power, V-A; Bana, Dhirendra S.; Marinelli, P; Wong-Tse, Anna; Paciej, Rozanne

doi:10.1378/chest.124.4_meetingabstracts.190s-b

Cited by 53 publications

(79 citation statements)

References 20 publications

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“…Although we do not as of yet claim a direct clinical application for our results, this does not preclude consideration of the basic mechanistic concepts for eventual clinical use, possibly even a solution which combines multiparametric lung sound analysis with other noninvasive bedside technologies for the assessment of lung function (e.g., electrical impedance tomography). Concurrent pathophysiologic processes could generate competing lung sounds or alter sound transmission in ways that obscure the distinct sound signatures of inspiratory recruitment, e.g., bronchospasm, fibrotic lung changes, and pneumonia [29][30][31][32][33]. Moreover, the present work cannot define to what extent changes in tidal volume bias the detection of the presented dCE parameter.…”

Section: Discussionmentioning

confidence: 78%

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

et al. 2018

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Section: Discussionmentioning

confidence: 78%

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

et al. 2018

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“…The association between crackle classification (fine vs coarse) and the location in the airways of their generation has been previously investigated by Fredberg and Holford, 29 and has been put on a firmer basis by Majumdar et al 30 Although CALSA has not previously been used as an outcome measure for therapeutic interventions, it has been reported that it can detect changes during the course of pharmacologically induced airway obstruction, 31 during forced expiratory maneuvers, 32 and during pathological processes such as pneumonia. 6,33 Baughman and Loudon 5 recorded lung sounds in asthma patients overnight and were able to detect degrees of obstruction severity not revealed by any other measure. CALSA may therefore provide a more sensitive measure to detect alterations in airway geometry than conventional outcome measures.…”

Section: Discussionmentioning

confidence: 99%

Are Crackles an Appropriate Outcome Measure for Airway Clearance Therapy?

Marques

Bruton²,

Barney

et al. 2012

Respir Care

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BACKGROUND: There is an urgent need to develop new outcome measures for respiratory therapy, to evaluate its effectiveness. Adventitious sounds generated from the lungs (crackles and wheezes), can now be quantified and characterized objectively with computer technology. To our knowledge, this is the first reported study designed to assess any change in lung crackles before and after a single session of airway clearance therapy. METHODS: Twenty-three stable bronchiectasis patients were recruited from United Kingdom out-patient clinics and treated with a single session of airway clearance therapy, using the active cycle of breathing technique. Sound recordings were made before and after the session at 7 anatomical chest locations. Computerized lung sound analysis was used to measure crackle parameters: 2-cycle deflection width (2CD), and crackle number per breath cycle (nBC). Perceived breathlessness, lung function, and oxygen saturation data were also recorded. RESULTS: Crackle mean 2CD and mean nBC increased post intervention. Sixteen participants (70%) showed a statistically significant difference in mean crackle 2CD before and after the session at > 1 chest location. Thirteen (57%) participants had a difference between mean crackle 2CD before and after the intervention > 1 Smallest Real Difference (SRD, mean SRD ‫؍‬ 2.23 ms) at > 1 chest location. Differences in mean crackle nBC before and after the intervention did not exceed the SRD (mean SRD ‫؍‬ 32 crackles per breath cycle) in any participant. Perceived breathlessness was significantly reduced post intervention; no significant changes were observed in either lung function or oxygen saturation. CONCLUSIONS: Crackle duration (2CD) was found to change after a single session of airway clearance therapy, and shows promise as a new outcome measure for respiratory therapy interventions.

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“…The subjects underwent automated auscultation with a 16-channel lung-sound analyzer (STG1602, Stethographics, Boston, Massachusetts,) described previously, [7][8][9][10] which uses 14 electret condenser microphones embedded in a soft foam pad that is positioned at a 45°angle on a stretcher or a plastic reclining chair. The subject lies recumbent on the microphone pad and each breathing maneuver is recorded for 20 seconds.…”

Section: Methodsmentioning

confidence: 99%

Crackle Pitch and Rate Do Not Vary Significantly During a Single Automated-Auscultation Session in Patients With Pneumonia, Congestive Heart Failure, or Interstitial Pulmonary Fibrosis

2011

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OBJECTIVE:To determine the variability of crackle pitch and crackle rate during a single automated-auscultation session with a computerized 16-channel lung-sound analyzer. METHODS: Forty-nine patients with pneumonia, 52 with congestive heart failure (CHF), and 18 with interstitial pulmonary fibrosis (IPF) performed breathing maneuvers in the following sequence: normal breathing, deep breathing, cough several times; deep breathing, vital-capacity maneuver, and deep breathing. From the auscultation recordings we measured the crackle pitch and crackle rate. RESULTS: Crackle pitch variability, expressed as a percentage of the average crackle pitch, was small in all patients and in all maneuvers: pneumonia 11%, CHF 11%, pulmonary fibrosis 7%. Crackle rate variability was also small: pneumonia 31%, CHF 32%, IPF 24%. Compared to the first deepbreathing maneuver (100%), the average crackle pitch did not significantly change following coughing (pneumonia 100%, CHF 103%, IPF 100%), the vital-capacity maneuver (pneumonia 100%, CHF 92%, IPF 104%), or during quiet breathing (pneumonia 97%, CHF 100%, IPF 104%). Similarly, the average crackle rate did not change significantly following coughing (pneumonia 105%, CHF 110%, IPF 90%) or the vital-capacity maneuver (pneumonia 102%, CHF 101%, IPF 99%). However, during normal breathing the crackle rate was significantly lower in the patients with pneumonia (74%, P < .001) and significantly higher in the patients with IPF (147%, P < .05) than it was during deep breathing. In patients with CHF the average crackle rate during normal breathing was not significantly different from that during the first deep-breathing maneuver (108%). CONCLUSIONS: Crackle pitch and rate were surprisingly stable in all 3 conditions. Neither crackle pitch nor crackle rate changed significantly from breath to breath or from one deepbreathing maneuver to another, even when the maneuvers were separated by cough or the vitalcapacity maneuver. The observation that crackle rate is a reproducible measurement during one automated-auscultation session suggests that crackle rate can be used to follow the course of cardiopulmonary illnesses such as pneumonia, IPF, and CHF.

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Automated Lung Sound Analysis in Patients With Pneumoni

Cited by 53 publications

References 20 publications

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

Are Crackles an Appropriate Outcome Measure for Airway Clearance Therapy?

Crackle Pitch and Rate Do Not Vary Significantly During a Single Automated-Auscultation Session in Patients With Pneumonia, Congestive Heart Failure, or Interstitial Pulmonary Fibrosis

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