Literature DB >> 2019160

Crackles in patients with fibrosing alveolitis, bronchiectasis, COPD, and heart failure.

P Piirilä1, A R Sovijärvi, T Kaisla, H M Rajala, T Katila.   

Abstract

We have studied the crackling lung sounds of ten patients with cryptogenic fibrosing alveolitis, ten with bronchiectasis, ten with chronic obstructive pulmonary disease, and ten with heart failure by analyzing frequency, waveform, and timing of crackles. The upper frequency limit of inspiratory sounds was higher in CFA than in COPD or in HF. The period of crackling was shorter in COPD than in CFA or BE. Inspiratory crackling terminated significantly earlier in COPD than in CFA, BE, or HF. The initial deflection width and the two-cycle duration of the expanded waveforms of crackles were smaller in CFA than in BE, COPD, or HF. The largest deflection width was smaller in CFA than in BE, HF, or COPD and smaller in BE than in HF. The results indicate that crackling lung sounds in different diseases have distinctive features and that their analysis can be of diagnostic value.

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Year:  1991        PMID: 2019160     DOI: 10.1378/chest.99.5.1076

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  12 in total

1.  Representation and classification of breath sounds recorded in an intensive care setting using neural networks.

Authors:  L R Waitman; K P Clarkson; J A Barwise; P H King
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2.  Acoustic thoracic image of crackle sounds using linear and nonlinear processing techniques.

Authors:  Sonia Charleston-Villalobos; Guadalupe Dorantes-Méndez; Ramón González-Camarena; Georgina Chi-Lem; José G Carrillo; Tomás Aljama-Corrales
Journal:  Med Biol Eng Comput       Date:  2010-07-21       Impact factor: 2.602

3.  Combining neural network and genetic algorithm for prediction of lung sounds.

Authors:  Inan Güler; Hüseyin Polat; Uçman Ergün
Journal:  J Med Syst       Date:  2005-06       Impact factor: 4.460

4.  Validated method for automatic detection of lung sound crackles.

Authors:  T Kaisla; A Sovijärvi; P Piirilä; H M Rajala; S Haltsonen; T Rosqvist
Journal:  Med Biol Eng Comput       Date:  1991-09       Impact factor: 2.602

5.  Toolkit for lung sound analysis.

Authors:  T Rosqvist; E Paajanen; K Kallio; H M Rajala; T Katila; P Piirilä; P Malmberg; A Sovijärvi
Journal:  Med Biol Eng Comput       Date:  1995-03       Impact factor: 2.602

6.  Lung sound analysis correlates to injury and recruitment as identified by computed tomography: an experimental study.

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Journal:  Intensive Care Med       Date:  2011-06-29       Impact factor: 17.440

7.  Wheezes, crackles and rhonchi: simplifying description of lung sounds increases the agreement on their classification: a study of 12 physicians' classification of lung sounds from video recordings.

Authors:  Hasse Melbye; Luis Garcia-Marcos; Paul Brand; Mark Everard; Kostas Priftis; Hans Pasterkamp
Journal:  BMJ Open Respir Res       Date:  2016-04-28

8.  Respiratory sound energy and its distribution patterns following clinical improvement of congestive heart failure: a pilot study.

Authors:  Zhen Wang; Brigitte M Baumann; Karen Slutsky; Karen N Gruber; Smith Jean
Journal:  BMC Emerg Med       Date:  2010-01-15

Review 9.  Auscultation of the respiratory system.

Authors:  Malay Sarkar; Irappa Madabhavi; Narasimhalu Niranjan; Megha Dogra
Journal:  Ann Thorac Med       Date:  2015 Jul-Sep       Impact factor: 2.219

10.  Usefulness of digital velcro crackles detection in identification of interstitial lung disease in patients with connective tissue diseases.

Authors:  Andreina Manfredi; Giulia Cassone; Caterina Vacchi; Fabrizio Pancaldi; Giovanni Della Casa; Stefania Cerri; Lisa De Pasquale; Fabrizio Luppi; Carlo Salvarani; Marco Sebastiani
Journal:  Arch Rheumatol       Date:  2020-06-25       Impact factor: 1.472

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