Pilot study on nocturnal monitoring of crackles in children with pneumonia

Autor: Volker Gross, Ulrich Koehler, Wilfried Nikolaizik, Andreas Weissflog, Olaf Hildebrandt, Lisa Wuensch, Stefanie Weber, Monika Bauck, Keywan Sohrabi
Rok vydání: 2021
Předmět:
Zdroj: ERJ Open Research
article-version (VoR) Version of Record
ERJ Open Research, Vol 7, Iss 4 (2021)
ISSN: 2312-0541
Popis: Background The clinical diagnosis of pneumonia is usually based on crackles at auscultation, but it is not yet clear what kind of crackles are the characteristic features of pneumonia in children. Lung sound monitoring can be used as a “longtime stethoscope”. Therefore, it was the aim of this pilot study to use a lung sound monitor system to detect crackles and to differentiate between fine and coarse crackles in children with acute pneumonia. The change of crackles during the course of the disease shall be investigated in a follow-up study. Patients and methods Crackles were recorded overnight from 22:00 to 06:00 h in 30 children with radiographically confirmed pneumonia. The data for a total of 28 800 recorded 30-s epochs were audiovisually analysed for fine and coarse crackles. Results Fine crackles and coarse crackles were recognised in every patient with pneumonia, but the number of epochs with and without crackles varied widely among the different patients: fine crackles were detected in 40±22% (mean±sd), coarse crackles in 76±20%. The predominant localisation of crackles as recorded during overnight monitoring was in accordance with the radiographic infiltrates and the classical auscultation in most patients. The distribution of crackles was fairly equal throughout the night. However, there were time periods without any crackle in the single patients so that the diagnosis of pneumonia might be missed at sporadic auscultation. Conclusion Nocturnal monitoring can be beneficial to reliably detect fine and coarse crackles in children with pneumonia.
Lung sound monitoring can detect crackles in children with pneumonia and might improve diagnosis https://bit.ly/3CfaCl7
Databáze: OpenAIRE