Kasim Nour, Bachner-Hinenzon Noa, Brikman Shay, Cheshin Ori, Adler Doron, Dori Guy
Department of Internal Medicine E and Corona, HaEmek Medical Center, Afula, Israel.
Sanolla Ltd. Nesher, Israel.
Biomed Signal Process Control. 2022 Sep;78:103920. doi: 10.1016/j.bspc.2022.103920. Epub 2022 Jun 27.
To characterize the frequencies of breathing sounds signals (BS) in COVID-19 patients at peak disease and pre-discharge from hospitalization using a Smart stethoscope.
Prospective cohort study conducted during the first COVID-19 wave (April-August 2020) in Israel. COVID-19 patients (n = 19) were validated by SARS-Cov-2 PCR test. The healthy control group was composed of 153 volunteers who stated that they were healthy. Power of BS was calculated in the frequency ranges of 0-20, 0-200, and 0-2000 Hz.
The power calculated over frequency ranges 0-20, 20-200, and 200-2000 Hz contributed approximately 45%, 45%, and 10% to the total power calculated over the range 0-2000 Hz, respectively. Total power calculated from the right side of the back showed an increase of 45-80% during peak disease compared with the healthy controls (p < 0.05). The power calculated over the back, in the infrasound range, 0-20 Hz, and not in the 20-2000 Hz range, was greater for the healthy controls than for patients. Using all 3 ranges of frequencies for distinguishing peak disease from healthy controls resulted in sensitivity and specificity of 84% and 91%, respectively. Omitting the 0-20 Hz range resulted in sensitivity and specificity of 74% and 67%, respectively.
The BS power acquired from COVID-19 patients at peak disease was significantly greater than that at pre-discharge from the hospital. The infrasound range had a significant contribution to the total power. Although the source of the infrasound is not presently clear, it may serve as an automated diagnostic tool when more clinical experience is gained with this method.
使用智能听诊器,对新冠病毒疾病(COVID-19)患者在疾病高峰期和出院前的呼吸音信号(BS)频率进行特征描述。
在以色列第一波新冠疫情期间(2020年4月至8月)进行前瞻性队列研究。通过新冠病毒2型(SARS-CoV-2)聚合酶链反应(PCR)检测对19例COVID-19患者进行验证。健康对照组由153名自称健康的志愿者组成。在0-20、0-200和0-2000赫兹的频率范围内计算呼吸音的功率。
在0-20、20-200和200-2000赫兹频率范围内计算出的功率,分别约占0-2000赫兹范围内总功率的45%、45%和10%。从背部右侧计算出的总功率在疾病高峰期比健康对照组增加了45%-80%(p<0.05)。在0-20赫兹的次声范围内,而不是在20-2000赫兹范围内,健康对照组的背部计算出的功率大于患者。使用所有三个频率范围来区分疾病高峰期与健康对照组,敏感性和特异性分别为84%和91%。省略0-20赫兹范围后,敏感性和特异性分别为74%和67%。
COVID-19患者在疾病高峰期获得的呼吸音功率明显大于出院前。次声范围对总功率有显著贡献。尽管目前次声的来源尚不清楚,但当通过这种方法获得更多临床经验时,它可能成为一种自动诊断工具。