A novel infrasound and audible machine-learning approach to the diagnosis of COVID-19.

Background: The coronavirus disease 2019 (COVID-19) outbreak has rapidly spread around the world, causing a global public health and economic crisis. A critical limitation in detecting COVID-19-related pneumonia is that it is often manifested as a "silent pneumonia", i.e. pulmonary auscultation that sounds "normal" using a standard stethoscope. Chest computed tomography is the gold standard for detecting COVID-19 pneumonia; however, radiation exposure, availability and cost preclude its utilisation as a screening tool for COVID-19 pneumonia. In this study we hypothesised that COVID-19 pneumonia, "silent" to the human ear using a standard stethoscope, is detectable using a full-spectrum auscultation device that contains a machine-learning analysis. Methods: Lung sound signals were acquired, using a novel full-spectrum (3-2000 Hz) stethoscope, from 164 COVID-19 pneumonia patients, 61 non-COVID-19 pneumonia patients and 141 healthy subjects. A machine-learning classifier was constructed and the data were classified into three groups: 1) normal lung sounds, 2) COVID-19 pneumonia and 3) non-COVID-19 pneumonia. Results: Standard auscultation found that 72% of the non-COVID-19 pneumonia patients had abnormal lung sounds compared with only 25% of the COVID-19 pneumonia patients. The classifier's sensitivity and specificity for the detection of COVID-19 pneumonia were 97% and 93%, respectively, when analysing the sound and infrasound data, and they were reduced to 93% and 80%, respectively, without the infrasound data (p<0.01 difference in receiver operating characteristic curves with and without infrasound). Conclusions: This study reveals that useful clinical information exists in the infrasound spectrum of COVID-19-related pneumonia and machine-learning analysis applied to the full spectrum of lung sounds is useful in its detection.

A comparison of the power of breathing sounds signals acquired with a smart stethoscope from a cohort of COVID-19 patients at peak disease, and pre-discharge from the hospital.

Objectives: 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. Methods: 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. Results: 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. Discussion: 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.

Diplopia from abducens nerve paresis as a presenting symptom of COVID-19: a case report and review of literature.

Neurological manifestations of novel coronavirus disease 3019 (COVID-19) remain unclear. We report the case of a 44-year-old febrile man who presented with double vision and headache 2 d after initial symptoms of fatigue, generalized muscle weakness, and loss of appetite. He was subsequently diagnosed with COVID-19 and transient abducens nerve paresis. He did not present with any respiratory symptoms or additional specific neurological findings. We recommend that with the rising number of cases across the world, physicians develop a greater index of suspicion for COVID-19 in patients with cranial neuropathies, even in those with mild disease without typical respiratory symptoms.

The Hyper-Inflammatory Response in Adults with Severe COVID-19 Pneumonia Differs from the Cytokine Storm of Hemophagocytic Syndrome.

BACKGROUND: In this review we described the values of commonly available HScore laboratory markers in patients with coronavirus-19 (COVID-19)-pneumonia associated cytokine storm syndrome (CPN-CSS) and compared results with those of other forms cytokine storm syndrome (O-CSS) to determine a pattern for CPN-CSS. Twelve CPN-CSS studies and six O-CSS studies were included. CPN-CSS typically obtained a single HScore value (e.g., aspartate transaminase > 30 U/L) while failing all other HScore criteria. A typical pattern for CPN-CSS was revealed when compared to O-CSS: lymphopenia vs. pancytopenia and increased vs. decreased fibrinogen. Findings, other than HScore commonly found in CPN-CSS studies, showed elevated lactate dehydrogenase, D-dimer, and C-reactive protein. Although CPN-CSS studies describe severely ill patients, the HScore markers are typically less toxic that O-CSS.

The Hyper-Inflammatory Response in Adults with Severe COVID-19 Pneumonia Differs from the Cytokine Storm of Hemophagocytic Syndrome

In this review we described the values of commonly available HScore laboratory markers in patients with coronavirus-19 (COVID-19)-pneumonia associated cytokine storm syndrome (CPN-CSS) and compared results with those of other forms cytokine storm syndrome (O-CSS) to determine a pattern for CPN-CSS. Twelve CPN-CSS studies and six O-CSS studies were included. CPN-CSS typically obtained a single HScore value (e.g., aspartate transaminase > 30 U/L) while failing all other HScore criteria. A typical pattern for CPN-CSS was revealed when compared to O-CSS: lymphopenia vs. pancytopenia and increased vs. decreased fibrinogen. Findings, other than HScore commonly found in CPN-CSS studies, showed elevated lactate dehydrogenase, D-dimer, and C-reactive protein. Although CPN-CSS studies describe severely ill patients, the HScore markers are typically less toxic that O-CSS.