Long-COVID Clinical Features and Risk Factors: A Retrospective Analysis of Patients from the STOP-COVID Registry of the PoLoCOV Study.

Despite recovering from the acute phase of coronavirus disease (COVID-19), many patients report continuing symptoms that most commonly include fatigue, cough, neurologic problems, hair loss, headache, and musculoskeletal pain, a condition termed long-COVID syndrome. Neither its etiopathogenesis, nor its clinical presentation or risk factors are fully understood. Therefore, the purpose of this study was to retrospectively evaluate the most common symptoms of long-COVID among patients from the STOP COVID registry of the PoLoCOV study, and to search for risk factors for development of the syndrome. The registry includes patients who presented to the medical center for persistent clinical symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The analysis included data from initial presentation and at three-month follow-up. Of the 2218 patients, 1569 (70.7%) reported having at least one symptom classified as long-COVID syndrome three months after recovery from the initial SARS-CoV-2 infection. The most common symptoms included chronic fatigue (35.6%\), cough (23.0%), and a set of neurological symptoms referred to as brain fog (12.1%). Risk factors for developing long-COVID syndrome included female gender (odds ratio [OR]: 1.48, 95% confidence intervals [CI] [1.19-1.84]), severe COVID-19 (OR: 1.56, CI: 1.00-2.42), dyspnea (OR: 1.31, CI: 1.02-1.69), and chest pain (OR: 1.48, CI: 1.14-1.92). Long-COVID syndrome represents a significant clinical and social problem. The most common clinical manifestations are chronic fatigue, cough, and brain fog. Given the still-limited knowledge of long-COVID syndrome, further research and observation are needed to better understand the mechanisms and risk factors of the disease.

Associations between physical activity prior to infection and COVID-19 disease severity and symptoms: results from the prospective Predi-COVID cohort study.

OBJECTIVE: To investigate if the physical activity (PA) prior to infection is associated with the severity of the disease in patients positively tested for COVID-19, as well as with the most common symptoms. DESIGN: A cross-sectional study using baseline data from a prospective, hybrid cohort study (Predi-COVID) in Luxembourg. Data were collected from May 2020 to June 2021. SETTING: Real-life setting (at home) and hospitalised patients. PARTICIPANTS: All volunteers aged >18 years with confirmed SARS-CoV-2 infection, as determined by reverse transcription-PCR, and having completed the PA questionnaire (n=452). PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was disease severity (asymptomatic, mild illness and moderate illness). The secondary outcomes were self-reported symptoms. RESULTS: From the 452 patients included, 216 (48%) were female, the median (IQR) age was 42 (31-51) years, 59 (13%) were classified as asymptomatic, 287 (63%) as mild illness and 106 (24%) as moderate illness. The most prevalent symptoms were fatigue (n=294; 65%), headache (n=281; 62%) and dry cough (n=241; 53%). After adjustment, the highest PA level was associated with a lower risk of moderate illness (OR 0.37; 95% CI 0.14 to 0.98, p=0.045), fatigue (OR 0.54; 95% CI 0.30 to 0.97, p=0.040), dry cough (OR 0.55; 95% CI 0.32 to 0.96, p=0.034) and chest pain (OR 0.32; 95% CI 0.14 to 0.77, p=0.010). CONCLUSIONS: PA before COVID-19 infection was associated with a reduced risk of moderate illness severity and a reduced risk of experiencing fatigue, dry cough and chest pain, suggesting that engaging in PA may be an effective approach to minimise the severity of COVID-19. TRIAL REGISTRATION NUMBER: NCT04380987.

Clinical features of 375 COVID-19 cases imported from Russia through the Suifenhe port and countermeasures.

BACKGROUND AND OBJECTIVES: At present, the focus of the fighting against COVID-19 in China is shifting to strictly prevent the entrance of cases from abroad and disease transmission. Therefore, it is extremely urgent to better understand the clinical features of imported cases from overseas countries, which is conductive to formulate the corresponding countermeasures. This study aimed to describe the clinical features of COVID-19 cases imported from Russia through the Suifenhe port, in order to identify baseline and clinical data associated with disease progression and present corresponding countermeasures. METHODS: All COVID-19 cases imported from Russia through the Suifenhe port were included in this retrospective study. According to the "Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (seventh edition)", imported COVID-19 cases were divided into asymptomatic infection, mild, moderate, severe, and critical groups. Baseline and clinical data, including age, gender, comorbidities, disease severity, symptoms at onset, body temperature, white blood cell (WBC) count, lymphocyte (LYMPH) count, lymphocyte percentage (LYM%), C-reactive protein (CRP), oxygenation index (OI), and the use therapeutic modalities were obtained on admission, and then compared between groups. RESULTS: A total of 375 COVID-19 cases imported from Russia through Suifenhe port were included, of whom the asymptomatic infection, mild, moderate, severe, and critical groups accounted for 4.0%, 13.9%, 75.5%, 5.3%, and 1.3%, respectively. The majority of the imported COVID-19 cases were men (61.9%) with a median age of 38.72 years who had no comorbidity (87.7%). Nearly one-third of them (33.1%) were asymptomatic at onset, and common initial symptoms included fever (36.5%), cough (36.0%), pharyngeal discomfort (12.3%), expectoration (8.0%), and chest tightness (5.3%). In total, 180 (48%) and 4 (1.1%) enrolled imported cases received nasal tube oxygen inhalation therapy and high-flow oxygen absorption, respectively; the remaining patients did not undergo oxygen therapy. The values of age, body temperature, WBC, LYMPH, LYM%, CRP, and OI were 38.72 ± 10.50, 35.10 ± 7.92, 5.59 ± 1.97, 1.67 ± 0.68, 31.05 ± 10.22, 8.00 ± 14.75, and 389.03 ± 74.07, respectively. Gender, age, LYMPH, LYM%, symptoms at onset, cough, fever, other rare symptoms, and oxygen therapy showed significant differences between groups (P = 0.036, < 0.001, < 0.001, < 0.001, < 0.001, < 0.001, < 0.001, = 0.045, < 0.001, respectively). CONCLUSIONS: Compared with domestic confirmed patients, COVID-19 patients who arrived at China from Russia through the Suifenhe port had significantly different clinical features, and the differences in gender, age, LYMPH, LYM%, symptoms at onset, cough, fever, other rare symptoms, and oxygen therapy between groups were statistically significant. Therefore, detailed and comprehensive countermeasures were developed to manage and prevent another outbreak based on these clinical features.

Clinical Features and Laboratory Examination to Identify Severe Patients with COVID-19: A Systematic Review and Meta-Analysis.

BACKGROUND: With the COVID-19 epidemic breakout in China, up to 25% of diagnosed cases are considered to be severe. To effectively predict the progression of COVID-19 via patients' clinical features at an early stage, the prevalence of these clinical factors and their relationships with severe illness were assessed. METHODS: In this study, electronic databases (PubMed, Embase, Web of Science, and Chinese database) were searched to obtain relevant studies, including information on severe patients. Publication bias analysis, sensitivity analysis, prevalence, sensitivity, specificity, likelihood ratio, diagnosis odds ratio calculation, and visualization graphics were achieved through software Review Manager 5.3, Stata 15, Meta-DiSc 1.4, and R. RESULTS: Data of 3.547 patients from 24 studies were included in this study. The results revealed that patients with chronic respiratory system diseases (pooled positive likelihood 6.07, 95% CI: 3.12-11.82), chronic renal disease (4.79, 2.04-11.25), cardiovascular disease (3.45, 2.19-5.44), and symptoms of the onset of chest tightness (3.8, 1.44-10.05), shortness of breath (3.18, 2.24-4.51), and diarrhea (2.04, 1.38-3.04) exhibited increased probability of progressing to severe illness. C-reactive protein, ratio of neutrophils to lymphocytes, and erythrocyte sedimentation rate increased a lot in severe patients compared to nonsevere. Yet, it was found that clinical features including fever, cough, and headache, as well as some comorbidities, have little warning value. CONCLUSIONS: The clinical features and laboratory examination could be used to estimate the process of infection in COVID-19 patients. The findings contribute to the more efficient prediction of serious illness for patients with COVID-19 to reduce mortality.

Discovery and Full Genome Characterization of SARS-CoV-2 in Stool Specimen from a Recovered Patient, China.

SARS-CoV-2 was found in a recovered patient's stool specimen by combining quantitative reverse transcription PCR (qRT-PCR) and genome sequencing. The patient was virus positive in stool specimens for at least an additional 15 days after he was recovered, whereas respiratory tract specimens were negative. The discovery of the complete genome of SARS-CoV-2 in the stool sample of the recovered patient demonstrates a cautionary warning that the potential mode of the virus transmission cannot be excluded through the fecal-oral route after viral clearance in the respiratory tract.

Clinical and laboratory factors associated with coronavirus disease 2019 (Covid-19): A systematic review and meta-analysis.

SARS Coronavirus-2 is one of the most widespread viruses globally during the 21st century, whose severity and ability to cause severe pneumonia and death vary. We performed a comprehensive systematic review of all studies that met our standardised criteria and then extracted data on the age, symptoms, and different treatments of Covid-19 patients and the prognosis of this disease during follow-up. Cases in this study were divided according to severity and death status and meta-analysed separately using raw mean and single proportion methods. We included 171 complete studies including 62,909 confirmed cases of Covid-19, of which 148 studies were meta-analysed. Symptoms clearly emerged in an escalating manner from mild-moderate symptoms, pneumonia, severe-critical to the group of non-survivors. Hypertension (Pooled proportion (PP): 0.48 [95% Confident interval (CI): 0.35-0.61]), diabetes (PP: 0.23 [95% CI: 0.16-0.33]) and smoking (PP: 0.12 [95% CI: 0.03-0.38]) were highest regarding pre-infection comorbidities in the non-survivor group. While acute respiratory distress syndrome (PP: 0.49 [95% CI: 0.29-0.78]), (PP: 0.63 [95% CI: 0.34-0.97]) remained one of the most common complications in the severe and death group respectively. Bilateral ground-glass opacification (PP: 0.68 [95% CI: 0.59-0.75]) was the most visible radiological image. The mortality rates estimated (PP: 0.11 [95% CI: 0.06-0.19]), (PP: 0.03 [95% CI: 0.01-0.05]), and (PP: 0.01 [95% CI: 0-0.3]) in severe-critical, pneumonia and mild-moderate groups respectively. This study can serve as a high evidence guideline for different clinical presentations of Covid-19, graded from mild to severe, and for special forms like pneumonia and death groups.

Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people.

BACKGROUND: Rapid detection, isolation, and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and investigated whether predictive symptoms differ between the B.1.1.7 (Alpha) lineage (predominating as of April 2021 in the US, UK, and elsewhere) and wild type. METHODS AND FINDINGS: We obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,370 volunteers aged 5 years and above (6,450 positive cases) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This study involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%-27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR-positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least 1 symptom identified 7 symptoms as jointly and positively predictive of PCR positivity in rounds 2-7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The resulting model (rounds 2-7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same 7 symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although when comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. The main limitations of our study are (i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England and (ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptom prevalence in England. CONCLUSIONS: Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of 7 symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage.

Add-on effect of Chinese herbal medicine in the treatment of mild to moderate COVID-19: A systematic review and meta-analysis.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic since its outbreak in Wuhan, China. It is an urgent task to prevent and treat COVID-19 effectively early. In China's experience combating the COVID-19 pandemic, Chinese herbal medicine (CHM) has played an indispensable role. A large number of epidemiological investigations have shown that mild to moderate COVID-19 accounts for the largest proportion of cases. It is of great importance to treat such COVID-19 cases, which can help control epidemic progression. Many trials have shown that CHM combined with conventional therapy in the treatment of mild to moderate COVID-19 was superior to conventional therapy alone. This review was designed to evaluate the add-on effect of CHM in the treatment of mild to moderate COVID-19. METHODS: Eight electronic databases including PubMed, EMBASE, Cochrane Central Register of Controlled Trials, the Clinical Trials.gov website, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Wanfang Database and China Biology Medicine (CBM) were searched from December 2019 to March 2021 without language restrictions. Two reviewers searched and selected studies, and extracted data according to inclusion and exclusion criteria independently. Cochrane Risk of Bias (ROB) tool was used to assess the methodological quality of the included RCTs. Review Manager 5.3.0 software was used for statistical analysis. RESULTS: Twelve eligible RCTs including 1393 participants were included in this meta-analysis. Our meta-analyses found that lung CT parameters [RR = 1.26, 95% CI (1.15, 1.38), P<0.00001] and the clinical cure rate [RR = 1.26, 95%CI (1.16, 1.38), P<0.00001] of CHM combined with conventional therapy in the treatment of mild to moderate COVID-19 were better than those of conventional therapy. The rate of conversion to severe cases [RR = 0.48, 95%CI (0.32, 0.73), P = 0.0005], TCM symptom score of fever [MD = -0.62, 95%CI (-0.79, -0.45), P<0.00001], cough cases [RR = 1.43, 95%CI (1.16, 1.75), P = 0.0006], TCM symptom score of cough[MD = -1.07, 95%CI (-1.29, -0.85), P<0.00001], TCM symptom score of fatigue[MD = -0.66, 95%CI (-1.05, -0.28), P = 0.0007], and CRP[MD = -5.46, 95%CI (-8.19, -2.72), P<0.0001] of combination therapy was significantly lower than that of conventional therapy. The WBC count was significantly higher than that of conventional therapy[MD = 0.38, 95%CI (0.31, 0.44), P<0.00001]. Our meta-analysis results were robust through sensitivity analysis. CONCLUSION: Chinese herbal medicine combined with conventional therapy may be effective and safe in the treatment of mild to moderate COVID-19. More high-quality RCTs are needed in the future.

An ensemble learning approach to digital corona virus preliminary screening from cough sounds.

This work develops a robust classifier for a COVID-19 pre-screening model from crowdsourced cough sound data. The crowdsourced cough recordings contain a variable number of coughs, with some input sound files more informative than the others. Accurate detection of COVID-19 from the sound datasets requires overcoming two main challenges (i) the variable number of coughs in each recording and (ii) the low number of COVID-positive cases compared to healthy coughs in the data. We use two open datasets of crowdsourced cough recordings and segment each cough recording into non-overlapping coughs. The segmentation enriches the original data without oversampling by splitting the original cough sound files into non-overlapping segments. Splitting the sound files enables us to increase the samples of the minority class (COVID-19) without changing the feature distribution of the COVID-19 samples resulted from applying oversampling techniques. Each cough sound segment is transformed into six image representations for further analyses. We conduct extensive experiments with shallow machine learning, Convolutional Neural Network (CNN), and pre-trained CNN models. The results of our models were compared to other recently published papers that apply machine learning to cough sound data for COVID-19 detection. Our method demonstrated a high performance using an ensemble model on the testing dataset with area under receiver operating characteristics curve = 0.77, precision = 0.80, recall = 0.71, F1 measure = 0.75, and Kappa = 0.53. The results show an improvement in the prediction accuracy of our COVID-19 pre-screening model compared to the other models.

Prevalence of COVID-19 in 10,000 samples from 7853 patients in Eastern Turkey by positive real-time PCR.

Aim: COVID-19, caused by SARS-CoV-2, started in December 2019 and has spread across the world. Materials & methods: We analyzed real-time PCR results of 10,000 samples from 2 April to 30 May 2020 in three neighbor cities located in the East of Turkey. The final study population was 7853 cases, after excluding screening tests. Results: Real-time PCR was performed to detect the SARS-CoV-2-specific RNA-dependent-RNA-polymerase gene fragment. The number of total positive samples out of 7853 were 487; however, the number of nonrepeating positive patient was 373 (4.8%). Cough and fever were the most common symptoms in positive cases. Conclusion: Epidemiologic studies should be performed about the prevalence of SARS-CoV-2 infection to better understand the effect of the virus across the world.

Ear, Nose, and Throat Manifestations of COVID-19 in Children.

The article reviews and analyzes the different ear, nose, and throat (ENT)-related manifestations reported in coronavirus disease 2019 (COVID-19)-positive pediatric patients (age <18 years) in peer-reviewed and published literature. We searched the PubMed database using medical subject headings and associated key words, focusing on ENT symptoms in children with COVID-19. We included relevant published and peer-reviewed articles in English and excluded case reports and articles in press. There were 1,140 children positive for COVID-19 (56% boys) in the 23 studies included in this review. Although 11% of patients were asymptomatic, the most common symptoms reported were fever (48%) and cough (37%). Nasal symptoms (stuffy nose, nasal congestion, rhinorrhea) and sore throat occurred in about 22% of all patients. Otitis, dizziness, anosmia, and ageusia are hardly reported in children with COVID-19. Although fever and cough are the most common symptoms, ENT manifestations are frequently observed in pediatric patients with COVID-19. [Pediatr Ann. 2021;50(7):e277-e281.].

Factors associated with mortality in patients hospitalized with COVID-19: A prospective cohort in a Peruvian national referral hospital. / Factores asociados a mortalidad en pacientes hospitalizados con COVID-19: cohorte prospectiva en un hospital de referencia nacional de Perú.

OBJECTIVES: To describe and assess clinical characteristics and factors associated with mortality in adult patients with COVID-19 admitted to a national referral hospital in Peru. METHODS: We conducted a prospective cohort study that included hospitalized patients older than 18 years with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection diagnosis. Patients with a positive rapid serological test on admission but no respiratory symptoms nor compatible images were excluded. We collected the data from clinical records. RESULTS: A total of 813 adults were included, 544 (66.9%) with confirmed COVID-19. The mean age was 61.2 years (standard deviation: 15.0), and 575 (70.5%) were male. The most frequent comorbidities were hypertension (34.1%) and obesity (25.9%). On admission, the most frequent symptoms were dyspnea (82.2%) and cough (53.9%). A total of 114 (14.0%) patients received mechanical ventilation, 38 (4.7%) were admitted to the intensive care unit, and 377 (46.4%) died. The requirement for ventilatory support, greater lung involvement, and inflammatory markers were associated with higher mortality. It was found that for every 10-year age increase, the risk of dying increased 32% (relative risk: 1.32; 95% confidence interval: 1.25 to 1.38). Those who were admitted to the intensive care unit and and were placed on mechanical ventilation had 1.39 (95% confidence interval: 1.13 to 1.69) and 1.97 (95% confidence interval: 1.69 to 2.29) times the risk of dying compared to those who did not, respectively. CONCLUSION: We found a high mortality rate among hospitalized patients associated with older age, higher inflammatory markers, and greater lung involvement.

OBJETIVOS: Describir las características clínicas y evaluar los factores asociados con la mortalidad de los pacientes adultos con la nueva enfermedad causada por coronavirus 2019 (COVID-19) ingresados a un hospital de referencia nacional de Perú. MÉTODOS: Se realizó un estudio de cohorte prospectivo. Se incluyó a pacientes mayores de 18 años hospitalizados con el diagnóstico de infección por coronavirus 2 del síndrome respiratorio agudo severo (SARS-CoV-2). Se excluyó a quienes ingresaron con prueba rápida serológica positiva al ingreso, sin clínica sugestiva ni imágenes compatibles. Los datos se recolectaron a partir de la historia clínica. RESULTADOS: Se incluyó un total de 813 adultos, 544 (66,9%) tuvieron COVID-19 confirmado. La media de la edad fue de 61,2 años (desviación estándar: 15) y 575 (70,5%) fueron de sexo masculino. Las comorbilidades más frecuentes fueron hipertensión arterial (34,1%) y obesidad (25,9%). Los síntomas más frecuentes al ingreso fueron disnea (82,2%) y tos (53,9%). Un total de 114 (14%) pacientes recibieron ventilación mecánica, 38 (4,7%) ingresaron a unidad de cuidados intensivos y 377 (46,4%) fallecieron. Se asociaron a la mortalidad el requerimiento de soporte ventilatorio, el mayor compromiso pulmonar y los marcadores inflamatorios. Encontramos que por cada 10 años que aumentó la edad, el riesgo de morir se incrementó en 32% (riesgo relativo: 1,32; intervalo de confianza 95%: 1,25 a 1,38). Aquellos pacientes que requirieron ingreso a unidad de cuidados intensivos y ventilación mecánica tuvieron 1,39 (intervalo de confianza 95%: 1,13 a 1,69) y 1,97 (intervalo de confianza 95%: 1,69 a 2,29) veces el riesgo de morir, respectivamente. CONCLUSIÓN: La mortalidad encontrada en nuestro estudio fue alta y estuvo asociada a la edad, marcadores inflamatorios y compromiso respiratorio.

Factores asociados a mortalidad en pacientes hospitalizados con COVID-19: cohorte prospectiva en un hospital de referencia nacional de Perú / Factors associated with mortality in patients hospitalized with COVID-19: a prospective cohort in a Peruvian national referral hospital

Objetivos Describir las características clínicas y evaluar los factores asociados con la mortalidad de los pacientes adultos con la nueva enfermedad causada por coronavirus 2019 (COVID-19) ingresados a un hospital de referencia nacional de Perú. Métodos Se realizó un estudio de cohorte prospectivo. Se incluyó a pacientes mayores de 18 años hospitalizados con el diagnóstico de infección por coronavirus 2 del síndrome respiratorio agudo severo (SARS-CoV-2). Se excluyó a quienes ingresaron con prueba rápida serológica positiva al ingreso, sin clínica sugestiva ni imágenes compatibles. Los datos se recolectaron a partir de la historia clínica. Resultados Se incluyó un total de 813 adultos, 544 (66,9%) tuvieron COVID-19 confirmado. La media de la edad fue de 61,2 años (desviación estándar: 15) y 575 (70,5%) fueron de sexo masculino. Las comorbilidades más frecuentes fueron hipertensión arterial (34,1%) y obesidad (25,9%). Los síntomas más frecuentes al ingreso fueron disnea (82,2%) y tos (53,9%). Un total de 114 (14%) pacientes recibieron ventilación mecánica, 38 (4,7%) ingresaron a unidad de cuidados intensivos y 377 (46,4%) fallecieron. Se asociaron a la mortalidad el requerimiento de soporte ventilatorio, el mayor compromiso pulmonar y los marcadores inflamatorios. Encontramos que por cada 10 años que aumentó la edad, el riesgo de morir se incrementó en 32% (riesgo relativo: 1,32; intervalo de confianza 95%: 1,25 a 1,38). Aquellos pacientes que requirieron ingreso a unidad de cuidados intensivos y ventilación mecánica tuvieron 1,39 (intervalo de confianza 95%: 1,13 a 1,69) y 1,97 (intervalo de confianza 95%: 1,69 a 2,29) veces el riesgo de morir, respectivamente. Conclusión La mortalidad encontrada en nuestro estudio fue alta y estuvo asociada a la edad, marcadores inflamatorios y compromiso respiratorio.

Objectives To describe and assess clinical characteristics and factors associated with mortality in adult patients with COVID-19 admitted to a national referral hospital in Peru. Methods We conducted a prospective cohort study that included hospitalized patients older than 18 years with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection diagnosis. Patients with a positive rapid serological test on admission but no respiratory symptoms nor compatible images were excluded. We collected the data from clinical records. Results A total of 813 adults were included, 544 (66.9%) with confirmed COVID-19. The mean age was 61.2 years (standard deviation: 15.0), and 575 (70.5%) were male. The most frequent comorbidities were hypertension (34.1%) and obesity (25.9%). On admission, the most frequent symptoms were dyspnea (82.2%) and cough (53.9%). A total of 114 (14.0%) patients received mechanical ventilation, 38 (4.7%) were admitted to the intensive care unit, and 377 (46.4%) died. The requirement for ventilatory support, greater lung involvement, and inflammatory markers were associated with higher mortality. It was found that for every 10-year age increase, the risk of dying increased 32% (relative risk: 1.32; 95% confidence interval: 1.25 to 1.38). Those who were admitted to the intensive care unit and and were placed on mechanical ventilation had 1.39 (95% confidence interval: 1.13 to 1.69) and 1.97 (95% confidence interval: 1.69 to 2.29) times the risk of dying compared to those who did not, respectively. Conclusion We found a high mortality rate among hospitalized patients associated with older age, higher inflammatory markers, and greater lung involvement.

Is carbonic anhydrase inhibition useful as a complementary therapy of Covid-19 infection?

The ongoing Covid-19 is a contagious disease, and it is characterised by different symptoms such as fever, cough, and shortness of breath. Rising concerns about Covid-19 have severely affected the healthcare system in all countries as the Covid-19 outbreak has developed at a rapid rate all around the globe. Intriguing, a clinically used drug, acetazolamide (a specific inhibitor of carbonic anhydrase, CA, EC 4.2.1.1), is used to treat high-altitude pulmonary oedema (HAPE), showing a high degree of clinical similarities with the pulmonary disease caused by Covid-19. In this context, this preliminary study aims to provide insights into some factors affecting the Covid-19 patients, such as hypoxaemia, hypoxia as well as the blood CA activity. We hypothesise that patients with Covid-19 problems could show a dysregulated acid-base status influenced by CA activity. These preliminary results suggest that the use of CA inhibitors as a pharmacological treatment for Covid-19 may be beneficial.

Modeling of aerosol transmission of airborne pathogens in ICU rooms of COVID-19 patients with acute respiratory failure.

The COVID-19 pandemic has generated many concerns about cross-contamination risks, particularly in hospital settings and Intensive Care Units (ICU). Virus-laden aerosols produced by infected patients can propagate throughout ventilated rooms and put medical personnel entering them at risk. Experimental results found with a schlieren optical method have shown that the air flows generated by a cough and normal breathing were modified by the oxygenation technique used, especially when using High Flow Nasal Canulae, increasing the shedding of potentially infectious airborne particles. This study also uses a 3D Computational Fluid Dynamics model based on a Lattice Boltzmann Method to simulate the air flows as well as the movement of numerous airborne particles produced by a patient's cough within an ICU room under negative pressure. The effects of different mitigation scenarii on the amount of aerosols potentially containing SARS-CoV-2 that are extracted through the ventilation system are investigated. Numerical results indicate that adequate bed orientation and additional air treatment unit positioning can increase by 40% the number of particles extracted and decrease by 25% the amount of particles deposited on surfaces 45s after shedding. This approach could help lay the grounds for a more comprehensive way to tackle contamination risks in hospitals, as the model can be seen as a proof of concept and be adapted to any room configuration.

The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms.

Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. The COUGHVID dataset provides over 25,000 crowdsourced cough recordings representing a wide range of participant ages, genders, geographic locations, and COVID-19 statuses. First, we contribute our open-sourced cough detection algorithm to the research community to assist in data robustness assessment. Second, four experienced physicians labeled more than 2,800 recordings to diagnose medical abnormalities present in the coughs, thereby contributing one of the largest expert-labeled cough datasets in existence that can be used for a plethora of cough audio classification tasks. Finally, we ensured that coughs labeled as symptomatic and COVID-19 originate from countries with high infection rates. As a result, the COUGHVID dataset contributes a wealth of cough recordings for training ML models to address the world's most urgent health crises.

Clinical, Biochemical and Molecular Evaluations of Ivermectin Mucoadhesive Nanosuspension Nasal Spray in Reducing Upper Respiratory Symptoms of Mild COVID-19.

BACKGROUND: Ivermectin is an FDA-approved broad-spectrum anti-parasitic agent that has been shown to inhibit SARS-CoV-2 replication in vitro. OBJECTIVE: We aimed to assess the therapeutic efficacy of ivermectin mucoadhesive nanosuspension intranasal spray in treatment of patients with mild COVID-19. METHODS: This clinical trial included 114 patients diagnosed as mild COVID-19. Patients were divided randomly into two age and sex-matched groups; group A comprising 57 patients received ivermectin nanosuspension nasal spray twice daily plus the Egyptian protocol of treatment for mild COVID-19 and group B comprising 57 patients received the Egyptian protocol for mild COVID-19 only. Evaluation of the patients was performed depending on improvement of presenting manifestations, negativity of two consecutive pharyngeal swabs for the COVID-19 nucleic acid via rRT-PCR and assessments of hematological and biochemical parameters in the form of complete blood counts, C-reactive protein, serum ferritin and d-dimer which were performed at presentation and 7 days later. RESULTS: Of the included patients confirmed with mild COVID-19, 82 were males (71.9%) and 32 females (28.1%) with mean age 45.1 ± 18.9. In group A, 54 patients (94.7%) achieved 2 consecutive negative PCR nasopharyngeal swabs in comparison to 43 patients (75.4%) in group B with P = 0.004. The durations of fever, cough, dyspnea and anosmia were significantly shorter in group A than group B, without significant difference regarding the duration of gastrointestinal symptoms. Duration taken for nasopharyngeal swab to be negative was significantly shorter in group A than in group B (8.3± 2.8 days versus 12.9 ± 4.3 days; P = 0.0001). CONCLUSION: Local use of ivermectin mucoadhesive nanosuspension nasal spray is safe and effective in treatment of patients with mild COVID-19 with rapid viral clearance and shortening the anosmia duration. CLINICALTRIALSGOV IDENTIFIER: NCT04716569; https://clinicaltrials.gov/ct2/show/NCT04716569.

Shielding of viruses such as SARS-Cov-2 from ultraviolet radiation in particles generated by sneezing or coughing: Numerical simulations of survival fractions.

SARS-CoV-2 and other microbes within aerosol particles can be partially shielded from UV radiation. The particles refract and absorb light, and thereby reduce the UV intensity at various locations within the particle. Previously, we demonstrated shielding in calculations of UV intensities within spherical approximations of SARS-CoV-2 virions within spherical particles approximating dried-to-equilibrium respiratory fluids. The purpose of this paper is to extend that work to survival fractions of virions (i.e., fractions of virions that can infect cells) within spherical particles approximating dried respiratory fluids, and to investigate the implications of these calculations for using UV light for disinfection. The particles may be on a surface or in air. Here, the survival fraction (S) of a set of individual virions illuminated with a UV fluence (F, in J/m2) is assumed described by S(kF) = exp(-kF), where k is the UV inactivation rate constant (m2/J). The average survival fraction (Sp) of the simulated virions in a group of particles is calculated using the energy absorbed by each virion in the particles. The results show that virions within particles of dried respiratory fluids can have larger Sp than do individual virions. For individual virions, and virions within 1-, 5-, and 9-µm particles illuminated (normal incidence) on a surface with 260-nm UV light, the Sp = 0.00005, 0.0155, 0.22, and 0.28, respectively, when kF = 10. The Sp decrease to <10-7, <10-7, 0.077, and 0.15, respectively, for kF = 100. Results also show that illuminating particles with UV beams from widely separated directions can strongly reduce the Sp. These results suggest that the size distributions and optical properties of the dried particles of virion-containing respiratory fluids are likely important to effectively designing and using UV germicidal irradiation systems for microbes in particles. The results suggest the use of reflective surfaces to increase the angles of illumination and decrease the Sp. The results suggest the need for measurements of the Sp of SARS-CoV-2 in particles having compositions and sizes relevant to the modes of disease transmission.

A Fully-Automated Method to Evaluate Coronavirus Disease Progression with COVID-19 Cough Sounds Using Minimal Phase Information.

This paper focuses on an important issue of disease progression of COVID-19 (coronavirus disease 2019) through processing COVID-19 cough sounds by proposing a fully-automated method. The new method is based on time-domain exploiting only phase 1 data which is always available for any cough events. The proposed approach generates plausible click sequences consist of clicks for various cough samples from covid-19 patients. The click sequence, which is extracted from the phase slope function of an input signal, is used to calculate inter-click intervals (ICIs), and thereby a scoring index (SI) is derived based on coefficient of variation(CV) of the extracted ICIs. Moreover, probability density function (pdf) of the output click sequence is obtained. The method does not need to adjust any parameters. The experimental results achieved from real-recorded COVID-19 cough data using the medically annotated Novel Coronavirus Cough Database (NoCoCoDa) reveal that the proposed time-domain method can be a very useful tool for automatic cough sound processing to determine the disease progression of coronavirus patients.