Clinical and radiological imaging as prognostic predictors in COVID-19 patients

BackgroundSince the announcement of COVID-19 as a pandemic infection, several studies have been performed to discuss the clinical picture, laboratory finding, and imaging features of this disease. The aim of this study is to demarcate the imaging features of novel coronavirus infected pneumonia (NCIP) in different age groups and outline the relation between radiological aspect, including CT severity, and clinical aspect, including age, oxygen saturation, and fatal outcome. We implemented a prospective observational study enrolled 299 laboratory-confirmed COVID-19 patients (169 males and 130 females;age range = 2–91 years;mean age = 38.4 ± 17.2). All patients were submitted to chest CT with multi-planar reconstruction. The imaging features of NCIP in different age groups were described. The relations between CT severity and age, oxygen saturation, and fatal outcome were evaluated.ResultsThe most predominant CT features were bilateral (75.4%), posterior (66.3%), pleural-based (93.5%), lower lobe involvement (89.8%), and ground-glass opacity (94.7%). ROC curve analysis revealed that the optimal cutoff age that was highly exposed to moderate and severe stages of NCIP was 38 years old (AUC = 0.77, p < 0.001). NCIP was noted in 42.6% below 40-year-old age group compared to 84% above 40-year-old age group. The CT severity was significantly related to age and fatal outcome (p < 0.001). Anterior, centrilobular, hilar, apical, and middle lobe involvements had a significant relation to below 90% oxygen saturation. A significant negative correlation was found between CT severity and oxygen saturation (r = − 0.49, p < 0.001). Crazy-paving pattern, anterior aspect, hilar, centrilobular involvement, and moderate and severe stages had a statistically significant relation to higher mortality.ConclusionThe current study confirmed the value of CT as a prognostic predictor in NCIP through demonstration of the strong relation between CT severity and age, oxygen saturation, and the fatal outcome. In the era of COVID-19 pandemic, this study is considered to be an extension to other studies discussing chest CT features of COVID-19 in different age groups with demarcation of the relation of chest CT severity to different pattern and distribution of NCIP, age, oxygen saturation, and mortality rate.

Fear of Virus or of Competitors? The Decision Rationales of Financial Managers Under COVID-19.

This paper surveyed 422 financial managers before the number of novel coronavirus (COVID-19) infections in China peaked and used path analysis to study the risk decision-making mechanisms of financial managers. The study found that whether financial managers developed coping strategies depends on their assessment of potential business revenue losses. There are two transmission paths: the direct effect refers to the risk perception directly caused by COVID-19, while the indirect effect refers to managers' fear that they will not make timely adjustments or will make judgment errors, resulting in the loss of competitive advantage. It is worth noting that the indirect effect exceeds the direct effect, which indicates that financial managers are more rational than ordinary people in dealing with COVID-19, that they are relatively more concerned about competitor changes, and that they may even view COVID-19 as an important opportunity to obtain a better competitive position.

Predictive Value of Systemic Immune-Inflammation index and Neutrophil-to-Lymphocyte Ratio in Patients with Severe COVID-19.

Objective: It was initially reported that a novel coronavirus (COVID-19) had been identified in Wuhan, China, in December 2019.To date, COVID-19 is still threatening all humanity and has affected the public healthcare system and the world economic situation. Neutrophil-to-lymphocyte ratio (NLR) has also been demonstrated that associated with severity of COVID-19, but little is known about systemic immune-inflammation index (SII) relation with COVID-19. Methods: One hundred and twenty-five patients with diagnosed COVID-19 including non-severe cases (n = 77) and severe cases (n = 48) were enrolled in this study. Each patient of clinical characteristic information, blood routine parameters, and the haemogram-derived ratios were collected, calculated, and retrospectively analyzed. Receiver operating characteristics (ROC) was performed to investigate whether these parameters could be used to the predictive value of patients with severe COVID-19. Results: White blood cell count (WBC), neutrophil count (NEU), red cell volume distribution width (RDW), NLR, Platelet to lymphocyte ratio (PLR), neutrophil-to-platelet ratio (NPR), and SII were significantly higher in the severe groups than in the non-severe group (p < 0.01).Conversely, the severe group had a markedly decreased lymphocyte count, basophil (Baso#) count, red blood cell count (RBC), Hemoglobin (HGB), hematocrit (HCT), and lymphocyte-to-monocyte ratio (LMR) (P < 0.01).ROC curve analysis showed the AUC, optimal cut-off value, sensitivity, specificity of NLR and SII to early predict severe-patients with COVID-19 were 0.867, 7.25, 70.83%, 92.21% and 0.860, 887.20, 81.25%, 81.82%, respectively. Conclusion The results suggest that the SII and NLR is a potential new diagnosed biomarker in severe-patients with COVID-19.

The Impacts of Novel Coronavirus (COVID-19) Pandemic on Family Relations among Saudi Family Members

The current research aimed at investigating the psychological, social and economic impacts of Coronavirus (COVID-19) pandemic on family relations from parents’ viewpoints. In addition, it aimed at presenting proposed strategies to reduce the negative impacts of Coronavirus (COVID-19) pandemic on family relations. To achieve the research objectives, the researcher followed the descriptive analytical research design. The research instruments included a questionnaire designed to verify the most significant psychological, social and economic impacts, and the most effective proposed strategies. The questionnaire was administered to a sample of parents of some Saudi families. Results showed that there was a high percentage of agreement ranged between (50.86: 84.20) about the negative psychological impacts of Coronavirus (COVID-19) pandemic on family relations. Nevertheless, there was a high percentage of agreement ranged between (68.40: 85.93) about the positive social impacts of Coronavirus (COVID-19) pandemic on family relations, whereas there was a high percentage of agreement ranged between (68.40: 80.99) about the negative economic impacts of coronavirus (COVID-19) pandemic on family relations. This meant that the pandemic had significant negative psychological and economic impacts on family relations, whereas it had considerable positive social impacts. Additionally, all the proposed strategies to reduce the negative impacts of Coronavirus (COVID-19) pandemic on family relations indicated high percentage of agreement ranged between (80.74: 88.64). Furthermore, some recommendations were also presented, the most important of which is preparing group counseling programs to train all Family members, i.e. Parents and their children, on communication and problem-solving skills during Coronavirus pandemic. © 2022 NSP Natural Sciences Publishing Cor.

Impact of Artificial Intelligence in COVID-19 Pandemic: A Comprehensive Review

The goals of a health-care system are, to provide effective treatment with minimum cost and risk factors, delivery of medical services on time, and be ready to counter any emergency situation. To achieve these goals, a health-care system must be well prepared. The preparation is depending upon data, and the data scientists to analyze that data. Artificial Intelligence (AI) introduced a novelty in health-care, with its different tools which are built upon Machine Learning (ML) and Deep Learning (DL) algorithms. Besides clinical procedures and treatments, these algorithms are used for analyzing data and provides help in decision making. Similarly, to tackle this pandemic Novel Coronavirus disease 2019 (COVID-19) the computer scientists played their role individually and with the help of biological scientists to provide the solutions related to risk management (How much this pandemic can spread and affect the people), diagnosis of this disease with minimum time and cost, making vaccine and, suggesting that which medical treatment should adopt. © 2022 IEEE.

Assessing the Impact of Novel Coronavirus (COVID-19) on Renewable Energy Sector of India During the Lockdown

This paper presents the impact of coronavirus disease on the Renewable Energy (solar and wind) market of India. This study describes the impact on RE business over its five dimensions—continuity of operation, year on year (YOY) growth, securing financials, client and employee, and social responsibility. This commentary presents the effect on the implementation of upcoming projects, policies, and frameworks in 2020–21 are presented in detail with special emphasis on challenges faced by RE developers and off-grid companies, economic slowdown and government response and actions to mitigate the same. In the end, the paper presents possible measures and recommendations with a short-term and long-term vision, immediately aiming for safeguarding public health and gradually for the country’s economic revival and developing shock resilient RE sector. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The immediate impact of the 2019 novel coronavirus (COVID-19) outbreak on subjective sleep status

Background: An outbreak of the 2019 novel coronavirus (COVID-19) has been ongoing in China since January 2020. The threat of infection affects the work and life of most of the population and may also damage sleep. This study aims to examine the subjective sleep status and mental health of the population during the peak of the COVID-19 epidemic. Method: The datawere collected through an online questionnaire with a sample of 5461 individuals in China fromFebruary 5, 2020, to February 23, 2020. Participantswere divided into four groups based on their degree of threat fromCOVID-19:Group 1wasmost closely associatedwith COVID-19, including inpatients diagnosed with COVID-19, first-line hospital workers and first-line management staff;Group 2 included outpatients diagnosed with COVID-19 and patients who developed a fever and visited the hospital;Group 3 included people related to Group 1 or 2, such as their colleagues, relatives, friends and rescuers;and Group 4 was the farthest removed fromcontact with COVID-19, covering the general public affected by COVID-19 prevention strategies. The Insomnia Severity Index (ISI), Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7) and Acute Stress Disorder Scale (ASDS) were used. Results: Threat degree of COVID-19 (groups) had significant correlations with insomnia, depression, anxiety, and stress (p <0.05, p<0.01). Age, gender, and area (Hubei province or other provinces) had significant correlations with insomnia (p < 0.01). A total of 1380 (24.46%) participants were suspected of having major depression based on the PHQ-9. Additionally, 1042 (18.47%) participants were suspected of having generalized anxiety disorder based on the GAD-7. A total of 892 (15.8%) of the participants had Acute Stress Disorder (ASD) according to the ASDS. The prevalence of clinical insomnia during the outbreakwas 20.05% (1131) according to the ISI. The factors of satisfaction with the current sleep pattern and howperceptible the symptoms of the current sleep pattern are to other people (p < 0.05) and the middle (difficulty staying asleep) and terminal (waking up too early) (p < 0.01) factors of the ISI were significantly different across groups. A total of 1129 (20.01%) participants spent more than one hour awake in bed. Conclusion: The results indicated that insomnia is more severe in people who are female, young, living in the epicenter and experiencing a high degree of threat from COVID-19. As prevention and treatment efforts continue with regard to COVID-19, the general public has developed poor sleep hygiene habits, which deserve attention. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Asymptomatic and pre-symptoms transmission of covid-19 in heterogeneous epidemic network

The diversity of the spread pattern of the Corona virus is one of the most important reasons for the seriousness of the virus. Therefore, in this paper, we present a fractional mathematical SEIAS model that studies many ways of spreading (asymptomatic and pre-symptoms transmission) with the hypothesis of the spread of the virus in a heterogeneous network of individuals. The system consists of nonlinear equations which formed in fractional order. And it turns out that the system has two equilibrium positions (free and endemic positions). We also calculated the disease prevalence threshold (ℛ" ) within the network. The condition for the existence of the epidemiological situation has been determined. The stability of the free equilibrium position has been studied. The numerical part has been added to explain the proved theorems of the system in addition to clarifying the role of the heterogeneous network on the value of the virus spread threshold within the network. Keywords: Complex Networks, Novel Coronavirus (COVID-19), Asymptomatic and Pre-Symptoms Transmission, Basic. © 2022 NSP Natural Sciences Publishing Cor.

Electron beam irradiation on novel coronavirus (COVID-19): A Monte-Carlo simulation.

The novel coronavirus pneumonia triggered by COVID-19 is now raging the whole world. As a rapid and reliable killing COVID-19 method in industry, electron beam irradiation can interact with virus molecules and destroy their activity. With the unexpected appearance and quickly spreading of the virus, it is urgently necessary to figure out the mechanism of electron beam irradiation on COVID-19. In this study, we establish a virus structure and molecule model based on the detected gene sequence of Wuhan patient, and calculate irradiated electron interaction with virus atoms via a Monte Carlo simulation that track each elastic and inelastic collision of all electrons. The characteristics of irradiation damage on COVID-19, atoms' ionizations and electron energy losses are calculated and analyzed with regions. We simulate the different situations of incident electron energy for evaluating the influence of incident energy on virus damage. It is found that under the major protecting of an envelope protein layer, the inner RNA suffers the minimal damage. The damage for a ∼100-nm-diameter virus molecule is not always enhanced by irradiation energy monotonicity, for COVID-19, the irradiation electron energy of the strongest energy loss damage is 2 keV.

A fractional complex network model for novel corona virus in China.

As is well known the novel coronavirus (COVID-19) is a zoonotic virus and our model is concerned with the effect of the zoonotic source of the coronavirus during the outbreak in China. We present a SEIS complex network epidemic model for the novel coronavirus. Our model is presented in fractional form and with varying population. The steady states and the basic reproductive number are calculated. We also present some numerical examples and the sensitivity analysis of the basic reproductive number for the parameters.

Prevalence of and risk factors associated with sleep disturbances among HPCD exposed to COVID-19 in China.

OBJECTIVE: To assess sleep disturbances and associated factors among front-line healthcare providers who have been called upon for, dispatched (HPCD) and exposed to COVID-19 in China. METHODS: This cross-sectional, survey-based, isolation area-stratified study collected demographic data, sleep status and emotional measurements from 1036 HPCD in nine medical institutions from March 5 to 9, 2020 in Wuhan, China, which was the epicenter of the epidemic. HPCD who worked in isolation areas with COVID-19 were eligible for inclusion. The severity of symptoms of sleep disorders, insomnia and emotional self-efficacy were assessed by the Chinese versions of the 10-item Self-rating sleeping situation scale, the seven-item Insomnia Severity Index and the 12-item Regulatory emotional self-efficacy questionnaire, respectively. Univariate analysis was performed to identify factors associated with sleep disturbances. A structural equation model (SEM) was constructed via AMOS to explore the relationship among the four components. RESULTS: A total of 1036 out of 1075 contacted individuals completed the survey, with a participation rate of 96.4%. A total of 925 (89.3%) were aged 20-39 years, and 755 (72.9%) were women. Among all participants, 874 (84.4%) were nurses, and 162 (15.6%) were physicians; 538 (51.9%) worked in intensive care isolation units; 843 (81.4%) worked in isolation areas for 4 h straight, and 395 (38.1%) perceived COVID-19 peer exposure. A considerable proportion of participants reported symptoms of sleep disorders (543, 52.4%). Exposure status and length of work were the main factors affecting sleep status, which had indirect effects on sleep status by mediating regulatory emotional self-efficacy. CONCLUSIONS: In this survey of HPCD for patients with COVID-19 in China, participants reported experiencing sleep disturbance burdens, especially those having exposure experience and working long shifts. Regulatory emotional self-efficacy (RESE) is an important resource for alleviating sleep disturbances and improving sleep quality. These findings emphasize the importance of being prepared to support HPCD through psychological interventions.

The effect of Bacillus Calmette-Guérin (BCG) vaccination in preventing severe infectious respiratory diseases other than TB: Implications for the COVID-19 pandemic.

The rapid spread of the Coronavirus pandemic and its significant health and social impact urges the search for effective and readily available solutions to mitigate the damages. Thus, evaluating the effectiveness of existing vaccines like Bacillus Calmette-Guérin (BCG) has attracted attention. The aim of this review was evidence synthesis on the effect of BCG vaccine in preventing severe infectious respiratory disease including COVD-19, but not tuberculosis. We considered studies conducted on human participants of any study design from any country setting that were published in Enlgish. We did a systematic literature search in MEDLINE, Scopus and Google scholar databases and a free search on Google. The identified studies were appraised and relevant data were extracted using Joanna Briggs Institute tools. The extracted findings were synthesized with tables and narrative summary. Nine studies met the inclusion criteria. The findings indicated that BCG vaccine has a strong protective effect against both upper and lower acute respiratory tract infections. For instance in countries with universal BCG vaccination policy, the incidence of COVID-19 was lower compared to the counterparts. Addtionally, BCG vaccine was found to protect against infections like lethal influenza A virus, pandemic influenza (H1N1), and other acute respiratory tract infections. BCG improved the human body's immune response involving antigen-specific T cells and memory cells. It also induced adaptive functional reprogramming of mononuclear phagocytes that induce protective effects against different respiratory infections other than tuberculosis. In countries with universal BCG vaccination, the incidence and death from acute respiratory viral infection including COVID - 19 is significantly low. However, there is an urgent need for further evidence from well-designed studies to understand the possible role of BCG vaccination over time and across age groups, its possible benefits in special populations such as health workers and cost-savings related to a policy of universal BCG vaccination.

Exploration of CT manifestations of different clinical types of novel coronavirus pneumonia.

BACKGROUND: To explore computed tomography (CT) characteristics of the 2019 novel coronavirus (COVID-19) pneumonia and explore variations among the different clinical types. METHODS: Clinical and CT imaging data of 43 patients diagnosed with COVID-19 in our hospital and the cooperative hospital between January 15-30, 2020 were collected (27 male and 16 female). Patients were classified as common type (26 cases, 60%), severe type (14 cases, 33%) or critical type (three cases, 7%) according to the new coronavirus pneumonia treatment scheme (sixth edition). Patient clinical data and CT images were analyzed and evaluated. RESULTS: Fever was the main symptom in common type COVID-19 cases (23/26, 88.46%). Both severe and critical type COVID-19 patients had fever and cough symptoms, and dyspnea was observed in all three critical COVID-19 patients. CT manifestations in the common type COVID-19 cohort were bilateral involvement (20/26, 71%), multiple lesions (14/26, 54%), ground-glass density shadow (17/26, 65%), and some cases were accompanied by local consolidation (9/26, 35%), which is consistent with early stage COVID-19 CT performance. CT manifestations in the severe and critical types involved both lungs. Severe COVID-19 cases predominantly consisted of multiple mixed-density lesions (10/14, 71%), and a few patients showed diffuse lung glass density shadows in both lungs (4/14, 29%), which is consistent with the progression stage COVID-19 CT performance. Critical COVID-19 cases exhibited mixed-density lesions, and two cases displayed "white lung", which is the CT manifestation at the severe COVID-19 stage. Only one critical COVID-19 patient had pleural effusion. CONCLUSIONS: The CT manifestations of COVID-19 are specific and there are variations between different clinical types. Thus, CT is an important clinical tool for early diagnosis and assessment of the severity of COVID-19.

Epidemiological and clinical based study on four passages of COVID-19 patients: intervention at asymptomatic period contributes to early recovery.

BACKGROUND: With the worldwide spread of the 2019 novel coronavirus, scarce knowledge is available on the clinical features of more than two passages of patients. Further, in China, early intervention policy has been enacted since February. Whether early intervention contributes to swift recovery is still unknown. Hence, in this study, we focused on the patients from an isolated area, investigated the epidemiological and clinical characteristics of four serial passages of the virus. METHODS: From January 25 to February 29, 2020, all patient data on the SARS-CoV-2 passages in this isolated area were traced, and the patients were grouped according to the passaging of SARS-CoV-2. Clinical characteristics of patients, including laboratory, radiology, treatment and outcomes, were collected and analyzed. RESULTS: A total of 78 patients with four passages of virus transmission were included in this study. One patient transmitted SARS-CoV-2 to 8 patients (passage 2, P2), who next infected 23 patients (passage 3, P3), and then 46 patients (passage 4, P4). P2 received antiviral treatment when they had symptom, whereas P4 received antiviral treatment during their asymptomatic period. The incubation periods for P2, P3 and P4 patients were 7 days (IQR:2-12), 8 days (IQR:4-13) and 10 days (IQR:7-15), respectively. P2 patients showed lymphocytopenia (0.79 × 109/L), decreased lymphocyte percentages (12.15%), increased white blood cell count (6.51 × 109/L), increased total bilirubin levels (25% of P2 patients), increased C-reactive protein levels (100% of P2 patients) and abnormal liver function. By chest CT scans, all P2 patients (100%), 15 of P3 patients (65.22%) and 16 of P4 patients (34.78%) showed abnormality with typical feature of ground glass opacity. All of P2 patients (100%) received oxygen therapy, and in contrast, 19 of P4 patients (41.3%) received oxygen therapy. Further, significant decreased nucleic acid positive periods was found in P4 group (16 days, IQR: 10-23), compared with that of P2 group (22 days, IQR: 16-27). Moreover, the severity ratios were sharply decreased from 50% (P2 patients) to 4.35% (P4 patients), and the case fatality rate is zero. CONCLUSIONS: Judged from four passages of patients, early intervention contributes to the early recovery of COVID-19 patients.

[Anatomical pathology of novel coronavirus (COVID-19) infection. First impressions]. / Patologicheskaya anatomiya novoi koronavirusnoi infektsii COVID-19. Pervye vpechatleniya.

To date, descriptive results of a clinical and morphological study of novel coronavirus COVID-19 infection, mainly of the lungs, have appeared. However, in other organs, primarily in the cardiovascular system, there are substantial structural changes that lead to multiple organ dysfunction and contribute to death. OBJECTIVE: To analyze the thanatogenetic significance of novel coronavirus COVID-19 infection in different age and gender groups and to describe the main morphopathological manifestations in various organs. MATERIAL AND METHODS: The investigators carried out a comprehensive analysis of 700 autopsies of people disease from the novel coronavirus COVID-19 infection, which included an examination of gross changes reflected in the autopsy protocols and forensic medical examination reports, as well as that of microscopic changes detected during histological examination of organs. Immunohistochemistry (IHC) using mouse or rabbit antibodies to CD34, CD68, EMA, Ki67, caspase-3, and VEGF was employed in some observations. RESULTS: The novel coronavirus COVID-19 infection was the primary cause of death. Acute respiratory and pulmonary heart failure and multiple organ dysfunction became the leading thanatogenetic mechanisms in COVID-19. Cardiovascular disease, diabetes mellitus, and obesity were the most common diseases in patients with COVID-19. The most pronounced lung changes in COVID-19 were determined with a predominance of multiple total bilateral lesions of the lower lobes of the lungs, which was manifested by virus-induced changes in the parenchyma and stroma, as well as by microcirculation disorders. Acute dyscirculatory and ischemic changes in the parenchymal organs dominated in tissue damage caused by the virus. CONCLUSION: The changes in different organs of those who have died from the new coronavirus COVID-19 infection are stereotyped and include the manifestations of virus-induced action and a systemic inflammatory response with mainly microvasculature alteration, which leads to the development of coagulopathies and, accordingly, to total hypoxia.

Enhanced Gaussian process regression-based forecasting model for COVID-19 outbreak and significance of IoT for its detection.

Virus based epidemic is one of the speedy and widely spread infectious disease which can affect the economy of the country as well as it is life-threatening too. So, there is a need to forecast the epidemic lifespan, which can help us in taking preventive measures and remedial action on time. These preventive measures and corrective action may consist of closing schools, closing malls, closing theaters, sealing of borders, suspension of public services, and suspension of traveling. Resuming such restrictions is depends upon the outbreak momentum and its decay rate. The accurate forecasting of the epidemic lifespan is one of the enormously essential and challenging tasks. It is a challenging task because the lack of knowledge about the novel virus-based diseases and its consequences with complicated societal-governmental factors can influence the widespread of this newly born disease. At this stage, any forecasting can play a vital role, and it will be reliable too. As we know, the novel virus-based diseases are in a growing phase, and we also do not have real-time data samples. Thus, the biggest challenge is to find out the machine learning-based best forecasting model, which could offer better forecasting with the limited training samples. In this paper, the Multi-Task Gaussian Process (MTGP) regression model with enhanced predictions of novel coronavirus (COVID-19) outbreak is proposed. The purpose of the proposed MTGP regression model is to predict the COVID-19 outbreak worldwide. It will help the countries in planning their preventive measures to reduce the overall impact of the speedy and widely spread infectious disease. The result of the proposed model has been compared with the other prediction model to find out its suitability and correctness. In subsequent analysis, the significance of IoT based devices in COVID-19 detection and prevention has been discussed.

Generalized logistic growth modeling of the COVID-19 outbreak: comparing the dynamics in the 29 provinces in China and in the rest of the world.

Started in Wuhan, China, the COVID-19 has been spreading all over the world. We calibrate the logistic growth model, the generalized logistic growth model, the generalized Richards model and the generalized growth model to the reported number of infected cases for the whole of China, 29 provinces in China, and 33 countries and regions that have been or are undergoing major outbreaks. We dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogeneous situations across provinces. The extreme containment measures implemented by China were very effective with some instructive variations across provinces. Borrowing from the experience of China, we made scenario projections on the development of the outbreak in other countries. We identified that outbreaks in 14 countries (mostly in western Europe) have ended, while resurgences of cases have been identified in several among them. The modeling results clearly show longer after-peak trajectories in western countries, in contrast to most provinces in China where the after-peak trajectory is characterized by a much faster decay. We identified three groups of countries in different level of outbreak progress, and provide informative implications for the current global pandemic.

Potential risk factors for case fatality rate of novel coronavirus (COVID-19) in China: A pooled analysis of individual patient data.

BACKGROUND AND OBJECTIVE: Since the first case of the pneumonia caused by 2019 novel coronavirus (COVID-19) is found in Wuhan, there have been more than 70,000 cases reported in China. This study aims to perform the meta-analysis of risk factors for the case fatality rate (CFR) of the 2019 novel coronavirus (COVID-19). DESIGN AND METHODS: We have searched PubMed, Google scholar and medRxiv for the cohort studies involving risk factors for the CFR of COVID-19. This meta-analysis compares the risk factors of CFR between fatal patients and non-fatal patients. RESULTS: Two cohort studies are included in this study. After comparing the patients between fatal cases and non-fatal cases, several important factors are found to significantly increase the CFR in patients with COVID-19, and include the age ranging 60-70 (OR = 1.85; 95% CI = 1.62 to 2.11; P < .00001) and especially≥70 (OR = 8.45; 95% CI = 7.47 to 9.55; P < .00001), sex of male (OR = 1.88; 95% CI = 1.30 to 2.73; P = .0008), occupation of retirees (OR = 4.27; 95% CI = 2.50 to 7.28; P < .00001), and severe cases (OR = 691.76; 95% CI = 4.82 to 99,265.63; P = .01). As the advancement of early diagnosis and treatment, the CFR after January 21 (or 22), 2020 is substantially decreased in COVID-19 than before (OR = 0.21; 95% CI = 0.19 to 0.24; P < .00001). CONCLUSIONS: Several factors are confirmed to significantly improve the CFR in patients with COVID-19, which is very important for the treatment and good prognosis of these patients.

Antiviral properties of placental growth factors: A novel therapeutic approach for COVID-19 treatment.

The current challenge of the COVID-19 pandemic is complicated by the limited therapeutic options against the virus, with many being anecdotal or still undergoing confirmatory trials, underlining the urgent need for novel strategies targeting the virus. The pulmotropic virus causes loss of oxygenation in severe cases with acute respiratory distress syndrome (ARDS) and need for mechanical ventilation. This work seeks to introduce placental extract-derived biologically active components as a therapeutic option and highlights their mechanism of action relevant to COVID-19 virus. Human placenta has been used in clinical practice for over a century and there is substantial experience in clinical applications of placental extract for different indications. Aqueous extract of human placentacontains growth factors, cytokines/chemokines, natural metabolic and other compounds, anti-oxidants, amino acids, vitamins, trace elements and biomolecules, which individually or in combination show accelerated cellular metabolism, immunomodulatory and anti-inflammatory effects, cellular proliferation and stimulation of tissue regeneration processes. Placental extract treatment is proposed as a suitable therapeutic approach consideringthe above properties which could protect against initial viral entry and acute inflammation of alveolar epithelial cells, reconstitute pulmonary microenvironment and regenerate the lung. We reviewed useful therapeutic information of placental biomolecules in relation to COVID-19 treatment. We propose the new approach of using placental growth factors, chemokines and cytokine which will execute antiviral activity in coordination with innate and humoral immunity and improve patient's immunological responses to COVID-19. Executing a clinical trial using placental extract as preventive, protective and/or therapeutic approach for COVID-19treatment could advance the development of a most promising therapeutic candidate that can join the armamentaria against the COVID-19 virus.

Moving Average Based Index for Judging the Peak of the COVID-19 Epidemic.

A pneumonia outbreak caused by a novel coronavirus (COVID-19) has spread around the world. A total of 2,314,621 laboratory-confirmed cases, including 157,847 deaths (6.8%) were reported globally by 20 April 2020. Common symptoms of COVID-19 pneumonia include fever, fatigue, and dry cough. Faced with such a sudden outbreak of emerging infectious disease, traditional models for predicting the peak of the epidemic often show inconsistent results. With the aim to timely judge the epidemic peak and provide support for decisions for resuming production and returning to normal life based on publicly reported data, we used a seven-day moving average of log-transformed daily new cases (LMA) to establish a new index named the "epidemic evaluation index" (EEI). We used SARS epidemic data from Hong Kong to verify the practicability of the new index, and then applied it to the COVID-19 epidemic analysis. The results showed that the epidemic peaked, respectively, on 9 February and 5 February 2020, in Hubei Province and other provinces in China. The proposed index can be applied for judging the epidemic peak. While the global COVID-19 epidemic reached its peak in the middle of April, the epidemic peaks in some countries have not yet appeared. Global and united efforts are still needed to eventually eliminate the epidemic.