An intelligent platform of services based on multimedia understanding and telehealth for supporting the management of SARS-CoV-2 multi-pathological patients

The combination of pervasive sensing and multimedia understanding with the advances in communications makes it possible to conceive platforms of services for providing telehealth solutions responding to the current needs of society. The recent outbreak has indeed posed several concerns on the management of patients at home, urging to devise complex pathways to address the Severe Acute Respiratory Syndrome (SARS) in combination with the usual diseases of an increasingly elder population. In this paper, we present TiAssisto, a project aiming to design, develop, and validate an innovative and intelligent platform of services, having as its main objective to assist both Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) multi-pathological patients and healthcare professionals. This is achieved by researching and validating new methods to improve their lives and reduce avoidable hospitalisations. TiAssisto features telehealth and telemedicine solutions to enable high-quality standards treatments based on Information and Communication Technologies (ICT), Artificial Intelligence (AI) and Machine Learning (ML). Three hundred patients are involved in our study: one half using our telehealth platform, while the other half participate as a control group for a correct validation. The developed AI models and the Decision Support System assist General Practitioners (GPs) and other healthcare professionals in order to help them in their diagnosis, by providing suggestions and pointing out possible presence or absence of signs that can be related to pathologies. Deep learning techniques are also used to detect the absence or presence of specific signs in lung ultrasound images. © 2022 IEEE.

COVID-19 Identification From Lung CT Scans in a Low-Resource Setting Using a Regularized 3D Convolutional Neural Network

Right at the end of 2019, the world saw an outbreak of a new type of SARS (severe acute respiratory syndrome) disease, SARS-Cov-2, or COVID-19. Even in 2022, around 1 million people worldwide are getting infected with the virus every day. To date, more than 6 million people have died as a result of the virus. To tackle the pandemic, the first step is to successfully detect the virus among the mass population. The most popular method is the RT-PCR test, which, unfortunately, is not always conclusive. The physicians thus suggest lung CT tests for the patients for clinical relevance. But the problem with lung CT scans for the detection of coronavirus is that the COVID-19 infected scan is very similar to community-affected pneumonia (CAP) infected scan, and the results in many cases get wrongly interpreted. In addition, the virus is always mutating into different strains, and the severity and infection pattern slightly change with each mutation. Because of this rapid mutation, a large and balanced dataset of lung CT scans is not always available. In this work, we systematically evaluate the accuracy of a deep 3D convolutional neural network (CNN) on a small-scale and highly imbalanced dataset of lung CT scans (the SPGC COVID 2021 dataset). Our experiments show that it can outperform previous state-of-the-art 3D CNN models with proper regularization, an appropriate number of dense layers, and a weighted loss function. Our research, therefore, suggests an effective solution for identifying COVID-19 in lung CT scans using deep learning for small and highly imbalanced datasets. © 2022 IEEE.

A Genomic Signal Processing-Based Coronavirus Classification Model Using Deep Learning with Web-Based Console

Various strains of Coronavirus have led to numerous deaths worldwide with CoViD-19 being the most recent. Hence, the need for various research studies to determine and develop technologies that would reduce the spread of this virus as well as aid in the early diagnosis of the disease. The Severe Acute Respiratory Syndrome CoV (SARS-CoV), which emerged in 2003, Middle East Respiratory Syndrome CoV (MERS-CoV) in 2012 and Severe Acute Respiratory Syndrome CoV 2 (SARS-CoV-2) which is generally regarded as CoViD-19, in 2019 have very similar symptoms and genetics. Without proper diagnosis of these strains, they may be mistaken for one another. Therefore, there is a need to distinguish CoViD-19 from the other two Coronaviruses to enhance prompt and specific treatment. In this study, we developed a deep learning model with a web console for the classification of genomic sequences of the three Coronavirus strains using genomic signal processing. The DNA sequences harvested from the Virus Pathogen Database and Analysis Resource (ViPR) was used as dataset and these sequences were transformed to RGB images using Voss and Z-curve encodings. A convolutional neural network (CNN) model was consequently used for classification and incorporated in a web application platform developed with the Django framework. The results of the transformation of the images highlights the similarities of the three coronaviruses in terms of visual and genetic characteristics with the CNN model distinctly classifying SARS-CoV-2, SARS-CoV and MERS-CoV with a training and validation accuracies of 95.58% and 85% respectively which compares favourably with other results in the literature. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Synthesis Review of Vitamins Involved in the Fight against Covid-19

Although literature studies on earlier viruses such as the Severe Acute Respiratory Syndrome (SARS), the Middle East Respiratory Syndrome (MERS), and other similar viruses, in terms of treatment of coronavirus suggested the repurposing of some antiviral drugs, some Covid-19 specific treatments, general forms of treatments, the use of convalescent plasma, as well as nutritional interventions in the form of vitamins, it is imperative to interrogate the nutritional status, age, and comorbidities of each infected patient before receiving any form of treatment. In the absence of any conclusive treatment so far, the study encourages the use of all likely interventions that could help arrest the spread of the disease. In addition, the current study has a particular interest in the syntheses and applications of vitamins and their derivatives which have been touted to play a significant role in the fight against Covid-19, namely, vitamins A–E. It must, however, be mentioned that literature is not comprehensive. © 2023 Wiley-VCH GmbH.

An assessment on Air Quality in various Polluted Industrialized states of India due to COVID-19

Coronavirus disease 2019 (SARS-CoV-2) is an infectious disease which is caused by the severe acute respiratory syndrome (SARS) coronavirus. It was discovered in the city of Wuhan, China in late December 2019 and was later declared as a pandemic by the World Health Organization (WHO). The first case in India was reported in Kerala state when the affected person had returned from China. As a result, cases started increasing readily to all the surrounding states due to unprotected contact. In this regard, India imposed various lockdown measures to keep the spread of the disease under control by restricting people gatherings. These lockdown measures improved considerably in the air quality of the states/cities, especially in polluted industrial states, and turned out to be an important benefit. This study aims to assess and compare the impact of major air quality parameters (PM2.5, PM10, CO, NOx, Ozone) on Four major polluted Industrial states of India (Gujarat, Rajasthan, Maharashtra and Uttar Pradesh). The timeline taken for this study is taken for three phases namely: Pre-Covid (March to June of 2019);The strongly affected months of wave 1 of Covid (March to June of 2020) and wave 2 of Covid (March to June of 2021). The results highlighted the following trends during the three phases considered in this study. PM 2.5 showed a reduction of almost 35.65 percent during wave 1 and showed an increase of 7.5 percent during wave 2. PM 10 showed a reduction of almost 38.94 percent during wave 1 and showed an increase of 1.25 percent during wave 2. NOx showed a reduction of almost 54.92 percent during wave 1 and showed a reduction of 3.1 percent during wave 2. CO showed a reduction of almost 26.96 percent during wave 1 and showed a reduction of 7.38 percent during wave 2. Ozone showed a reduction of almost 16.76 percent during wave1 and showed a reduction of 38.5 percent during wave 2. © 2022 IEEE.

Characteristics and Predictive Value of T-lymphocyte Subset Absolute Counts in Patients with COVID-19-associated Acute Respiratory Failure: A Retrospective Study.

Background: Of the factors influencing severity and outcomes following coronavirus disease-2019 (COVID-19), cellular immune response has a strong impact. The spectrum of response varies from over-activation to hypo-functioning. The severe infection leads to reduction in numbers and dysfunction of T-lymphocytes/subsets. Patients and methods: This retrospective, single-center study aimed to analyze the expression of T-lymphocyte/subsets by flow cytometry and inflammation-related biomarker, serum ferritin in real-time polymerase chain reaction (RT-PCR) positive patients. According to oxygen requirements, patients were stratified into nonsevere (room air, nasal prongs, and face mask) and severe [nonrebreather mask (NRBM), noninvasive ventilation (NIV), high-flow nasal oxygen (HFNO), and invasive mechanical ventilation (IMV)] subgroups for analysis. Patients were classified into survivors and nonsurvivors. Mann-Whitney U test was used to analyze differences in T-lymphocyte and subset values when classified according to gender, the severity of COVID, outcome, and prevalence of diabetes mellitus (DM). Cross tabulations were computed for categorical data and compared using Fisher's exact test. Spearman correlation was used to analyze the correlation of T-lymphocyte and subset values with age or serum ferritin levels. p <0.05 values were considered to be statistically significant. Results: A total of 379 patients were analyzed. Significantly higher percentage of patients with DM were aged ≥61 years in both nonsevere and severe COVID groups. A significant negative correlation of CD3+, CD4+, and CD8+ was found with age. CD3+ and CD4+ absolute counts were significantly higher in females as compared to males. Patients with severe COVID had significantly lesser total lymphocyte (%), CD3+, CD4+, and CD8+ counts as compared to those with nonsevere COVID (p <0.05). T-lymphocyte subsets were reduced in patients with severe disease. A significant negative correlation of total lymphocyte (%), CD3+, CD4+, and CD8+ counts was found with serum ferritin levels. Conclusions: T-lymphocyte/subset trends are an independent risk factor for clinical prognosis. Monitoring may help in intervening in patients with disease progression. How to cite this article: Vadi S, Pednekar A, Suthar D, Sanwalka N, Ghodke K, Rabade N. Characteristics and Predictive Value of T-lymphocyte Subset Absolute Counts in Patients with COVID-19-associated Acute Respiratory Failure: A Retrospective Study. Indian J Crit Care Med 2022;26(11):1198-1203.

Evaluation of blood glucose levels of COVID-19 patients before and after recovery regardless of their diabetic status: A retrospective cohort study

Background: Blood glucose level is an important risk factor for the prognosis of infection and critically ill patients. Stress-induced hyperglycemia is well-known as an adaptive response and expected during times of infection. However, this is believed to be a transient response that resolves upon the improvement of the infection. Aim: The aim of this study is to evaluate the blood glucose levels in a cohort of COVID-19 patients to determine their hyperglycemic status before and after the recovery regardless of their diabetic status. Methodology: This is a multicenter, retrospective, observational study. A detailed case history including investigations and laboratory findings was taken from the recovered COVID-19 patients. Data of their random blood sugar levels before and after COVID-19 recovery were collected and compared to check for their hyperglycemic status after the recovery. Data were then tabulated in the spreadsheet and statistical analysis was done. Results: In our study, we compared the hyperglycemic status after the recovery. About 22.1% had hyperglycemia post-COVID. During COVID, the prevalence of hyperglycemia in patients was 23% with or without a previous history of diabetes. Altogether, there was a significant increase in Blood Glucose levels post-COVID (2-month follow-up) period. A significant P (P = 0.0001) was found in the statistical analysis. Conclusion: Clinicians must recognize that some patients may require monitoring the glycemic status and intensification of the antihyperglycemics for several weeks to months after infection devoid of their diabetic status. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

A review on newer detection technologies for the diagnosis of COVID-19 infection

COVID-19 is a sickness brought about by coronavirus responsible for causing simple to extreme complications in people. COVID-19 first case was seen in Wuhan, Hubei Province, China, on December, 2019. The World Health Organization (WHO) to pronounce it as a worldwide pandemic on March 11, 2020, as the pandemic has spread quickly all through the world. Regardless of extensive endeavors made to contain the infection, the infection has proceeded with its pervasiveness in numerous nations with changing levels of clinical signs. Henceforth, in this report, we discuss the various strategies, for example, serological and nucleic acid-based procedures which are accessible for the determination and successful counteraction of coronavirus. With expanding the rate of coronavirus cases, the precise and early identification of the COVID-19 is the need of great importance for viable avoidance with treatment and just as to check its spread. Reverse transcriptase-real time polymerase chain reaction (PCR) measures are viewed as the highest quality level for the early identification of infection. This diagnostic technique is being utilized worldwide with recommendations from WHO and Center for Disease Control and Prevention. Reverse transcriptase real-time quantitative PCR (RT-qPCR) is being done compulsory before any medical procedures and major surgeries for early detection, prevention, and management in due time course. Rapid antigen test is also a screening test used widely in hospitals for screening of COVID-19 and before the admission in hospitals. Other nucleic acid amplification test widely done for the detection of COVID-19 are RT-qPCR, next-generation sequencing, clustered regularly interspaced short pallindromic repeats, reverse transcription -loop-mediated isothermal amplification, droplet digital PCR. Some immunological tests are lateral flow, ELISA. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Intelligent Approach for Clustering Mutations’ Nature of COVID-19 Genome

In December 2019, a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology pneumonia. The outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9, 2020, named Novel Coronavirus 2019 (nCoV-2019). This nCoV-2019 is now known as COVID-19. There is a big list of infections of this coronavirus which is present in the form of a big family. This virus can cause several diseases that usually develop with a serious problem. According to the World Health Organization (WHO), 2019-nCoV has been placed as the modern generation of Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) coronaviruses, so COVID-19 can repeatedly change its internal genome structure to extend its existence. Understanding and accurately predicting the mutational properties of the genome structure of COVID-19 can form a good leadership role in preventing and fighting against coronavirus. In this research paper, an analytical approach has been presented which is based on the k-means cluster technique of machine learning to find the clusters over the mutational properties of the COVID-19 viruses’ complete genome. This method would be able to act as a promising tool to monitor and track pathogenic infections in their stable and local genetics/hereditary varieties. This paper identifies five main clusters of mutations with k = 5 as best in most cases in the coronavirus that could help scientists and researchers develop disease control vaccines for the transformation of coronaviruses. © 2022 Tech Science Press. All rights reserved.

Interplay of Influenza A/B Subtypes and COVID-19

Influenza, or most commonly termed the flu, is a common respiratory illness caused by viral infection. The circulation of this virus is found year-round but is more common during the flu season: fall and winter. In the United States, the number of reported cases begins to rise in October, reaches a peak in December, and returns to normal in April. Even though there are four subtypes of the Influenza virus, the seasonal flu outbreaks in humans are caused by type A and B viruses. eVision utilizes influenza data provided by the United States Center for Disease Control and Prevention (CDC) and the World Health Organization (WHO) to analyze influenza A and B cases throughout the flu season. During the 2019-20 flu season, the positive influenza cases reported in the US were between 36 and 56 million, which is the highest over the past six years. However, during the 2020-21 flu season which is the first complete flu season within the COVID-19 pandemic, the reported flu cases reduced drastically to 1,899;of which 713 were caused by influenza A viruses, and 1,186 by influenza B viruses. This indicates that the number of flu B cases was higher than that of flu A which was not normally the case prior to the COVID-19 pandemic. It was further observed that flu B reached its peak either at the same time or earlier than flu A which is also unusual compared to the flu trends prior to the onset of the COVID-19 pandemic. This peculiar trend is also noted during the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003. This paper reports the findings on deviation in the Influenza type A and type B trends during the circulation of Coronavirus in the US and Canada and provides possible reasons for these changes. © 2021 IEEE.

COVID-19, An early investigation from exposure to treatment outcomes in Tehran, Iran.

BACKGROUND: There is a growing need for information regarding the recent coronavirus disease of 2019 (COVID-19). We present a comprehensive report of COVID-19 patients in Iran. MATERIALS AND METHODS: One hundred hospitalized patients with COVID-19 were studied. Data on potential source of exposure, demographic, clinical, and paraclinical features, therapy outcome, and postdischarge follow-up were analyzed. RESULTS: The median age of the patients was 58 years, and the majority of the patients (72.7%) were above 50 years of age. Fever was present in 45.2% of the patients on admission. The most common clinical symptoms were shortness of breath (74%) and cough (68%). Most patients had elevated C-reactive protein (92.3%), elevated erythrocyte sedimentation rate (82.9%), and lymphocytopenia (74.2%) on admission. Lower lobes of the lung were most commonly involved, and ground-glass opacity (81.8%) was the most frequent finding in computed tomography scans. The administration of hydroxychloroquine improved the clinical outcome of the patients. Lopinavir/ritonavir was efficacious at younger ages. Of the 70 discharged patients, 40% had symptom aggravation, 8.6% were readmitted to the hospital, and three patients (4.3%) died. CONCLUSION: This report demonstrates a heterogeneous nature of clinical manifestations in patients affected with COVID19. The most common presenting symptoms are nonspecific, so attention should be made on broader testing, especially in age groups with the greatest risk and younger individuals who can serve as carriers of the disease. Hydroxychloroquine and lopinavir/ritonavir (in younger age group) can be potential treatment options. Finally, patients discharged from the hospital should be followed up because of potential symptom aggravation.

Management of children with glucose-6-phosphate dehydrogenase deficiency presenting with acute haemolytic crisis during the SARs-COV-2 pandemic.

BACKGROUND AND OBJECTIVES: Shortage of blood during the severe acute respiratory syndrome-COV-2 (SARs-COV-2) pandemic impacted transfusion practice. The primary aim of the study is to assess management of acute haemolytic crisis (AHC) in glucose-6-phosphate dehydrogenase(G6PD)- deficient children during SARs-COV-2 pandemic, and then to assess blood donation situation and the role of telemedicine in management. METHODS: Assessment of G6PD-deficient children attending the Emergency Department (ER) with AHC from 1 March 2020 for 5 months in comparison to same period in the previous 2 years, in three paediatric haematology centres. AHC cases presenting with infection were tested for SARs-COV-2 using RT-PCR. Children with Hb (50-65 g/L) and who were not transfused, were followed up using telemedicine with Hb re-checked in 24 h. RESULTS: A 45% drop in ER visits due to G6PD deficiency-related AHC during SARs-COV-2 pandemic in comparison to the previous 2 years was observed. 10% of patients presented with fever and all tested negative for COVID-19 by RT-PCR. 33% of patients had Hb < 50 g/L and were all transfused. 50% had Hb between 50 and 65 g/L, half of them (n = 49) did not receive transfusion and only two patients (4%) required transfusion upon follow up. A restrictive transfusion strategy was adopted and one of the reasons was a 39% drop in blood donation in participating centres. CONCLUSION: Fewer G6PD-deficient children with AHC visited the ER during SARs-COV-2 and most tolerated lower Hb levels. Telemedicine was an efficient tool to support their families. A restrictive transfusion strategy was clear in this study.

Central Retinal Vein Occlusion in a Young Healthy COVID-19 Patient: A Case Report and Literature Review.

Coronavirus disease (COVID-19) has been declared by the World Health Organization as a pandemic on March 11, 2020. COVID-19 predispose patients to multisystem thromboembolic events, including pulmonary emboli and deep vein thrombosis. We report a 33-year-old previously healthy man, with previous history of COVID-19 infection presented with left eye central retinal vein occlusion (CRVO) with secondary macular edema. All possible risk factors for thromboembolic events were excluded. After a single dose of intravitreal injection of aflibercept (2 mg in 0.05 ml), gradual improvement in the clinical manifestation of CRVO with complete resolution of macular edema in the left eye was observed. To the best of our knowledge, this is the first report of CRVO post-COVID-19 in Oman.

A Systematic Review on the Therapeutic Relevance of Hydroxychloroquine/Chloroquine in the Management of COVID-19.

BACKGROUND: The coronavirus disease-2019 (COVID-19) pandemic is coming to the fore and has surfaced as a public health emergency of international concern. The lack of vaccines or an effective treatment has led to the global hunt for potential pharmaceuticals in adequately managing this disease. This systematic review highlights the efficacy of chloroquine and its derivative hydroxychloroquine in the treatment of COVID-19 and also explores the safety profile of these drugs. METHODS: EMBASE, COCHRANE, and PubMed databases were searched for studies on the use of hydroxychloroquine or chloroquine in the treatment of COVID-19. RESULTS: Twenty articles were selected including expert opinions, National Guidelines, three small randomized controlled trials, and one prospective study. Both hydroxychloroquine and chloroquine have shown promising results including reduction in hospital length of stay and overall mortality. Moreover, concomitant use with azithromycin seems to reduce viral load to a greater extent. CONCLUSIONS: Considering the known safety profile of these drugs in the treatment of other diseases, their availability and affordability, chloroquine and hydroxychloroquine are potential antiviral agents in the treatment of COVID-19. However, reported side effects of these drugs when used in conjunction with azithromycin in patients with comorbidities have raised significant safety concerns. High-quality randomized clinical trials are warranted to provide more comprehensive evidence of the safety of these drugs in patients infected with COVID-19.

Coronavirus management and control: Nutrition and alternative medicines.

Background: In late December 2019, the outbreak of COVID-19 caused by the coronavirus severe acute respiratory syndrome-CoV-2, originated in Wuhan Province, the People's Republic of China (PRC). The rapid and highly infectious virus quickly spread around the country and has become a global pandemic. Thousands of people have been infected, and have died. Scientists around the world are working on the vaccine; however, an effective cure is yet to be developed. Aims: Search to be made on some alternative antiviral components from the rich sources of traditional herbal medicine in India as well as in the PRC. Here we discuss them with references. Methods: The knowledge gained from the literature search of antiviral known herbal products or Ayurvedic medicines that used to be applied against any viral or bacterial infections in the past, may be considered for deployment against COVID-19, and may be rewarded. Results: Many medicinal compounds are extracted from plants and have led to drug discovery. Similarly, plant products and their analogues have been employed as an early line of defense against COVID-19. Conclusion: Research into ethnobotany, phytochemistry, plant physiology and ecology may be important in protecting the global population from current and future pandemics.

Resuming elective paediatric surgical procedures in the era of COVID-19.

BACKGROUND: The novel coronavirus and the disease it causes COVID-19, like other viral outbreaks, have an unpredictable timeline. Therefore, a triumph in the battle against COVID-19 could only be achieved if a health care system's capacity to support a potentially overwhelming increase in critical patient care needs is maintained, and the viral curve is flattened. Accordingly, health care bodies around the globe called upon prioritising appropriate resource allocation as it relates to elective invasive procedures and minimising the use of essential items required to care for patients. The unpredictability COVID-19 timeline in the absence of effective drug treatments and vaccination along with the restrictive health care policies implemented suggest that patients may be deprived of access to needed surgical care, likely for many months. However, the potential undue delay in delivering essential elective surgical care may have a more detrimental impact on patients' health compared to that of COVID-19 itself. This particularly applies to the paediatric population in which infection rates have been demonstrated to be considerably lower and mortalities have not been reported yet. Therefore, the need emerges for actions to be taken that allow for the resumption of essential elective surgical procedures in this population of patients. MATERIALS AND METHODS: A comprehensive search through surgical guidance and recommendations to develop a set of evidence based recommendations that allow for the safe and timely delivery of essential paediatric surgical care during the time of COVID-19. CONCLUSION: No compelling evidence that the paediatric population is at an increased risk of morbidity or mortality exists. Therefore, delaying essential paediatric surgical care cannot be justified as it may have a potentially negative health impact, and continuous refinements of surgical recommendations are encouraged in view of evolving circumstances.

Bibliometric analysis of coronavirus disease (COVID-19) literature published in Web of Science 2019-2020.

Coronavirus outbreak in Wuhan, China, turned into a pandemic in record time. Communication of disease presentation and mechanism of spread remain keys to getting ahead of the virus and limiting its spread beyond the capacity of management. Owing to huge academic focus and pandemic concern around the globe, this bibliometric analysis investigated research productivity related to coronavirus disease (COVID-19) pandemic using the Web of Science database. The relevant data were harvested, and search query was further refined by publication years (2020 OR 2019) and document types (article, book chapter, and proceedings paper). Finally, 6694 records were imported and downloaded in Plaintext and BibTeX formats on August 1, 2020. The data analysis was performed using MS Excel, VOS viewer, and Biblioshiny software. Of the 6694 publications that appeared in that period, the USA and Chinese research institutions topped the numbers. At the same time, the Journal of Medical Virology and CUREUS (Cureus Journal of Medical Science), remained favorite journals for publications. The pattern of multi-author publications has outstripped that of single-authors. Apart from COVID-19 and the novel coronavirus, the important keywords mentioned included pandemic, pneumonia, epidemiology, public health, outbreak, epidemic, China, infection, and treatment. The analysis shows a strong local research response from China, with large teams reporting on the disease outbreak. Subsequent studies will document a global response as the virus spreads worldwide. The initial research related to the current coronavirus outbreak was reported from within China. The data and patterns were supposed to alter as the virus spread globally.

The Clinical Characteristics and Risk Factors of Severe COVID-19.

OBJECTIVE: We aim to investigate the clinical characteristics and risk factors for the severe cases of coronavirus disease 2019 (COVID-19) in comparison with the non-severe patients. METHODS: We searched PubMed, EMBASE, Web of Science, and CNKI to collect all relevant studies published before July 26, 2020, and a total of 30 papers were included in this meta-analysis. RESULTS: In the severe COVID-19 patients, 60% (95% CI = 56-64%) were male, 25% (95% CI = 21-29%) were over 65 years old, 34% (95% CI = 24-44%) were obese, and 55% (95% CI = 41-70%) had comorbidities. The most prevalent comorbidities were hypertension (34%, 95% CI = 25-44%), diabetes (20%, 95% CI = 15-25%), and cardiovascular disease (CVD; 12%, 95% CI = 9-16%). The most common blood test abnormalities were elevated C-reactive protein (CRP; 87%, 82-92%), decreased lymphocyte count (68%, 58-77%), and increased lactate dehydrogenase (69%, 95% CI = 57-81%). In addition, abnormal laboratory findings revealing organ dysfunctions were frequently observed in the severe cases, including decrease in albumin (43%, 95% CI = 24-63%) and increase in aspartate aminotransferase (47%, 95% CI = 38-56%), alanine aminotransferase (28%, 95% CI = 16-39%), troponin I/troponin T (TnI/TnT; 29%, 95% CI = 13-45%), and serum Cr (SCr; 10%, 95% CI = 5-15%). CONCLUSION: The male, elderly and obese patients and those with any comorbidities, especially with hypertension, diabetes, and CVD, were more likely to develop into severe cases. But the association between hypertension, diabetes, CVD, and severity of COVID-19 was declined by the increase of age. A significant elevation in cardiac TnI/TnT, the hepatic enzymes, and SCr and the reduction in lymphocytes with elevated CRPs are important markers for the severity. Specific attention should be given to the elderly male and obese patients and those with indications of severe immune injury in combination with bacterial infection and indication of multi-organ dysfunction or damages.

Comparison of two real-time polymerase chain reaction assays for the detection of severe acute respiratory syndrome-CoV-2 from combined nasopharyngeal-throat swabs.

CONTEXT: In the absence of effective treatment or vaccine, the current strategy for the prevention of further transmission of severe acute respiratory syndrome (SARS) CoV-2 (COVID-19) infection is early diagnosis and isolation of cases. The diagnosis of SARS-CoV-2 is done by detecting viral RNA in the nasopharyngeal and throat swabs by real-time polymerase chain reaction (PCR). Many commercial assays are now available for performing the PCR assay. AIMS: The aim was to evaluate the performance of the SD Biosensor nCoV real-time detection kit with the real-time PCR kit provided by the Indian Council of Medical Research-National Institute of Virology (ICMR-NIV), Pune (NIV Protocol). SUBJECTS AND METHODS: A total of 253 pairs of nasopharyngeal-oropharyngeal swabs combined in a single viral transport medium were tested for viral RNA by both the protocols. The sensitivity and specificity of the SD Biosensor were calculated considering the ICMR-NIV kit as the gold standard. Matched pairs of recorded cycle threshold values (Ct values) were compared by Pearson's correlation coefficient. RESULTS: Concordant COVID-19 negative and positive PCR results were reported for 113 and 77 samples, respectively. The SD Biosensor kit additionally detected 62 cases, which were found negative by the NIV protocol. In all discordant positive results by the SD Biosensor kit, the average Ct values were higher than the concordant positive results. A total of forty samples tested positive for E gene by SD Biosensor and having Ct values <25 had 100% concordance with NIV protocol results and 39 samples tested positive for E gene by SD Biosensor having Ct value >32 were all found negative by the NIV protocol. CONCLUSIONS: The results highlight the need for careful evaluation of commercial kits before being deployed for screening of COVID-19 infections.

Initial Viral Load of a COVID-19-Infected Case Indicated by its Cycle Threshold Value of Polymerase Chain Reaction Could be used as a Predictor of its Transmissibility - An Experience from Gujarat, India.

BACKGROUND: Transmission dynamics of the infectious disease Corona Virus Disease - 19 (COVID-19) is yet to be understood fully. The study aimed at exploring whether quantitative viral load of COVID-19-infected case indicated by cycle threshold (Ct) value of real-time reverse transcription polymerase chain reaction could predict about transmission pattern in the community. MATERIALS AND METHODS: An observational study was conducted involving 1976 individuals, suspected to be suffering from COVID-19 and contacts, of laboratory confirmed cases from selected districts of Gujarat, India. A total of 138 persons were detected to be positive. Weekly positivity showed an overall increasing trend during the studied weeks. It was observed that only 7% had high, 9% as moderate and rest, 84% had low viral load based on Ct values of real-time RT-PCR. RESULTS: Most secondary cases clustered around index cases with high viral load whereas fewer secondary cases clustered around index cases with low viral load. Each index high viral load case transmitted an average of 6.25 secondary cases whereas the same of low viral load transmitted an average of 0.8 case. CONCLUSION: If cases with higher viral load are selectively isolated on detection from the rest of the community along with contact tracing of all individuals, who came in contact with them during the previous 5 days, the quantum of transmission will reduce subsequently. Moreover, health-care workers often get infected while working, probably due to the fact that they often handle cases with higher viral load. The Ct value of all may be provided along with test report to safeguard everybody's health including health-care workers.