Clinical and computed tomographic imaging features of novel coronavirus pneumonia caused by SARS-CoV-2

Molecular Epidemiology of SARS-CoV-2 within Accra Metropolis Postlockdown

Introduction

Currently, sequencing has been the only tool for the identification of circulating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants. However, it is known to be an expensive and laborious approach involving high technical expertise. Considering the reduced adherence to preventive measures postlockdown in Accra, this study presents an alternative method that leverages polymerase chain reaction (PCR) to identify circulating SARS-CoV-2 variants in the Accra Metropolis postlockdown.

Methods

This prospective cross-sectional study was conducted between July and December 2022. Nasopharyngeal samples were collected from 268 consenting participants. Samples were subjected to nucleic acid extraction and followed by real-time polymerase chain reaction for the detection and quantification of SARS-CoV-2 RNA. SARS-CoV-2 positive samples were subsequently subjected to variant identification using rapid PCR. Findings. The prevalence of SARS-CoV-2 within the Accra Metropolis was 30.2%. The majority of the SARS-CoV-2 infection was diagnosed in females, participants aged 41-50 years, and symptomatic participants. Participants aged ≤10 years and females recorded the highest viral load while participants aged 41-50 years recorded the highest number of infections. The SARS-CoV-2 variants detected were Alpha (64.2%), Delta (22.2%), and Omicron (13.6%). Predictors of SARS-CoV-2 infection identified were chills, cough, headache, body weakness, sore throat, and dyspnoea in order of decreasing association with SARS-CoV-2 infection. There was a strong association between symptom status, gender, age, and SARS-CoV-2 infection.

Conclusion

There was a high prevalence of SARS-CoV-2 within the Accra Metropolis postlockdown within the sampling period. The Alpha variant of SARS-CoV-2 is the predominant circulating variant, and persons presenting with symptoms are most likely to be diagnosed with COVID-19. Children aged ≤10 years serve as a reservoir for infection transmission.

Delta Variant in the COVID-19 Pandemic: A Comparative Study on Clinical Outcomes Based on Vaccination Status

BACKGROUND

As the global battle against the COVID-19 pandemic endures, the spread of the Delta variant has introduced nuanced challenges, prompting a nuanced examination.

MATERIALS AND METHODS

We performed a multilevel logistic regression analysis encompassing 197 patients, comprising 44 vaccinated individuals (V group) and 153 unvaccinated counterparts (UV). These patients, afflicted with the Delta variant of SARS-CoV-2, were hospitalized between October 2021 and February 2022 at the COVID-19 department of a University Centre in Cluj-Napoca, Romania. We compared patient characteristics, CT lung involvement, Padua score, oxygen saturation (O2 saturation), ventilation requirements, dynamics of arterial blood gas (ABG) parameters, ICU admission rates, and mortality rates between the two groups.

RESULTS

The UV group exhibited a statistically significant (p < 0.05) proclivity toward developing a more severe form of infection, marked by elevated rates of lung involvement, oxygen requirement, ICU admission, and mortality.

CONCLUSION

Our findings underscore the substantial efficacy of the vaccine in diminishing the incidence of severe disease, lowering the rates of ICU admissions, and mitigating mortality among hospitalized patients.

Detecting Respiratory Viruses Using a Portable NIR Spectrometer-A Preliminary Exploration with a Data Driven Approach

Respiratory viruses' detection is vitally important in coping with pandemics such as COVID-19. Conventional methods typically require laboratory-based, high-cost equipment. An emerging alternative method is Near-Infrared (NIR) spectroscopy, especially a portable one of the type that has the benefits of low cost, portability, rapidity, ease of use, and mass deployability in both clinical and field settings. One obstacle to its effective application lies in its common limitations, which include relatively low specificity and general quality. Characteristically, the spectra curves show an interweaving feature for the virus-present and virus-absent samples. This then provokes the idea of using machine learning methods to overcome the difficulty. While a subsequent obstacle coincides with the fact that a direct deployment of the machine learning approaches leads to inadequate accuracy of the modelling results. This paper presents a data-driven study on the detection of two common respiratory viruses, the respiratory syncytial virus (RSV) and the Sendai virus (SEV), using a portable NIR spectrometer supported by a machine learning solution enhanced by an algorithm of variable selection via the Variable Importance in Projection (VIP) scores and its Quantile value, along with variable truncation processing, to overcome the obstacles to a certain extent. We conducted extensive experiments with the aid of the specifically developed algorithm of variable selection, using a total of four datasets, achieving classification accuracy of: (1) 0.88, 0.94, and 0.93 for RSV, SEV, and RSV + SEV, respectively, averaged over multiple runs, for the neural network modelling of taking in turn 3 sessions of data for training and the remaining one session of an 'unknown' dataset for testing. (2) the average accuracy of 0.94 (RSV), 0.97 (SEV), and 0.97 (RSV + SEV) for model validation and 0.90 (RSV), 0.93 (SEV), and 0.91 (RSV + SEV) for model testing, using two of the datasets for model training, one for model validation and the other for model testing. These results demonstrate the feasibility of using portable NIR spectroscopy coupled with machine learning to detect respiratory viruses with good accuracy, and the approach could be a viable solution for population screening.

Neurological complications and effects of COVID-19: Symptoms and conceivable mechanisms

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. The new coronavirus disease (COVID-19) was declared a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 can invade the nervous system aside from infecting the respiratory system as its primary target. The most common nervous system symptoms of COVID-19 are stated as headache, myalgia, fatigue, nausea, vomiting, sudden and unexplained anosmia, and ageusia. More severe conditions such as encephalomyelitis, acute myelitis, thromboembolic events, ischemic stroke, intracerebral hemorrhage, Guillain-Barré-syndrome, Bell's palsy, rhabdomyolysis, and even coma have also been reported. Cohort studies revealed that neurological findings are associated with higher morbidity and mortality. The neurological symptoms and manifestations caused by SARS-CoV-2 and COVID-19 are examined and summarized in this article.

A systematic review of the research progress of traditional Chinese medicine against pulmonary fibrosis: from a pharmacological perspective

Pulmonary fibrosis is a chronic progressive interstitial lung disease caused by a variety of etiologies. The disease can eventually lead to irreversible damage to the lung tissue structure, severely affecting respiratory function and posing a serious threat to human health. Currently, glucocorticoids and immunosuppressants are the main drugs used in the clinical treatment of pulmonary fibrosis, but their efficacy is limited and they can cause serious adverse effects. Traditional Chinese medicines have important research value and potential for clinical application in anti-pulmonary fibrosis. In recent years, more and more scientific researches have been conducted on the use of traditional Chinese medicine to improve or reduce pulmonary fibrosis, and some important breakthroughs have been made. This review paper systematically summarized the research progress of pharmacological mechanism of traditional Chinese medicines and their active compounds in improving or reducing pulmonary fibrosis. We conducted a systematic search in several main scientific databases, including PubMed, Web of Science, and Google Scholar, using keywords such as idiopathic pulmonary fibrosis, pulmonary fibrosis, interstitial pneumonia, natural products, herbal medicine, and therapeutic methods. Ultimately, 252 articles were included and systematically evaluated in this analysis. The anti-fibrotic mechanisms of these traditional Chinese medicine studies can be roughly categorized into 5 main aspects, including inhibition of epithelial-mesenchymal transition, anti-inflammatory and antioxidant effects, improvement of extracellular matrix deposition, mediation of apoptosis and autophagy, and inhibition of endoplasmic reticulum stress. The purpose of this article is to provide pharmaceutical researchers with information on the progress of scientific research on improving or reducing Pulmonary fibrosis with traditional Chinese medicine, and to provide reference for further pharmacological research.

Distinct Features of Vascular Diseases in COVID-19

The Coronavirus Disease 2019 (COVID-19) pandemic was declared in early 2020 after several unexplained pneumonia cases were first reported in Wuhan, China, and subsequently in other parts of the world. Commonly, the disease comprises several clinical features, including high temperature, dry cough, shortness of breath, and hypoxia, associated with findings of interstitial pneumonia on chest X-ray and computer tomography. Nevertheless, severe forms of acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) are not limited to the respiratory tract but also may be extended to other systems, including the cardiovascular system. The bi-directional relationship between atherosclerosis and COVID-19 is accompanied by poor prognosis. The immune response hyperactivation due to SARS-CoV-2 infection causes an increased secretion of cytokines, endothelial dysfunction, and arterial stiffness, which promotes the development of atherosclerosis. Also, due to the COVID-19 pandemic, access to healthcare amenities was reduced, resulting in increased morbidity and mortality in patients at risk. Furthermore, as lockdown measures were largely adopted worldwide, the sedentary lifestyle and the increased consumption of processed nutrients or unhealthy food increased, and in the consequence, we might observe even 70% of overweight and obese population. Altogether, with the relatively low ratio of vaccinated people in many countries, and important health debt appeared, which is now and will be for next decade a large healthcare challenge. However, the experience gained in the COVID-19 pandemic and the new methods of patients' approaching have helped the medical system to overcome this crisis and will hopefully help in the case of new possible epidemics.

Long COVID in Young Patients: Impact on Lung Volume Evaluated Using Multidetector CT

PURPOSE

To evaluate using quantitative analysis on chest CT images a possible lung volume reduction in Long COVID patients who complain mild respiratory symptoms, with chest CT negative for inflammatory findings.

MATERIALS AND METHODS

CT images of patients from 18 to 40 years old who underwent chest CT scan at our institution were analyzed retrospectively, using AwServer Thoracic VCAR software for a quantitative study. Exclusion criteria were inflammatory findings at CT, previous lung surgery, lung cancer, and breath artifacts that invalidate the quality of images. Patients were divided into two groups: in the first one ("post-COVID") were patients who had previous SARS-CoV-2 infection, confirmed by an RT-PCR, who underwent chest CT from 3 to 6 months after their negativization for long COVID symptoms; in the control group ("non-COVID"), were enrolled patients who underwent a chest CT scan from January 2018 to December 2019, before the spread of COVID in Italy.

RESULTS

Our final population included 154 TC, 77 post-COVID patients (mean age 33 ± 6) and 77 non-COVID patients (mean age 33 ± 4.9). Non statistical significative differences were obtained between groups in terms of age, sex, and other characteristics that affect total lung capacity such as obesity, thoracic malformations, and smoking habit. Mean values of the total lung volume (TV), right-lung volume (RV), and left-lung volume (LV) in the post-COVID group compared with non-COVID group were, respectively: 5.25 ± 0.25 L vs. 5.72 ± 0.26 L (p = 0.01); 2.76 ± 0.14 L vs. 3 ± 0.14 L (p = 0.01); 2.48 ± 0.12 L vs. 2.72 ± 0.12 L (p = 0.01).

CONCLUSION

In patients with symptoms suggesting Long COVID and negative chest CT macroscopic findings, quantitative volume analysis demonstrated a mean value of reduction in lung volume of 10% compared to patients of the same age who never had COVID. A chest CT negative for inflammatory findings may induce clinicians to attribute Long COVID mild respiratory symptoms to anxiety, especially in young patients. Our study brings us beyond appearances and beyond the classic radiological signs, introducing a quantitative evaluation of lung volumes in these patients. It is hard to establish to what extent this finding may contribute to Long COVID symptoms, but this is another step to gain a wider knowledge of the potential long-term effects caused by this new virus.

Auxiliary screening COVID-19 by computed tomography

Background

The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for the control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the computed tomography (CT) auxiliary screening methods for COVID-19 infection in the real world.

Methods

Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wanfang databases were searched for relevant articles published prior to 1 September 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully.

Results

One hundred and fifteen studies were included with 51,500 participants in the meta-analysis. Among these studies, the pooled estimates for AUC of CT in confirmed cases, and CT in suspected cases to predict COVID-19 diagnosis were 0.76 and 0.85, respectively. The CT in confirmed cases dOR was 5.51 (95% CI: 3.78-8.02). The CT in suspected cases dOR was 13.12 (95% CI: 11.07-15.55).

Conclusion

Our findings support that CT detection may be the main auxiliary screening method for COVID-19 infection in the real world.

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia

BACKGROUND

The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model.

METHODS

LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived quantities corresponding to qualitative characteristics used to clinically assess COVID-19 lesions. The comparison was carried out on 120 publicly available CT scans of patients affected by COVID-19 pneumonia. Scans were scored for four qualitative metrics: percentage of lung involvement, type of lesion, and two disease distribution scores. We evaluated the agreement between the LungQuant output and the visual assessments through receiver operating characteristics area under the curve (AUC) analysis and by fitting a nonlinear regression model.

RESULTS

Despite the rather large heterogeneity in the qualitative labels assigned by the clinical experts for each metric, we found good agreement on the metrics compared to the LungQuant output. The AUC values obtained for the four qualitative metrics were 0.98, 0.85, 0.90, and 0.81.

CONCLUSIONS

Visual clinical evaluation could be complemented and supported by computer-aided quantification, whose values match the average evaluation of several independent clinical experts.

KEY POINTS

We conducted a multicenter evaluation of the deep learning-based LungQuant automated software. We translated qualitative assessments into quantifiable metrics to characterize coronavirus disease 2019 (COVID-19) pneumonia lesions. Comparing the software output to the clinical evaluations, results were satisfactory despite heterogeneity of the clinical evaluations. An automatic quantification tool may contribute to improve the clinical workflow of COVID-19 pneumonia.

The role of immune activation and antigen persistence in acute and long COVID

In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the global coronavirus disease 2019 (COVID-19) pandemic. Although most infections cause a self-limited syndrome comparable to other upper respiratory viral pathogens, a portion of individuals develop severe illness leading to substantial morbidity and mortality. Furthermore, an estimated 10%-20% of SARS-CoV-2 infections are followed by post-acute sequelae of COVID-19 (PASC), or long COVID. Long COVID is associated with a wide variety of clinical manifestations including cardiopulmonary complications, persistent fatigue, and neurocognitive dysfunction. Severe acute COVID-19 is associated with hyperactivation and increased inflammation, which may be an underlying cause of long COVID in a subset of individuals. However, the immunologic mechanisms driving long COVID development are still under investigation. Early in the pandemic, our group and others observed immune dysregulation persisted into convalescence after acute COVID-19. We subsequently observed persistent immune dysregulation in a cohort of individuals experiencing long COVID. We demonstrated increased SARS-CoV-2-specific CD4⁺ and CD8⁺ T-cell responses and antibody affinity in patients experiencing long COVID symptoms. These data suggest a portion of long COVID symptoms may be due to chronic immune activation and the presence of persistent SARS-CoV-2 antigen. This review summarizes the COVID-19 literature to date detailing acute COVID-19 and convalescence and how these observations relate to the development of long COVID. In addition, we discuss recent findings in support of persistent antigen and the evidence that this phenomenon contributes to local and systemic inflammation and the heterogeneous nature of clinical manifestations seen in long COVID.

Risk of mortality in COVID-19 patients: a meta- and network analysis

Understanding the most relevant hematological/biochemical characteristics, pre-existing health conditions and complications in survivors and non-survivor will aid in predicting COVID-19 patient mortality, as well as intensive care unit (ICU) referral and death. A literature review was conducted for COVID-19 mortality in PubMed, Scopus, and various preprint servers (bioRxiv, medRxiv and SSRN), with 97 observational studies and preprints, consisting of survivor and non-survivor sub-populations. This meta/network analysis comprised 19,014 COVID-19 patients, consisting of 14,359 survivors and 4655 non-survivors. Meta and network analyses were performed using META-MAR V2.7.0 and PAST software. The study revealed that non-survivors of COVID-19 had elevated levels of gamma-glutamyl transferase and creatinine, as well as a higher number of neutrophils. Non-survivors had fewer lymphocytes and platelets, as well as lower hemoglobin and albumin concentrations. Age, hypertension, and cerebrovascular disease were shown to be the most influential risk factors among non-survivors. The most common complication among non-survivors was heart failure, followed by septic shock and respiratory failure. Platelet counts, creatinine, aspartate aminotransferase, albumin, and blood urea nitrogen levels were all linked to ICU admission. Hemoglobin levels preferred non-ICU patients. Lower levels of hemoglobin, lymphocytes, and albumin were associated with increased mortality in ICU patients. This meta-analysis showed that inexpensive and fast biochemical and hematological tests, as well as pre-existing conditions and complications, can be used to estimate the risk of mortality in COVID-19 patients.

Vertical Artifacts as Lung Ultrasound Signs: Trick or Trap? Part 2- An Accademia di Ecografia Toracica Position Paper on B-Lines and Sonographic Interstitial Syndrome

Although during the last few years the lung ultrasound (LUS) technique has progressed substantially, several artifacts, which are currently observed in clinical practice, still need a solid explanation of the physical phenomena involved in their origin. This is particularly true for vertical artifacts, conventionally known as B-lines, and for their use in clinical practice. A wider consensus and a deeper understanding of the nature of these artifactual phenomena will lead to a better classification and a shared nomenclature, and, ultimately, result in a more objective correlation between anatomo-pathological data and clinical scenarios. The objective of this review is to collect and document the different signs and artifacts described in the history of chest ultrasound, with a particular focus on vertical artifacts (B-lines) and sonographic interstitial syndrome (SIS). By reviewing the possible physical and anatomical interpretation of the signs and artifacts proposed in the literature, this work also aims to bring order to the available studies and to present the AdET (Accademia di Ecografia Toracica) viewpoint in terms of nomenclature and clinical approach to the SIS.

Effect of vaccine on prognosis and mortality in COVID-19

INTRODUCTION:The purpose of our study is to reveal the factors affecting the clinical course of the Covid-19 infection and mortality in the immunized and non-immunized 65-year-old and older patients. METHOD AND MATERIAL: The study was conducted by screening the files of 1,642 65-year-old and older Covid-19 cases in total.1337 cases enrolled in the study were categorized into two groups as follows: the patients vaccinated with the 2nd dose of CoronaVac but infected with Covid-19 after the 14-day period during which immunization is supposed to develop (Group I) and the patients who have never been vaccinated, who have been vaccinated with a single dose, or who have been infected with Covid-19 before the 14-day period is completed in spite of being vaccinated with the 2nd dose (Group II).The groups were compared with each other with regard to mortality and the factors affecting mortality. RESULTS: The length of ICU stay and the total length of hospital stay were significantly longer in Group II than Group I ( p

Chronic Disease and Other Determinants in Deaths Due to COVID-19 From a Health Protection and Promotion Perspective: A Retrospective Analysis

OBJECTIVE

To examine the age, gender, and chronic disease status of patients who died due to coronavirus disease 2019 (COVID-19) during the pandemic process and the effects of these diseases on their deaths.

METHODS

It was a retrospective retrospective analysis with 2715 patients. The statistics of the patients who met the research criteria were evaluated from the hospital database. Patients were evaluated in terms of age, gender, length of hospital stay, presence of chronic disease, and Modified Comorbidity Index Scores.

RESULTS

It was determined that the Modified Charlson Comorbidity Index (MCCI) score mean of the patients was 4.74 ± 2.07 and MCCI scores of 56.9% were serious. There was a statistically significant difference in the length of hospital stay according to the number of diseases the patient had, age, and MCCI score. It was determined that there was a statistically significant, negative and high-level correlation between MCCI score and the length of hospital stay (r = -0.075: P = 0.001).

CONCLUSIONS

Age, comorbidity score, and the number of comorbidities were found to affect the length of hospital stay, ie death. For this reason, it is recommended to use comorbidity indices in health protection and development studies, in the field, as well as in the clinics.

Sex and age differences in the COVID-19 mortality in East Jakarta, Indonesia: Analysis of COVID-19 surveillance system

Demographic factors have been reported to worsen COVID-19 outcomes. However, there is limited evidence about the different effects of sex and age on COVID-19 death in East Jakarta, Indonesia. This study examined the association between sex and age with COVID-19 mortality. Using COVID- 19 surveillance data of East Jakarta from March 2020 to December 2021, we calculated COVID-19 mortality and examined the risk of COVID-19 death by sex and age. The risk of COVID-19 death associated with sex and age was examined by using Multiple Logistic Regression. A total of 202.412 cases were analyzed and 1.9% of them died. The elderly had a 41.88-folds increased risk of COVID-19 mortality than younger patients (<45 years) (aOR 41.88; 95% CI 37.49-46.77; p-value <0.0001). Male had a higher risk of COVID-19 death compared to female (aOR 1.27; 95% CI 1.19-1.35; pvalue <0.0001). Age and sex had a significant association with COVID-19 mortality. Adequate management of COVID-19 cases, particularly in the elderly and male patients, may reduce the severity of COVID-19 or even mortality.

SARS COV-2 and other viral etiology as a possible clue for the olfactory dilemma

Background

Post-viral anosmia is responsible for more than 40% of cases of anosmia. Anosmia has been a neglected symptom in the primary healthcare setting until the emergence of the SARS-CoV-2 pandemic. The spread of SARS-CoV-2 infection highlighted new atypical symptoms of the disease, including anosmia, which has become one of the diagnostic symptoms of the disease, and epidemiological concern. We aimed to detect the incidence of SARS-CoV-2 infection within patients presented with anosmia and to test for other respiratory viruses in the negative COVID-19 patients. We also detected the recovery of anosmia and IgM/IgG against COVID-19. We prospectively included 60 outpatients with the major complaint of anosmia. Nasopharyngeal swabs were done for SARS-CoV-2 real-time PCR, and if negative, PCR to other respiratory pathogens was tested. After one month, we inquired about the recovery of smell loss together with testing for antibodies against SARS-CoV-2.

Results

Sixty patients were enrolled in the study. Forty-six patients (76.7%) were SARS-CoV-2 PCR positive and 14 (23.3%) were negative. Rhinovirus was the commonest isolated pathogen in the negative cases (5/14). Complete recovery of anosmia occurred in 34 patients (56.7%), while partial recovery in 24 (40.0%), and no recovery in 2 patients (3.3%). The median time to complete recovery was 10 days. 28.3% (13/46) of the patients showed negative antibody response for both IgG and IgM.

Conclusions

Sudden-onset anosmia is a symptom that is highly predictive of being COVID-19-infected. While recovery is expected within 2 weeks, some patients have no antibodies against SARS-CoV-2.

Neurological manifestations of COVID-19: a retrospective observational study based on 1060 patients with a narrative review

Background

In the past two decades, three coronavirus epidemics have been reported. Coronavirus disease 2019 (COVID-19) is caused by a severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2). In most patients, the disease is characterized by interstitial pneumonia, but features can affect other organs.

Purpose

To document the radiological features of the patients and to perform a narrative review of the literature.

Material and Methods

We conducted a retrospective, single-center study on 1060 consecutive hospitalized patients with COVID-19 at our institution. According to the inclusion criteria, we selected patients to be studied in more radiological detail. All images were obtained as per standard of care protocols. We performed a statistic analysis to describe radiological features. We then presented a systematic review of the main and conventional neuroimaging findings in COVID-19.

Results

Of 1060 patients hospitalized for COVID-19 disease, 15% (159) met the eligibility criteria. Of these, 16 (10%) did not undergo radiological examinations for various reasons, while 143 (90%) were examined. Of these 143 patients, 48 (33.6%) had positive neuroimaging. We found that the most frequent pathology was acute ischemic stroke (n=16, 33.3%). Much less frequent were Guillain–Barre syndrome (n=9, 18.8%), cerebral venous thrombosis (n=7, 14.6%), encephalitis or myelitis (n=6, 12.5%), intracranial hemorrhage and posterior hemorrhagic encephalopathy syndrome (n=4, 8.3%), exacerbation of multiple sclerosis (n=4, 8.3%), and Miller–Fisher syndrome (n=2, 4.2%).

Conclusion

Our data are coherent with the published literature. Knowledge of these patterns will make clinicians consider COVID-19 infection when unexplained neurological findings are encountered.

A persistent neutrophil-associated immune signature characterizes post-COVID-19 pulmonary sequelae

Interstitial lung disease and associated fibrosis occur in a proportion of individuals who have recovered from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection through unknown mechanisms. We studied individuals with severe coronavirus disease 2019 (COVID-19) after recovery from acute illness. Individuals with evidence of interstitial lung changes at 3 to 6 months after recovery had an up-regulated neutrophil-associated immune signature including increased chemokines, proteases, and markers of neutrophil extracellular traps that were detectable in the blood. Similar pathways were enriched in the upper airway with a concomitant increase in antiviral type I interferon signaling. Interaction analysis of the peripheral phosphoproteome identified enriched kinases critical for neutrophil inflammatory pathways. Evaluation of these individuals at 12 months after recovery indicated that a subset of the individuals had not yet achieved full normalization of radiological and functional changes. These data provide insight into mechanisms driving development of pulmonary sequelae during and after COVID-19 and provide a rational basis for development of targeted approaches to prevent long-term complications.

Drug Repurposing Against Angiotensin-Converting Enzyme-Related Carboxypeptidase (ACE2) Through Computational Approach

Ongoing novel coronavirus (COVID-19) with high mortality is an infectious disease in the world which epidemic in 2019 with human-human transmission. According to the literature, S-protein is one of the main proteins of COVID-19 that bind to the human cell receptor angiotensin-converting enzyme 2 (ACE2). In this study, it was attempted to identify the main effective drugs approved that may be repurposed to the binding site of ACE2. High throughput virtual screening based on the docking study was performed to know which one of the small-molecules had a potential interaction with ACE2 structure. Forasmuch as investigating and identifying the best ACE2 inhibitors among more than 3,500 small-molecules is time-consuming, supercomputer was utilized to apply docking-based virtual screening. Outputs of the proposed computational model revealed that vincristine, vinbelastin and bisoctrizole can significantly bind to ACE2 and may interface with its normal activity.

A systematic review and meta-analysis of the epidemiological characteristics of COVID-19 in children

BACKGROUND

Several individual studies from specific countries have reported rising numbers of pediatric COVID-19 cases with inconsistent reports on the clinical symptoms including respiratory and gastrointestinal symptoms as well as diverse reports on the mean age and household exposure in children. The epidemiological characteristics of COVID-19 in children are not fully understood, hence, comprehensive meta-analyses are needed to provide a better understanding of these characteristics.

METHODS

This review was conducted in Medline, Scopus, Cochrane library, Embase, Web of Science, and published reports on COVID-19 in children. Data were extracted by two independent researchers and a third researcher resolved disputes. STATA software and the random-effect model were used in the synthesis of our data. For each model, the heterogeneity between studies was estimated using the Q Cochrane test. Heterogeneity and publication bias were calculated using the I² statistic and Egger's/Begg's tests.

RESULTS

The qualitative systematic review was performed on 32 articles. Furthermore, the meta-analysis estimated an overall rate of involvement at 12% (95% CI: 9-15%) among children, with an I² of 98.36%. The proportion of household exposure was calculated to be 50.99% (95% CI: 20.80%-80.80%) and the proportion of admitted cases was calculated to be 45% (95% CI: 24%-67%). Additionally, the prevalence of cough, fatigue, fever and dyspnea was calculated to be 25% (95% CI: 0.16-0.36), 9% (95% CI: 0.03-0.18), 33% (95% CI: 0.21-0.47) and 9% (95% CI: 0.04-0.15), respectively. It is estimated that 4% (95% CI: 1-8%) of cases required intensive care unit admission.

CONCLUSIONS

The pediatric clinical picture of COVID-19 is not simply a classic respiratory infection, but unusual presentations have been reported. Given the high incidence of household transmission and atypical clinical presentation in children, we strongly recommend their inclusion in research and population-based preventive measures like vaccination as well as clinical trials to ensure efficacy, safety, and tolerability in this age group.

Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis

Background

Chest computerized tomography (CT) plays an important role in detecting patients with suspected coronavirus disease 2019 (COVID-19), however, there are no systematic summaries on whether the chest CT findings of patients within mainland China are applicable to those found in patients outside.

Methods

Relevant studies were retrieved comprehensively by searching PubMed, Embase, and Cochrane Library databases before 15 April 2022. Quality assessment of diagnostic accuracy studies (QUADAS) was used to evaluate the quality of the included studies, which were divided into two groups according to whether they were in mainland China or outside. Data on diagnostic performance, unilateral or bilateral lung involvement, and typical chest CT imaging appearances were extracted, and then, meta-analyses were performed with R software to compare the CT features of COVID-19 pneumonia between patients from within and outside mainland China.

Results

Of the 8,258 studies screened, 19 studies with 3,400 patients in mainland China and 14 studies with 554 outside mainland China were included. Overall, the risk of quality assessment and publication bias was low. The diagnostic value of chest CT is similar between patients from within and outside mainland China (93, 91%). The pooled incidence of unilateral lung involvement (15, 7%), the crazy-paving sign (31, 21%), mixed ground-glass opacities (GGO) and consolidations (51, 35%), air bronchogram (44, 25%), vascular engorgement (59, 33%), bronchial wall thickening (19, 12%), and septal thickening (39, 26%) in patients from mainland China were significantly higher than those from outside; however, the incidence rates of bilateral lung involvement (75, 84%), GGO (78, 87%), consolidations (45, 58%), nodules (12, 17%), and pleural effusion (9, 15%) were significantly lower.

Conclusion

Considering that the chest CT features of patients in mainland China may not reflect those of the patients abroad, radiologists and clinicians should be familiar with various CT presentations suggestive of COVID-19 in different regions.

Efficacy of the lactate dehydrogenase (LDH)/lymphocyte ratio (LLR) to reduce the need for X-ray in pregnant patients with COVID-19

OBJECTIVES

Pregnancy carries a significant risk for coronavirus disease-2019 (COVID-19) due to natural immunosuppression. A previous study from our center has shown that the lactate dehydrogenase (LDH)/lymphocyte ratio (LLR) can be used in the early diagnosis of COVID-19 and predicting mortality. Based on this, we aimed to determine the effect of LLR on early detection of critical pregnant women and mortality in COVID-19.

METHODS

The data of 145 patients who were admitted to our hospital between March and December 2020; diagnosed with COVID-19 and hospitalized, were retrospectively analyzed.

RESULTS

The median gestation period was 31 weeks (range: 5-41), 30.3% (n: 44) gave birth and 68.3% (n: 99) were pregnant. Median LLR was 0.13 (range: 0.04-0.70). The rate of cough (47% vs. 22.8%; p=0.003) was found to be high in patients with LLR>0.13. The patients were divided into subgroups. The proportion of patients without active complaints was higher in the Q1, followed by the Q4. The proportion of patients with an initial complaint of cough increased as LLR from Q1 to Q4, the distribution of other complaints did not differ between the quartiles.

CONCLUSIONS

The higher rate of cough in the group with high LLR indicates that it may be an important indicator of lung involvement during pregnancy. The highest rate of non-treatment follow-up in the lowest LLR group proved that the LLR value at the time of diagnosis can be used as an important clinical marker in pregnant women.

Follow‐up the severity of abnormalities diagnosed in chest CT imaging of COVID‐19 patients: A cross‐sectional study

Background and Aims

Methods

Results

Conclusion

Update on the limited sensitivity of computed tomography relative to RT-PCR for COVID-19: a systematic review

Purpose

The global and ongoing COVID-19 outbreak has compelled the need for timely and reliable methods of detection for SARS-CoV-2 infection. Although reverse transcription-polymerase chain reaction (RT-PCR) has been widely accepted as a reference standard for COVID-19 diagnosis, several early studies have suggested the superior sensitivity of computed tomography (CT) in identifying SARS-CoV-2 infection. In a previous systematic review, we stratified studies based on risk for bias to evaluate the true sensitivity of CT for detecting SARS-CoV-2 infection. This study revisits our prior analysis, incorporating more current data to assess the sensitivity of CT for COVID-19.

Material and methods

The PubMed and Google Scholar databases were searched for relevant articles published between 1 January 2020, and 25 April 2021. Exclusion criteria included lack of specification regarding whether the study cohort was adult or paediatric, whether patients were symptomatic or asymptomatic, and not identifying the source of RT-PCR specimens. Ultimately, 62 studies were included for systematic review and were subsequently stratified by risk for bias using the QUADAS-2 quality assessment tool. Sensitivity data were extracted for random effects meta-analyses.

Results

The average sensitivity for COVID-19 reported by the high-risk-of-bias studies was 68% [CI: 58, 80; range: 38-96%] for RT-PCR and 91% [CI: 87, 96; range: 47-100%] for CT. The average sensitivity reported by the low-risk-of-bias studies was 84% [CI: 0.75, 0.94; range: 70-97%] for RT-PCR and 78% [CI: 71, 0.86; range: 44-92%] for CT.

Conclusions

On average, the high-risk-of bias studies underestimated the sensitivity of RT-PCR and overestimated the sensitivity of CT for COVID-19. Given the incorporation of recently published low-risk-of-bias articles, the sensitivities according to low-risk-of-bias studies for both RT-PCR and CT were higher than previously reported.

Conventional and pathogenic Th2 cells in inflammation, tissue repair, and fibrosis

Type 2 helper T (Th2) cells, a subset of CD4⁺ T cells, play an important role in the host defense against pathogens and allergens by producing Th2 cytokines, such as interleukin-4 (IL-4), IL-5, and IL-13, to trigger inflammatory responses. Emerging evidence reveals that Th2 cells also contribute to the repair of injured tissues after inflammatory reactions. However, when the tissue repair process becomes chronic, excessive, or uncontrolled, pathological fibrosis is induced, leading to organ failure and death. Thus, proper control of Th2 cells is needed for complete tissue repair without the induction of fibrosis. Recently, the existence of pathogenic Th2 (Tpath2) cells has been revealed. Tpath2 cells produce large amounts of Th2 cytokines and induce type 2 inflammation when activated by antigen exposure or tissue injury. In recent studies, Tpath2 cells are suggested to play a central role in the induction of type 2 inflammation whereas the role of Tpath2 cells in tissue repair and fibrosis has been less reported in comparison to conventional Th2 cells. In this review, we discuss the roles of conventional Th2 cells and pathogenic Th2 cells in the sequence of tissue inflammation, repair, and fibrosis.

A novel multi-scale based deep convolutional neural network for detecting COVID-19 from X-rays

The COVID-19 pandemic has posed an unprecedented threat to the global public health system, primarily infecting the airway epithelial cells in the respiratory tract. Chest X-ray (CXR) is widely available, faster, and less expensive therefore it is preferred to monitor the lungs for COVID-19 diagnosis over other techniques such as molecular test, antigen test, antibody test, and chest computed tomography (CT). As the pandemic continues to reveal the limitations of our current ecosystems, researchers are coming together to share their knowledge and experience in order to develop new systems to tackle it. In this work, an end-to-end IoT infrastructure is designed and built to diagnose patients remotely in the case of a pandemic, limiting COVID-19 dissemination while also improving measurement science. The proposed framework comprises six steps. In the last step, a model is designed to interpret CXR images and intelligently measure the severity of COVID-19 lung infections using a novel deep neural network (DNN). The proposed DNN employs multi-scale sampling filters to extract reliable and noise-invariant features from a variety of image patches. Experiments are conducted on five publicly available databases, including COVIDx, COVID-19 Radiography, COVID-XRay-5K, COVID-19-CXR, and COVIDchestxray, with classification accuracies of 96.01%, 99.62%, 99.22%, 98.83%, and 100%, and testing times of 0.541, 0.692, 1.28, 0.461, and 0.202 s, respectively. The obtained results show that the proposed model surpasses fourteen baseline techniques. As a result, the newly developed model could be utilized to evaluate treatment efficacy, particularly in remote locations.

A study on the factors influencing the transfer of COVID-19 severe illness patients out of the ICU based on generalized linear mixed effect model

The clinical data of 76 severe illness patients with novel coronavirus SARS-CoV-2 from July to August, 2020 admitted to the ICU Intensive Care Unit ward in a hospital in Urumqi were collected in the paper. By using the Laplace approximation parameter estimation method based on maximum likelihood estimation, the generalized linear mixed effect model (GLMM) was established to analyze the characteristics of clinical indicators in critical patients, and to screen the main influencing factors of COVID-19 critical patients' inability to be transferred out of the ICU in a short time: age, C-reactive protein, serum creatinine and lactate dehydrogenase.

Exposure modality influences viral kinetics but not respiratory outcome of COVID-19 in multiple nonhuman primate species

The novel coronavirus SARS-CoV-2 emerged in late 2019, rapidly reached pandemic status, and has maintained global ubiquity through the emergence of variants of concern. Efforts to develop animal models have mostly fallen short of recapitulating severe disease, diminishing their utility for research focusing on severe disease pathogenesis and life-saving medical countermeasures. We tested whether route of experimental infection substantially changes COVID-19 disease characteristics in two species of nonhuman primates (Macaca mulatta; rhesus macaques; RM, Chlorocebus atheiops; African green monkeys; AGM). Species-specific cohorts were experimentally infected with SARS-CoV-2 by either direct mucosal (intratracheal + intranasal) instillation or small particle aerosol in route-discrete subcohorts. Both species demonstrated analogous viral loads in all compartments by either exposure route although the magnitude and duration of viral loading was marginally greater in AGMs than RMs. Clinical onset was nearly immediate (+1dpi) in the mucosal exposure cohort whereas clinical signs and cytokine responses in aerosol exposure animals began +7dpi. Pathologies conserved in both species and both exposure modalities include pulmonary myeloid cell influx, development of pleuritis, and extended lack of regenerative capacity in the pulmonary compartment. Demonstration of conserved pulmonary pathology regardless of species and exposure route expands our understanding of how SARS-CoV-2 infection may lead to ARDS and/or functional lung damage and demonstrates the near clinical response of the nonhuman primate model for anti-fibrotic therapeutic evaluation studies.

The Basic Reproduction Number and Delayed Action of T Cells for Patients Infected with SARS-CoV-2

COVID-19 has been prevalent for the last two years. The transmission capacity of SARS-CoV-2 differs under the influence of different epidemic prevention policies, making it difficult to measure the infectivity of the virus itself. In order to evaluate the infectivity of SARS-CoV-2 in patients with different diseases, we constructed a viral kinetic model by adding the effects of T cells and antibodies. To analyze and compare the delay time of T cell action in patients with different symptoms, we constructed a delay differential equation model. Through the first model, we found that the basic reproduction number of severe patients is greater than that of mild patients, and accordingly, we constructed classification criteria for severe and mild patients. Through the second model, we found that the delay time of T cell action in severe patients is much longer than that in mild patients, and accordingly, we present suggestions for the prevention, diagnosis, and treatment of different patients.

Manifestaciones pulmonares de la artritis reumatoide, una revisión en tiempos de pandemia por SARS-CoV-2

La artritis reumatoide (AR) es una de las patologías crónicas de origen autoinmune más frecuentes. Su prevalencia varía del 0,5 al 1%, con un compromiso primario a nivel articular, generando gran discapacidad por las deformidades secundarias derivadas de un estado inflamatorio persistente. Considerando el alto impacto en la calidad de vida de quienes la padecen, sumado al alto costo de las intervenciones terapéuticas, se vuelve imperativo para el personal de salud sumar todos los esfuerzos para promover un diagnóstico temprano y reconocer las potenciales complicaciones con el fin de impactar positivamente en los desenlaces clínicos. Alrededor del 50% de los pacientes con AR pueden tener compromiso extraarticular, siendo el pulmón uno de los órganos más afectados. En época de pandemia por el virus SARS-CoV-2 es necesario recordar los tipos de compromiso pulmonar en pacientes con AR y tener en cuenta la susceptibilidad de estos pacientes a cuadros infecciosos que pueden generar una gran morbimortalidad.

Possible Role of Matrix Metalloproteinases and TGF-β in COVID-19 Severity and Sequelae

The costs of coronavirus disease 2019 (COVID-19) are devastating. With millions of deaths worldwide, specific serological biomarkers, antiviral agents, and novel therapies are urgently required to reduce the disease burden. For these purposes, a profound understanding of the pathobiology of COVID-19 is mandatory. Notably, the study of immunity against other respiratory infections has generated reference knowledge to comprehend the paradox of the COVID-19 pathogenesis. Past studies point to a complex interplay between cytokines and other factors mediating wound healing and extracellular matrix (ECM) remodeling that results in exacerbated inflammation, tissue injury, severe manifestations, and a sequela of respiratory infections. This review provides an overview of the immunological process elicited after severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Also, we analyzed available data about the participation of matrix metalloproteinases (MMPs) and transforming growth factor-beta (TGF-β) in immune responses of the lungs. Furthermore, we discuss their possible implications in severe COVID-19 and sequela, including pulmonary fibrosis, and remark on the potential of these molecules as biomarkers for diagnosis, prognosis, and treatment of convalescent COVID-19 patients. Our review provides a theoretical framework for future research aimed to discover molecular hallmarks that, combined with clinical features, could serve as therapeutic targets and reliable biomarkers of the different clinical forms of COVID-19, including convalescence.

Proportion of New Onset of Anosmia and Its Diagnostic Significance in COVID-19

Objective: This study aimed to know the proportion of new-onset of anosmia and to find its diagnostic significance in coronavirus disease 2019 (COVID-19) patients attending the hospital.

Study design and duration: The Indian smell test in COVID-19 by AIIMS Raipur (ISCA-R) was developed for evaluating olfaction in the Indian population. The olfactory function was assessed using the corona scale on anosmia AIIMS Raipur (COSANAr).

Results: Out of 256 patients, 171 were males and 85 were females. In the majority of the patients, 75 (29.29%), the COSANAr score “0” was higher on the day of admission compared to the score “3” on the day of discharge with 61 (23.82%) patients. There was no improvement in 134 (52.34%) patients with loss of smell at the time of discharge.

Conclusion: This study is a step forward in identifying anosmia by ISCA-R at the early stages of the COVID phase. The COSANAr is affordable for the Indian population. It is noticed that most of the patients have mild hyposmia at the time of discharge and anosmia at the admission time.

Statistical analysis of COVID-19 infection severity in lung lobes from chest CT

Detection of the COVID 19 virus is possible through the reverse transcription-polymerase chain reaction (RT-PCR) kits and computed tomography (CT) images of the lungs. Diagnosis via CT images provides a faster diagnosis than the RT-PCR method does. In addition to low false-negative rate, CT is also used for prognosis in determining the severity of the disease and the proposed treatment method. In this study, we estimated a probability density function (PDF) to examine the infections caused by the virus. We collected 232 chest CT of suspected patients and had them labeled by two radiologists in 6 classes, including a healthy class and 5 classes of different infection severity. To segment the lung lobes, we used a pre-trained U-Net model with an average Dice similarity coefficient (DSC) greater than 0.96. First, we extracted the PDF to grade the infection of each lobe and selected five specific thresholds as feature vectors. We then assigned this feature vector to a support vector machine (SVM) model and made the final prediction of the infection severity. Using the T-Test statistics, we calculated the p-value at different pixel thresholds and reported the significant differences in the pixel values. In most cases, the p-value was less than 0.05. Our developed model was developed on roughly labeled data without any manual segmentation, which estimated lung infection involvements with the area under the curve (AUC) in the range of [0.64, 0.87]. The introduced model can be used to generate a systematic automated report for individual patients infected by COVID-19.

Enigma of COVID-19: is “multisystem inflammatory syndrome in adults” (MIS-A) predictable?

Background

Severe inflammation and one or more extrapulmonary organ dysfunctions have been reported and this clinical picture is defined as "multisystem inflammatory syndrome in adults" (MIS-A) in severe coronavirus disease-2019 (COVID-19). We aimed to determine the effect of LDH/lymphocyte ratio (LLR) on the development of MIS-A.

Methods

The data of 2333 patients were retrospectively analyzed.

Results

MIS-A rate was found to be 9.9% and MIS-A related mortality was 35.3%. LRR level above 0.24 was found to predict MIS-A development with 70% sensitivity and 65.2% specificity. The risk of MIS-A development was found to be 3.64 times higher in those with LRR levels above 0.24 compared to those with 0.24 and below. In patients with MIS-A, LRR level above 0.32 predicts mortality with 78% sensitivity and 70% specificity.

Conclusions

Early detection of MIS-A with high sensitivity and specificity in a practical ratio is very important in terms new studies.

Perspective of AI system for COVID-19 detection using chest images: a review

Coronavirus Disease 2019 (COVID-19) is an evolving communicable disease caused due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) which has led to a global pandemic since December 2019. The virus has its origin from bat and is suspected to have transmitted to humans through zoonotic links. The disease shows dynamic symptoms, nature and reaction to the human body thereby challenging the world of medicine. Moreover, it has tremendous resemblance to viral pneumonia or Community Acquired Pneumonia (CAP). Reverse Transcription Polymerase Chain Reaction (RT-PCR) is performed for detection of COVID-19. Nevertheless, RT-PCR is not completely reliable and sometimes unavailable. Therefore, scientists and researchers have suggested analysis and examination of Computing Tomography (CT) scans and Chest X-Ray (CXR) images to identify the features of COVID-19 in patients having clinical manifestation of the disease, using expert systems deploying learning algorithms such as Machine Learning (ML) and Deep Learning (DL). The paper identifies and reviews various chest image features using the aforementioned imaging modalities for reliable and faster detection of COVID-19 than laboratory processes. The paper also reviews and compares the different aspects of ML and DL using chest images, for detection of COVID-19.

Computed tomography findings and prognosis in older COVID-19 patients

Background

In older and multimorbid patients, chronic conditions may affect the prognostic validity of computed tomography (CT) findings in COVID-19. This study aims at assessing to which extent CT findings have prognostic implications in COVID-19 older patients.

Methods

Hospitalized COVID-19 patients aged 60 years or more enrolled in the multicenter, observational and longitudinal GeroCovid study who underwent chest CT were included. Patients were stratified by tertiles of age and pneumonia severity to compare CT findings. Hierarchical clustering based on CT findings was performed to identify CT-related classificatory constructs, if any. The hazard ratio (HR) of mortality was calculated for individual CT findings and for clusters, after adjusting for potential confounders.

Results

380 hospitalized COVID-19 patients, with a mean age of 78 (SD:9) years, underwent chest CT scan. Ground glass opacity (GGO), consolidation, and pleural effusion were the three most common CT findings, with GGO prevalence decreasing from younger to older patients and pleural effusion increasing. More severe the pneumonia more prevalent were GGO, consolidation and pleural effusion. HR of mortality was 1.94 (95%CI 1.24–3.06) for pleural effusion and 13 (95%CI 6.41–27) for cluster with a low prevalence of GGO and a high prevalence of pleural effusion (“LH”), respectively. Out of the three CT based clusters, “LH” was the only independent predictor in the multivariable model.

Conclusions

Pleural effusion qualifies as a distinctive prognostic marker in older COVID-19 patients. Research is needed to verify whether pleural effusion reflects COVID-19 severity or a coexisting chronic condition making the patient at special risk of death.

Trial registration

ClinicalTrials.gov: NCT04379440

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02837-7.

Investigating of the role of CT scan for cancer patients during the first wave of COVID-19 pandemic

Introduction

Amidst this current COVID-19 pandemic, we undertook this systematic review to determine the role of medical imaging, with a special emphasis on computed tomography (CT), on guiding the care and management of oncologic patients.

Material and Methods

Study selection focused on articles from 01/02/2020 to 04/23/2020. After removal of irrelevant articles, all systematic or non-systematic reviews, comments, correspondence, editorials, guidelines and meta-analysis and case reports with less than 5 patients were also excluded. Full-text articles of eligible publications were reviewed to select all imaging-based publications, and the existence or not of an oncologic population was reported for each publication. Two independent reviewers collected the following information: ( 1) General publication data; (2) Study design characteristics; (3) Demographic, clinical and pathological variables with percentage of cancer patients if available; (4) Imaging performances. The sensitivity and specificity of chest CT (C-CT) were pooled separately using a random-effects model. The positive predictive value (PPV) and negative predictive value (NPV) of C-CT as a test was estimated for a wide range of disease prevalence rates.

Results

A total of 106 publications were fully reviewed. Among them, 96 were identified to have extractable data for a two-by-two contingency table for CT performance. At the end, 53 studies (including 6 that used two different populations) were included in diagnosis accuracy analysis (N = 59). We identified 53 studies totaling 11,352 patients for whom the sensitivity (95CI) was 0.886 (0.880; 0.894), while specificity remained low: in 93% of cases (55/59), specificity was ≤ 0.5. Among all the 106 reviewed studies, only 7 studies included oncologic patients and were included in the final analysis for C-CT performances. The percentage of patients with cancer in these studies was 0.3% (34/11352 patients), lower than the global prevalence of cancer. Among all these studies, only 1 (0.9%, 1/106) reported performance specifically in a cohort of cancer patients, but it however only reported true positives.

Discussion

There is a concerning lack of COVID-19 studies involving oncologic patients, showing there is a real need for further investigation and evaluation of the performance of the different medical imaging modalities in this specific patient population.

COVID Tarnish Lung: Residual Radiological Lung Consequences of Infection with COVID-19

Background:

COVID-19 has still expressed as a mysterious viral infection with dramatic pulmonary consequences.

Objectives:

This article aims to study the radiological pulmonary consequences of respiratory covid-19 infection at 6 months and their relevance to the clinical stage, laboratory markers, and management modalities.

Patients and methods:

This study was implemented on two hundred and fifty (250) confirmed positive cases for COVID-19 infections. One hundred and ninety-seven cases (197) who completed the study displayed residual radiological lung shadowing (RRLS) on follow-up computed tomography (CT) of the chest. They were categorized by Simple clinical classification of COVID-19 into groups A, B and C.

Results:

GGO as well as reticulations were statistically significantly higher in group A than other two groups; however, bronchiectasis changes, parenchymal scarring, nodules as well as pleural tractions were statistically significantly higher in group C than the other two groups.

Conclusion:

Respiratory covid-19 infection might be linked to residual radiological lung shadowing. Ground glass opacities GGO, reticulations pervaded in mild involvement with lower inflammatory markers level, unlike, severe changes that expressed scarring, nodules and bronchiectasis changes accompanied by increased levels of inflammatory markers.

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.

Quantitative determination of pulmonary emphysema in follow-up LD-CTs of patients with COVID-19 infection

Purpose

To evaluate the association between the coronavirus disease 2019 (COVID-19) and post-inflammatory emphysematous lung alterations on follow-up low-dose CT scans.

Methods

Consecutive patients with proven COVID-19 infection and a follow-up CT were retrospectively reviewed. The severity of pulmonary involvement was classified as mild, moderate and severe. Total lung volume, emphysema volume and the ratio of emphysema/-to-lung volume were quantified semi-automatically and compared inter-individually between initial and follow-up CT and to a control group of healthy, age- and sex-matched patients. Lung density was further assessed by drawing circular regions of interest (ROIs) into non-affected regions of the upper lobes.

Results

A total of 32 individuals (mean age: 64 ± 13 years, 12 females) with at least one follow-up CT (mean: 52 ± 66 days, range: 5–259) were included. In the overall cohort, total lung volume, emphysema volume and the ratio of lung-to-emphysema volume did not differ significantly between the initial and follow-up scans. In the subgroup of COVID-19 patients with > 30 days of follow-up, the emphysema volume was significantly larger as compared to the subgroup with a follow-up < 30 days (p = 0.045). Manually measured single ROIs generally yielded lower attenuation values prior to COVID-19 pneumonia, but the difference was not significant between groups (all p > 0.05).

Conclusion

COVID-19 patients with a follow-up CT >30 days showed significant emphysematous lung alterations. These findings may help to explain the long-term effect of COVID-19 on pulmonary function and warrant validation by further studies.

Infectious Causes of Stroke

Stroke is one of the primary causes of mortality and morbidity worldwide. It can be ischemic or hemorrhagic, and the former can be due to an in-situ thrombus or a distant embolus. Despite being a rare cause, stroke can also be caused in the setting of infection. Bacterial agents are the most common cause of stroke, among other infectious agents. Until the antibiotic era, rheumatic heart disease was a predisposing risk factor of infective endocarditis. VZV is the most common cause of strokes in pediatric and adult populations. Cryptococcus and Candida spp are the most common yeasts involved in CNS infections, especially in immunocompromised patients. In COVID-19 patients, ischemic strokes are more common than hemorrhagic strokes. In this review, we will discuss the most common infectious agents, with particular emphasis on COVID-19.

Comparison of chest CT severity scoring systems for COVID-19

PURPOSE

To compare the diagnostic performance and inter-observer agreement of five different CT chest severity scoring systems for COVID-19 to find the most precise one with the least interpretation time.

METHODS AND MATERIALS

This retrospective study included 85 patients (54 male and 31 female) with PCR-confirmed COVID-19. They underwent CT to assess the severity of pulmonary involvement. Three readers were asked to assess the pulmonary abnormalities and score the severity using five different systems, including chest CT severity score (CT-SS), chest CT score, total severity score (TSS), modified total severity score (m-TSS), and 3-level chest CT severity score. Time consumption on reporting of each system was calculated.

RESULTS

Two hundred fifty-five observations were reported for each system. There was a statistically significant inter-observer agreement in assessing qualitative lung involvement using the m-TSS and the other four quantitative systems. The ROC curves revealed excellent and very good diagnostic accuracy for all systems when cutoff values for detection severe cases were > 22, > 17, > 12, and > 26 for CT-SS, chest CT score, TSS, and 3-level CT severity score. The AUC was very good (0.86), excellent (0.90), very good (0.89), and very good (0.86), respectively. Chest CT score showed the highest specificity (95.2%) in discrimination of severe cases. Time consumption on reporting was significantly different (< 0.001): CT-SS > 3L-CT-SS > chest CT score > TSS.

CONCLUSION

All chest CT severity scoring systems in this study demonstrated excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. CT-SS and TSS had the highest specificity and least time for interpretation.

KEY POINTS

• All chest CT severity scoring systems discussed in this study revealed excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. • Chest CT scoring system and TSS had the highest specificity. • Both TSS and m-TSS consumed the least time compared to the other three scoring systems.

Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19

This study investigated associations between chest computed tomography (CT) pulmonary opacity score on admission and clinical features and outcomes in COVID-19 patients. The retrospective multi-center cohort study included 496 COVID-19 patients in Jiangsu province, China diagnosed as of March 15, 2020. Patients were divided into four groups based on the quartile of pulmonary opacity score: ≤ 5%, 6-20%, 21-40% and 41% +. CT pulmonary opacity score was independently associated with age, single onset, fever, cough, peripheral capillary oxygen saturation, lymphocyte count, platelet count, albumin level, C-reactive protein (CRP) level and fibrinogen level on admission. Patients with score ≥ 41% had a dramatic increased risk of severe or critical illness [odds ratio (OR), 15.58, 95% confidence interval (CI) 3.82-63.53), intensive care unit (ICU)] admission (OR, 6.26, 95% CI 2.15-18.23), respiratory failure (OR, 19.49, 95% CI 4.55-83.40), and a prolonged hospital stay (coefficient, 2.59, 95% CI 0.46-4.72) compared to those with score ≤ 5%. CT pulmonary opacity score on admission, especially when ≥ 41%, was closely related to some clinical characteristics and was an independent predictor of disease severity, ICU admission, respiratory failure and long hospital stay in patients with COVID-19.

Differences in Clinical and Imaging Features between Asymptomatic and Symptomatic COVID-19 Patients

OBJECTIVES

The clinical and imaging features of asymptomatic carriers of severe acute respiratory syndrome coronavirus 2 and symptomatic COVID-19 patients.

METHODS

The clinical and chest computed tomography imaging data of 47 asymptomatic carriers and 36 symptomatic COVID-19 patients were derived. All patients underwent 4-6 CT scans over a period of 2-5 days.

RESULTS

The bulk of asymptomatic carriers who developed symptoms and most of the COVID-19 patients were older than 18 years of age with a decreased lymphocyte count, abnormal hepatic and renal function, and increased D-dimer and C-reactive protein. In the early stage, the pulmonary lesion involved mostly 1-2 lobes at the peripheral area in asymptomatic carriers but more than three lobes at both the central and peripheral areas in COVID-19 patients. In the progression stage, the lesion of asymptomatic carriers extended from the peripheral to the central area, and no significant difference was found in the lesion range compared with the symptomatic control group. In early improvement stage, the lesion was rapidly absorbed, and lesions were located primarily at the peripheral area in asymptomatic carriers; contrastingly, lesions were primarily located at both the central and peripheral areas in symptomatic patients. Asymptomatic carriers reflected a significantly shorter duration from disease onset to peak progression stage compared with the symptomatic.

CONCLUSIONS

Asymptomatic carriers are a potential source of transmission and may become symptomatic COVID-19 patients despite indicating less severe pulmonary damage, earlier improvement, and better prognosis. Early isolation and intervention can eliminate such carriers as potential sources of transmission and improve their prognosis.

COVID-19 and MERS: Are their Chest X-ray and Computed Tomography Scanning Signs Related?

Background

COVID-19 is a respiratory infection brought about by SARS-COV-2. Most of the patients contaminated by this pathogen are afflicted by respiratory syndrome with multiple stages ranging from mild upper respiratory involvement to severe dyspnea and acute respiratory distress syndrome cases. Keeping in mind the high sensitivity of computed tomography (CT) scan in detecting abnormalities, it became the number one modality in COVID-19 diagnosis. A wide diversity of CT features can be found in COVID-19 cases, which can be observed before the onset of clinical signs. The review article is aimed to highlight recent discrepancies in CT-scan and chest X-ray (CXR) characteristics between COVID-19 and Middle East Respiratory Syndrome (MERS).

Method

This review study was performed in the literature from the beginning of COVID-19 until the middle of April 2021. For this reason, all relevant works through scientific citation websites such as Google Scholar, PubMed, and Web of Science have been investigated in the mentioned period.

Results

COVID-19 was more reproductive than MERS, while MERS was significantly higher in terms of mortality rate (COVID-19: 2.3% and MERS: 34.4%). Signs of ground-glass opacity (GGO), peripheral consolidation, and GGO accompanying with consolidation are the same signs CXR in both MERS and COVID-19. Indeed, fever, cough, headache, and sore throat are the most symptoms in all studied patients.

Conclusion

Both COVID-19 and MERS have the same imaging signs. The most similar chest CT findings are GGO, peripheral consolidation, and GGO superimposed by consolidation in both studied diseases, and no statistical differences were seen among the mean number of chest CT-scans in MERS and COVID-19 cases.

A multicentric study to correlate severity of disease and vaccine in COVID-19 pandemic

Background

The purpose of the study was to find out correlation between severity of disease and vaccine in COVID-19 pandemic. Primary objective was to know occurrence of post-vaccination breakthrough infections in hospitalized patients and secondary objective was to know of COVID-19 vaccine to prevent severe infection, morbidity, and mortality of patients. This retrospective observational multicentric study included 325 confirmed COVID-19 patients on NRBM/BIPAP/ventilator admitted in high dependency unit (HDU)/intensive care unit (ICU) were divided into based on severity of symptoms and vaccination status. We included adult patients having positive RTPCR (reverse transcription polymerase chain reaction) COVID-19 test/high-resolution computed tomography scan (HRCT) thorax suggestive of COVID-19 pneumonia. Patients who developed adverse reaction post-vaccination, pregnant patient, and lactating mother were excluded from the study.

Results

Total 325 confirmed COVID-19-positive patients were studied. Statistical analysis with SPSS version 26 and data were analyzed by chi-square test and P value < 0.05 were considered as significant. Total duration of hospital stay was less in vaccinated patients compared to non-vaccinated patients. Oxygen requirement was also less in vaccinated patients. Vaccinated patients developed less severe infection than non-vaccinated patients.

Conclusions

COVID-19 vaccination is very effective against severity of disease. It reduces hospitalization, oxygen requirement, and mortality.

Mass Spectrometry-Based Proteomics Research to Fight COVID-19: An Expert Review on Hopes and Challenges

The COVID-19 pandemic caused by the severe acute respiratory syndrome (SARS)-CoV-2 infection is a systemic disease and a major planetary health burden. While SARS-CoV-2 impacts host biology extensively, our knowledge of these alterations from a systems perspective remains incomplete. Moreover, there is currently only a limited description of this systemic disease. For precision diagnosis and treatment of SARS-CoV-2, multiomics technologies and systems science research offer significant prospects. This expert review offers a critical analysis of the prospects and challenges of the emerging mass spectrometry-based proteomics approaches to the study of COVID-19 as seen through a systems medicine lens. We also discuss the ways in which proteomics is poised to offer hope for diagnostics and therapeutics innovation on SARS-CoV-2 infection as the disease transitions from a pandemic to an endemic disease, and thus further challenging the health systems and services worldwide in the coming decade. Proteomics is an important high-throughput technology platform to achieve a functional overview of the ways in which COVID-19 changes host biology, and hence, can help identify possible points of entry for innovation in medicines and vaccines, among others.

Prevalence and clinical outcomes of pleural effusion in COVID-19 patients: A systematic review and meta-analysis

Observational studies indicate that pleural effusion has an association with risk and the clinical prognosis of COVID-19 disease; however, the available literature on this area is inconsistent. The objective of this systematic review and meta-analysis is to evaluate the correlation between COVID-19 disease and pleural effusion. A rigorous literature search was conducted using multiple databases. All eligible observational studies were included from around the globe. The pooled prevalence and associated 95% confidence interval (CI) were calculated using the random effect model. Mantel-Haenszel odds ratios were produced to report overall effect size using random effect models for severity and mortality outcomes. Funnel plots, Egger regression tests, and Begg-Mazumdar's rank correlation test were used to appraise publication bias. Data from 23 studies including 6234 COVID-19 patients was obtained. The overall prevalence of pleural effusion in COVID-19 patients was 9.55% (95% CI, I2  = 92%). Our findings also indicated that the presence of pleural effusions associated with increased risk of severity of disease(OR = 5.08, 95% CI 3.14-8.22, I2  = 77.4%) and mortality due to illness(OR = 4.53, 95% CI 2.16-9.49, I2  = 66%) compared with patients without pleural effusion. Sensitivity analyses illustrated a similar effect size while decreasing the heterogeneity. No significant publication bias was evident in the meta-analysis. The presence of pleural effusion can assist as a prognostic factor to evaluate the risk of worse outcomes in COVID-19 patients hence, it is recommended that hospitalized COVID-19 patients with pleural effusion should be managed on an early basis.