A radiomics-based model for the outcome prediction in COVID-19 positive patients through deep learning with both longitudinal chest x-ray and chest computed tomography images

The coronavirus disease 2019 (COVID-19) pandemic had a major impact on global health and was associated with millions of deaths worldwide. During the pandemic, imaging characteristics of chest X-ray (CXR) and chest computed tomography (CT) played an important role in the screening, diagnosis and monitoring the disease progression. Various studies suggested that quantitative image analysis methods including artificial intelligence and radiomics can greatly boost the value of imaging in the management of COVID-19. However, few studies have explored the use of longitudinal multi-modal medical images with varying visit intervals for outcome prediction in COVID-19 patients. This study aims to explore the potential of longitudinal multimodal radiomics in predicting the outcome of COVID-19 patients by integrating both CXR and CT images with variable visit intervals through deep learning. 2274 patients who underwent CXR and/or CT scans during disease progression were selected for this study. Of these, 946 patients were treated at the University of Pennsylvania Health System (UPHS) and the remaining 1328 patients were acquired at Stony Brook University (SBU) and curated by the Medical Imaging and Data Resource Center (MIDRC). 532 radiomic features were extracted with the Cancer Imaging Phenomics Toolkit (CaPTk) from the lung regions in CXR and CT images at all visits. We employed two commonly used deep learning algorithms to analyze the longitudinal multimodal features, and evaluated the prediction results based on the area under the receiver operating characteristic curve (AUC). Our models achieved testing AUC scores of 0.816 and 0.836, respectively, for the prediction of mortality. © 2023 SPIE.

COVID-19: comparison lung CT signs and biochemical parameters in the groups of patients with three-time positive RT-PCR and with triple negative RT-PCR test during the period of hospitalization.

Research goal. Comparative characteristics of the dynamics of CT semiotics and biochemical parameters of two groups of patients: with positive RT-PCR and with triple negative RT-PCR. Reflection of the results by comparing them with the data already available in the literature. The aim of the study is to compare the dynamics of CT semiotics and biochemical parameters of blood tests in two groups of patients: with positive RT-PCR and with triple negative RT-PCR. We also reflect the results by comparing them with the data already available in the literature. Materials and methods. We have performed a retrospective analysis of CT images of 66 patients: group I (n1 = 33) consists of patients who had three- time negative RT-PCR (nasopharyngeal swab for SARS-CoV-2 RNA) during hospitalization, and group II (n2 = 33) includes patients with triple positive RT-PCR. An important selection criterion is the presence of three CT examinations (primary, 1st CT and two dynamic examinations - 2nd CT and 3rd CT) and at least two results of biochemistry (C-reactive protein (CRP), fibrinogen, prothrombin time, procalcitonin) performed in a single time interval of +/- 5 days from 1st CT, upon admission, and +/- 5 days from 3st CT. A total of 198 CT examinations of the lungs were analyzed (3 examinations per patient). Results. The average age of patients in the first group was 58 +/- 14.4 years, in the second - 64.9 +/- 15.7 years. The number of days from the moment of illness to the primary CT scan 6.21 +/- 3.74 in group I, 7.0 (5.0-8.0) in group II, until the 2nd CT scan - 12.5 +/- 4, 87 and 12.0 (10.0-15.0), before the 3rd CT scan - 22.0 (19.0-26.0) and 22.0 (16.0-26.0), respectively. In both groups, all 66 patients (100%), the primary study identified the double-sided ground-glass opacity symptom and 36 of 66 (55%) patients showed consolidation of the lung tissue. Later on, a first follow-up CT defined GGO not in all the cases: it was presented in 22 of 33 (67%) patients with negative RT-PCR (group I) and in 28 of 33 (85%) patients with the positive one (group II). The percentage of studies showing consolidation increased significantly: up to 30 of 33 (91%) patients in group I, and up to 32 of 33 (97%) patients in group II. For the first time, radiological symptoms of "involutional changes" appeared: in 17 (52%) patients of the first group and in 5 (15%) patients of the second one. On second follow-up CT, GGO and consolidations were detected less often than on previous CT: in 1 and 27 patients of group I (3% and 82%, respectively) and in 6 and 30 patients of group II (18% and 91%, respectively), although the consolidation symptom still prevailed significantly . The peak of "involutional changes" occurred on last CT: 31 (94%) and 25 (76%) patients of groups I and II, respectively.So, in the groups studied, the dynamics of changes in lung CT were almost equal. After analyzing the biochemistry parameters, we found out that CRP significantly decreased in 93% of patients (p < 0.001) in group I;in group II, there was a statistically significant decrease in the values of C-reactive protein in 81% of patients (p = 0.005). With an increase in CT severity of coronavirus infection by one degree, an increase in CRP by 41.8 mg/ml should be expected. In group I, a statistically significant (p = 0.001) decrease in fibrinogen was recorded in 77% of patients;and a similar dynamic of this indicator was observed in group II: fibrinogen values decreased in 66% of patients (p = 0.002). Such parameters as procalcitonin and prothrombin time did not significantly change during inpatient treatment of the patients of the studied groups (p = 0.879 and p = 0.135), which may indicate that it is inappropriate to use these parameters in assessing dynamics of patients with a similar course of the disease. When comparing the outcomes of the studied groups, there was a statistically significant higher mortality in group II - 30.3%, in group I - 21.2% (p = 0.043). Conclusion. According to our data, a course of the disease does not significantly differ in the groups o patients with positive RT-PCR and three-time negative RT-PCR. A negative RT-PCR analysis may be associated with an individual peculiarity of a patient such as a low viral load of SARS-CoV-2 in the upper respiratory tract. Therefore, with repeated negative results on the RNA of the virus in the oro- and nasopharynx, one should take into account the clinic, the X-ray picture and biochemical indicators in dynamics and not be afraid to make a diagnosis of COVID-19.Copyright © 2021 ALIES. All rights reserved.

Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity prediction

It is important to evaluate medical imaging artificial intelligence (AI) models for possible implicit discrimination (ability to distinguish between subgroups not related to the specific clinical task of the AI model) and disparate impact (difference in outcome rate between subgroups). We studied potential implicit discrimination and disparate impact of a published deep learning/AI model for the prediction of ICU admission for COVID-19 within 24 hours of imaging. The IRB-approved, HIPAA-compliant dataset contained 8,357 chest radiography exams from February 2020-January 2022 (12% ICU admission within 24 hours) and was separated by patient into training, validation, and test sets (64%, 16%, 20% split). The AI output was evaluated in two demographic categories: sex assigned at birth (subgroups male and female) and self-reported race (subgroups Black/African-American and White). We failed to show statistical evidence that the model could implicitly discriminate between members of subgroups categorized by race based on prediction scores (area under the receiver operating characteristic curve, AUC: median [95% confidence interval, CI]: 0.53 [0.48, 0.57]) but there was some marginal evidence of implicit discrimination between members of subgroups categorized by sex (AUC: 0.54 [0.51, 0.57]). No statistical evidence for disparate impact (DI) was observed between the race subgroups (i.e. the 95% CI of the ratio of the favorable outcome rate between two subgroups included one) for the example operating point of the maximized Youden index but some evidence of disparate impact to the male subgroup based on sex was observed. These results help develop evaluation of implicit discrimination and disparate impact of AI models in the context of decision thresholds © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

Detecting Coronavirus (COVID -19) Disease Cues from Chest Radiography Images

This paper proposes a deep learning-based approach to detect COVID-19 infections in lung tissues from chest Computed Tomography (CT) images. A two-stage classification model is designed to identify the infection from CT scans of COVID-19 and Community Acquired Pneumonia (CAP) patients. The proposed neural model named, Residual C-NiN uses a modified convolutional neural network (CNN) with residual connections and a Network-in-Network (NiN) architecture for COVID-19 and CAP detection. The model is trained with the Signal Processing Grand Challenge (SPGC) 2021 COVID dataset. The proposed neural model achieves a slice-level classification accuracy of 93.54% on chest CT images and patient-level classification accuracy of 86.59% with class-wise sensitivity of 92.72%, 55.55%, and 95.83% for COVID-19, CAP, and Normal classes, respectively. Experimental results show the benefit of adding NiN and residual connections in the proposed neural architecture. Experiments conducted on the dataset show significant improvement over the existing state-of-the-art methods reported in the literature. © 2022 ACM.

SARS-COV-2 Infection in Children and Young People in Bulgaria - A Prospective, Single-Center, Cohort Study

Compared to other respiratory viruses, the proportion of hospitalizations due to SARS-CoV-2 among children is relatively low. While severe illness is not common among children and young individuals, a particular type of severe condition called multisystem inflammatory syndrome in children (MIS-C) has been reported. The aim of this prospective cohort study, which followed a group of individuals under the age of 19, was to examine the characteristics of patients who had contracted SARS-CoV-2, including their coexisting medical conditions, clinical symptoms, laboratory findings, and outcomes. The study also aimed to investigate the features of children who met the WHO case definition of MIS-C, as well as those who required intensive care. A total of 270 patients were included between March 2020 and December 2021. The eligible criteria were individuals between 0-18 with a confirmed SARS-CoV-2 infection at the Infectious Disease Hospital "Prof. Ivan Kirov"in Sofia, Bulgaria. Nearly 76% of the patients were <= 12 years old. In our study, at least one comorbidity was reported in 28.1% of the cases, with obesity being the most common one (8.9%). Less than 5% of children were transferred to an intensive care unit. We observed a statistically significant difference in the age groups, with children between 5 and 12 years old having a higher likelihood of requiring intensive care compared to other age groups. The median values of PaO2 and SatO2 were higher among patients admitted to the standard ward, while the values of granulocytes and C-reactive protein were higher among those transferred to the intensive care unit. Additionally, we identified 26 children who met the WHO case definition for MIS-C. Our study data supports the evidence of milder COVID-19 in children and young individuals as compared to adults. Older age groups were associated with higher incidence of both MIS-C and ICU admissions.Copyright © 2023 P. Velikov et al., published by Sciendo.

The association between the elevated serum levels of cardiac Trop I and mortality in patients with and without pre-existing CAD in COVID-19 patients: A retrospective observational study

Background: COVID-19 has appeared as a pandemic and public health issue at a universal level. First documented as a respiratory disease, COVID-19 has been found to interrelate with and disturb the cardiovascular system causing myocardial injury and also cardiac dysfunction. Initial documentation of cardiac pathology can play a substantial role in dropping the death rate. This study emphasizes on the relationship between the serum levels of cardiac Trop I and prognosis in patients with and without pre-existing CAD in COVID-19 patients. Aims and Objectives: The first objective was to explore the association among the serum levels of cardiac Trop I and bad prognosis in patients with antiquity of CAD and without CAD. The secondary objective was to explore and understand whether increased Trop I is an appreciated prognostic indicator for COVID-19 patient antagonistic prognosis. Material(s) and Method(s): This was conducted as a retrospective observational study in which a whole of 45 patients admitted in COVID Hospital of Malabar Medical College and Research Center category C were studied. The medical record of the patients whose COVID-19 confirmation done by combined conclusions of reverse transcription PCR, symptoms, and chest X-ray was studies by the team. Result(s): Mean age of the study participants was 59.3 +/- 13.7. Every study participants had elevated Trop I levels with a median Trop I in study subjects being 397.9. There was a statistically significant elevation in Trop I levels in patients with CAD linked with non-CAD patients with a median IQR of 641.6 and P = 0.003 and there was a significant increase in Trop I levels in patients who expired related to patients who got discharged with a median IQR of 587.3 and P = 0.003. Conclusion(s): From this study, we accomplish that rise in cardiac troponin-I level is connected with elevated mortality in patients with COVID-19. Hence, it can be used as significant biomarker of disease evolution, hospitalization, and worse prognosis in COVID-19 patients.Copyright © 2023, Mr Bhawani Singh. All rights reserved.

Assessment of palliative approach in the pain management in endodontic emergencies during Covid-19 outbreak: Retrospective cohort study

Aim: During the coronavirus disease, a palliative approach was recommended for the management of endodontic emergencies. This retrospective cohort study was conducted to investigate the effectiveness of dexamethasone or ibuprofen-acetaminophen combination for pain management in endodontic emergencies. Material(s) and Method(s): One hundred and eight records of patients who presented to the emergency department with dental pain were evaluated retrospectively. Since interventional procedures were not performed during the pandemic period, Specific analgesics/antibiotics for the management of pain were preferred. A follow-up protocol with a questionnaire was developed to observe the effectiveness of palliative treatment and make changes if necessary. All participants received a questionnaire to rate the pain levels 6, 12, 18, 24, 48, and 72 hours after taking the drug. All data were collected from the patient file and assessed. After inclusion and exclusion criteria, 32 patients were included (n = 19, ibuprofen + acetaminophen;n = 13, dexamethasone). Data were analyzed using the chi-square test (P = 0.05). Result(s): In both groups, a significant decrease in pain was experienced immediately after medication and at 6, 12, and 18 hours, with no significant difference (P >.05). However, dexamethasone (Group II) resulted in lower pain levels than ibuprofen\acetaminophen (Group I) at 24 and 48 hours (P <.05) Discussion: Both dexamethasone and ibuprofen-acetaminophen can be good palliative choices in endodontic emergencies in pandemic conditions. However, at 24 and 48 hours, dexamethasone resulted in lower pain levels.Copyright © 2022, Derman Medical Publishing. All rights reserved.

Assessing Robustness of a Deep Learning Model for COVID-19 Classification on Chest Radiographs

The COVID-19 pandemic has made a dramatic impact on human life, medical systems, and financial resources. Due to the disease's pervasive nature, many different and interdisciplinary fields of research pivoted to study the disease. For example, deep learning (DL) techniques were employed early to assess patient diagnosis and prognosis from chest radiographs (CXRs) and computed tomography (CT) scans. While the use of artificial intelligence (AI) in the medical sector has displayed promising results, DL may suffer from lack of reproducibility and generalizability. In this study, the robustness of a pre-trained DL model utilizing the DenseNet-121 architecture was evaluated by using a larger collection of CXRs from the same institution that provided the original model with its test and training datasets. The current test set contained a larger span of dates, incorporated different strains of the virus, and included different immunization statuses. Considering differences in these factors, model performance between the original and current test sets was evaluated using area under the receiver operating characteristic curve (ROC AUC) [95% CI]. Statistical comparisons were performed using the Delong, Kolmogorov-Smirnov, and Wilcoxon rank-sum tests. Uniform manifold approximation and projection (UMAP) was used to help visualize whether underlying causes were responsible for differences in performance between test sets. In the task of classifying between COVID-positive and COVID-negative patients, the DL model achieved an AUC of 0.67 [0.65, 0.70], compared with the original performance of 0.76 [0.73, 0.79]. The results of this study suggest that underlying biases or overfitting may hinder performance when generalizing the model. © 2023 SPIE.

A Deep Ensemble Model for Differential Diagnosis of Covid-19 Pneumonia using Thoracic Radiography

The successful elimination of the SARS-Cov2 virus has evaded the society and medical fraternity to date. Months have passed but the virus is still very much present amongst us though its severity and contagiousness have decreased. The pandemic which was first detected in Wuhan, China in late 2019 has had colossal ramifications for the societal, financial and physical well-being of humankind. Timely detection and isolation of infected persons is the only way to contain this contagion. One of the biggest hurdles in accurately detecting Covid-19 is its similarities to other thoracic ailments such as Lung cancer, bacterial and viral Pneumonia, tuberculosis and others. Differential observation is challenging due to identical radioscopic discoveries such as GGOs, crazy paving structures and their combinations. Thorax imaging such as X-rays(CXR) have proven to be an efficient and economical diagnostics for detecting Covid-19 Pneumonia. The proposed work aims at utilising three CNN models namely Inception-V3, DenseNet169 and VGG16 along with feature concatenation and Ensemble technique to correctly predict Covid-19 Pneumonia from Chest X-rays of patients. The Covid-19 Radiography dataset, having a total of 4839 CXR images, has been employed to evaluate the proposed model and accuracy, precision, recall and F1-Score of 97.74%, 97.78%, 97.73% and 97.75% has been obtained. The proposed system can assist medical professionals in detecting Covid-19 from a host of other pulmonary diseases with a high probability. © 2023 IEEE.

Bilateral Spontaneous Pneumothorax in a Child with Multisystem Inflammatory Syndrome Associated with COVID-19

Introduction: Spontaneous pneumothorax is a rare complication of coronavirus disease 2019 (COVID-19), primarily reported in adults. Pediatric cases with bilateral pneumothorax are much less reported. Case Presentation: We presented the case of a five-year-old previously healthy boy who developed persistent fever, abdominal pain, generalized maculopapular rash, and dyspnea before admission. His chest computed tomography (CT) showed a viral involvement pattern of pneumonia suggestive of COVID-19. Subsequently, he was confirmed with multisystem inflammatory syndrome in children (MIS-C). While he responded well to the therapies, on the fifth day of admission, he developed respiratory distress again. A chest roentgenogram showed bilateral spontaneous pneumothorax. Bilateral chest tubes were inserted, and his condition improved sig-nificantly after five days of admission to the intensive care unit. Two weeks later, he was discharged in good condition. Conclusion(s): Children with MIS-C associated with COVID-19 may develop primary spontaneous pneumothorax. Owing to the clinical picture overlapping with MIS-C associated with COVID-19, the timely diagnosis of pneumothorax may be challenging in such patients.Copyright © 2022, Author(s).

Liver biomarkers for prognosis in COVID-19

The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).Mortality attributable to COVID-19 remains considerably high, with case fatality rates as high as 8-11%. Early medical intervention in patients who are seriously and critically ill with COVID-19 reduces fatal outcomes. Thus, there is an urgent need to identify biomarkers that could help clinicians determine which patients with SARS-CoV-2 infection are at a higher risk of developing the most adverse outcomes, which include intensive care unit (ICU) admission, invasive ventilation, and death. In COVID-19 patients experiencing the most severe form of the disease, tests of liver function are frequently abnormal and liver enzymes are found to be elevated. For this reason, we examine the most promising liver biomarkers for COVID-19 prognosis in an effort to help clinicians predict the risk of ARDS, ICU admission, and death at hospital admission. In patients meeting hospitalization criteria for COVID-19, serum albumin < 36 g/L is an independent risk factor for ICU admission, with an AUC of 0.989, whereas lactate dehydrogenase (LDH) values > 365 U/L accurately predict death with an AUC of 0.943.The clinical scores COVID-GRAM and SOFA that include measures of liver function such as albumin, LDH, and total bilirubin are also good predictors of pneumonia development, ICU admission, and death, with AUC values ranging from 0.88 to 0.978.Thus, serum albumin and LDH, together with clinical risk scores such as COVID-GRAM and SOFA, are the most accurate biomarkers in the prognosis of COVID-19.Copyright © 2021 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.

A Review on the Effect of COVID-19 in Pregnant Women

Coronavirus Disease 2019 (COVID-19) is an emerging disease with a rapid increase in cases and deaths since its first discovery in December 2019, in Wuhan, China. Limited data are available on COVID-19 effects during pregnancy;however, information on diseases associated with other highly pathogenic coronaviruses (i.e. Severe Acute Respiratory Syndrome [SARS] and the Middle East respiratory syndrome [MERS]) may provide insight into the effects of COVID-19 during pregnancy. Coronaviruses cause illnesses ranging from the common cold to severe respiratory disease and death. The data indicate an average of 5 days incubation period (range: 2-14 days). The average age range of the hospitalized patients was 49-56 years, and a third to half of them have an underlying illness. Children were rarely mentioned. Within hospitalized cases, men were more frequent (54%-73%). Fever, cough, myalgia, vomiting, and diarrhea are common symptoms. This review aims at giving an in-depth understanding of COVID-19 by comparing its effects with SARS and MERS to evaluate its severity in pregnant women1. The results of varied studies show that COVID-19 affects pregnant women seriously and there is an alarming need to look into this aspect to prevent its harmful effects on the fetus.Copyright © 2020

Anaesthetic Management for A Patient Presenting for Caesarean Delivery with A giant Thymoma - A Case Report

Presentation of a thymoma during pregnancy means that safe delivery becomes more challenging. We present a 33-year-old pregnant woman who was diagnosed with a large thymoma causing marked compression of the tracheobronchial tree and right atrium. After various multidisciplinary meetings she presented for elective caesarean section delivery at 31 weeks of gestation. A combined spinal-epidural anaesthesia was performed, along with colloid pre-and co-loading, and vasopressor support. The delivery was uneventful. The possibility of catastrophic complications was foreseen. Therefore, all requirements for the possibility of airway or haemodynamic collapse were planned carefully, including the possibility of emergent cardiopulmonary bypass.Copyright © 2023, College of Anaesthesiologists of Sri Lanka. All rights reserved.

Chest X-ray Imaging System for Early Detection of Tuberculosis

Today it is observed that few people respect the biosecurity measures announced by the WHO, which aimed to reduce the amount of COVID-19 infection among people, even knowing that this virus has not disappeared from our environment, being an unprecedented infection in the world. It should be noted that before this pandemic, tuberculosis affected millions of people, having a great role because it is highly contagious and directly affects the lungs, although it has a cure, if it is not treated in time it can be fatal for the person, although there are many methods of detection of tuberculosis, one that is most often used is the diagnosis by chest x-ray, although it has low specificity, when the image processing technique is applied, tuberculosis would be accurately detected. In view of this problem, in this article a chest X-ray image processing system was conducted for the early detection of tuberculosis, helping doctors to detect tuberculosis accurately and quickly by having a second opinion by the system in the analysis of the chest x-ray, prevents fatal infections in patients. Through the development of the tuberculosis early detection system, it was possible to observe the correct functioning of the system with an efficiency of 97.84% in the detection of tuberculosis, detailing the characteristics presented by normal or abnormal images so that the doctor detects tuberculosis in the patient early. © 2023 IEEE.

CovidXNet: An Ensemble of Deep Neural Networks for Non-invasive Binary Identification of COVID-19 through Chest Radiographs

This study compared five different image classification algorithms, namely VGG16, VGG19, AlexNet, DenseNet, and ConVNext, based on their ability to detect and classify COVID-19-related cases given chest X-ray images. Using performance metrics like accuracy, F1 score, precision, recall, and MCC compared these intelligent classification algorithms. Upon testing these algorithms, the accuracy for each model was quite unsatisfactory, ranging from 80.00% to 92.50%, provided it is for medical application. As such, an ensemble learning-based image classification model, made up of AlexNet and VGG19 called CovidXNet, was proposed to detect COVID-19 through chest X-ray images discriminating between health and pneumonic lung images. CovidXNet achieved an accuracy of 97.00%, which was significantly better considering past results. Further studies may be conducted to increase the accuracy, particularly for identifying and classifying chest radiographs for COVID-19-related cases, since the current model may still provide false negatives, which may be detrimental to the prevention of the spread of the virus. © 2022 IEEE.

Should Young Covid-19 Patients be Suplemented with Vitamin D?

It is well known that vitamin D's general immunomodulatory actions are helpful in viral infections and that a shortage is linked to a more serious prognosis for Covid-19. In this sistematic review, we examined the existing literature on evidence as to whether there is also link between vitamin D range levels in pediatric population and the outcome of the Covid-19 infection. We looked for studies that measured vitamin D blood concentrations and examined the effects of vitamin D supplementation in young infected patients. Vitamin D may decrease the risk of respiratory infections in a number of ways through its interactions with numerous cells, including by decreasing viral survival and replication, reducing the cytokine storm, raising angiotensin-converting enzyme 2 concentrations (ACE2) while not damaging the endothelial integrity. The incidence or severity of Covid-19 is linked with blood 25-hydroxyvitamin D concentrations, according to many observational studies. However experimental verification is still needed. Given their safety and broad therapeutic window, vitamin D supplements seem to be an effective way for individuals and doctors to prevent or treat Covid-19. Nonetheless, the outcomes of significant vitamin D randomized controlled trials are further needed.Copyright © 2022 Maria Nicolae et al., published by Sciendo.

Research COVID-19 and its Outcomes in Multiple Sclerosis Patients

Background: Coronavirus Disease 2019 (COVID-19) is a highly contagious disease that resulted in 4533645 deaths until September first, 2021. Multiple Sclerosis (MS) patients receive immunosuppressive drugs. Thus, there is a concern that these drugs will reduce the patient's immune system resistance against COVID19. Objective(s): This study aimed to evaluate the epidemiology of COVID19 and its impact on MS patients in our university hospital in Tehran City, Iran. Material(s) and Method(s): A cross-sectional study was conducted based on hospital-based registry data from May 2020 to March 2021. Among more than 500 registered MS patients in Imam Khomeini Hospital in Tehran City, Iran, referring within our study period, 84 patients reported SARS-COV2 infection. The diagnosis of MS was confirmed by the McDonald criteria. Moreover, the diagnosis of COVID-19 in MS patients was established by the real-time-PCR technique and chest computed tomography. Result(s): Out of 84 MS patients with SARS-COV2 infection, 55(65.5%) were women, and their mean age was 37.48 years. The most commonly used medications by MS patients were Rituximab 20 (26.3%) and Dimethyl Fumarate 14(18.4%). Totally, 9(10.8%) of the patients needed to be hospitalized due to COVID-19, with a mean hospitalization duration of 5.88 days. A total of 1 (1.2%) death was reported. Conclusion(s): Compared to the healthy population, COVID-19 is not more serious in MS patients. Most MS patients with COVID-19 infection were not hospitalized and continued their medication during the infection.Copyright © 2022 The Authors. This is an open access article under the CC-By-NC license. All Rights Reserved.

Assessing the clinical manifestations, laboratory and radiological findings of hospitalization of pediatrics patients with COVID-19 in pediatric hospital of Amirkola, Babol

Variant Omicron was discovered as a newest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first emergence of the omicron variant was detected in November 2021. In this study, we investigated the clinical manifestation, laboratory and radiological findings and responding to treatment of 70 pediatric patients with positive RT- PCR COVID-19 in Omicron peak. We described 20 criteria associated with efficacy, such as demographic data, clinical manifestation, laboratory and radiological findings. All of the patients received Remdesivir that 5.7% of patients responded to the treatment. No patients were given Intravenous Immunoglobulin (IVIG). This is the first study aimed at assessing symptoms clinical manifestation among hospitalization pediatrics patients in pediatric Hospital of Amir kola, Babol. The findings of this study can be effective in preventing and controlling disease transmission among children.

Report of the Association Between Multisystem Inflammatory Syndrome and Severe Myocarditis

Introduction: The people worldwide have been affected by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection since its appearance in December, 2019. Kawasaki disease-like hyperinflammatory shock associated with SARS-CoV-2 infection in previously healthy children has been reported in the literature, which is now referred to as a multisystem inflammatory syndrome in children (MIS-C). Some aspects of MIS-C are similar to those of Kawasaki disease, toxic shock syndrome, secondary hemophagocytic syndrome, and macrophage activation syndrome. Case Presentation: This study reported an 11-year-old boy with MIS-C presented with periorbital and peripheral edema, abdominal pain, elevated liver enzymes, severe right pleural effusion, moderate ascites, and severe failure of right and left ventricles. Conclusion(s): Due to the increasing number of reported cases of critically ill patients afflicted with MIS-C and its life-threatening complications, it was recommended that further studies should be carried out in order to provide screening tests for myocardial dysfunction. Adopting a multidisciplinary approach was found inevitable.Copyright © 2023, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

Ultrasound of Covid 19

We present how we used ultrasound to improve our diagnosis of lung Covid 19 and use ultrasound to diagnose the complications of Covid 19. Ultrasound was more sensitive in detecting early Covid 19 than chest radiograph. The complications of Covid 19 include renal impairment, liver impairment and vascular complications, mainly large vessel venous thrombosis, including renal vein thrombosis. We are all suffering from post-viral fatigue but lessons can be learnt from this pandemic and the use of ultrasound.