Mathematical Morphology Adopted Automatic Detection of Ground Glass Opacities in Lung CT Images of COVID-19 Patients

The severity of the nCOVID infection relies on the presence of Ground Glass Opacities (GGO) present in the patient's chest CT scan images. Although, detecting and delineating the precise boundaries of GGO in the chest CT images is challenging. Here, we proposed a fast and novel technique to automatically segment the regions containing GGO in lung CT images using mathematical morphology. We have tested our algorithm on the chest CT images of 145 Covid-positive cases. This unique segmentation approach correctly segments the lung field from chest CT images and identifies GGO with average sensitivity, specificity, and accuracy of 96.89%, 95.23%, and 97.22%, respectively. We used expert radiologists' hand-curated segmentation of GGO as ground truth for quantificational performance analysis. Our research results indicate that this algorithm performs well found in the literature. © 2023 IEEE.

Introduction—Epigenetics regulations in organ specific disorders

Epigenetics is used to explain stable heritable chemical modifications to DNA and histones that affect gene expression without changing nucleotide sequence. The genetic expression of a trait in an organism can be moderated by epigenetics depending on the prevailing environmental conditions and activate different traits from the same genotype via modulating gene expression patterns. Several diseases can control or get influenced by the epigenome. A recent surge in research is focused on decoding such changes as early indicators of diseases. SARS-CoV-2, responsible for the worldwide pandemic, is also suggested to rattle the epigenetic network, impacting the host immune system negatively. While epigenetic drugs have majorly been studied in treating cancer, the increasing funding and interest have paved the way for the researchers to focus on other inflammatory diseases. The primary focus of this book has been to delineate the role of epigenetics in regulating disorders affecting organs in our body. © 2023 Elsevier Inc. All rights reserved.

Futuristic Rehabilitation Technique Of Acquired Maxillectomy Defect In Post Covid19 Mucormycosis Using Polyether Ether Ketone Obturator Prosthesis- A Case Report

Background: Oroantral communication can occur due to maxillectomy defects, jeopardizing the integrity and function of oral cavity. It is an interdisciplinary challenge to restore these by surgery and prosthetics since many facets need to be addressed, such as speech, deglutition, mastication, aesthetics and psychological distress. Rationale: Surgical repair of maxillectomy defects is not always achievable due to various reasons such as poor systemic health, advanced age etc. Thus prosthetic rehabilitation becomes the most suitable treatment option. Relevance for Patients: Post COVID-19 mucormycosis has seen a surge in the past two years. It is an opportunistic fungal infection in humans infecting intracranial structures by direct invasion in the blood stream. Fundamental goal of prosthetic rehabilitation is the closure of oronasal communication and restoring it functionally thereby improving quality of life for the patient. CAD/CAM (computer aided design/computer aided milling) technology was employed to fabricate a milled framework for maxillary obturator in the most innovative way using PEEK (Polyether ether ketone). Result(s): PEEK material due to its excellent biocompatibility ensured a light weight prosthesis for the large maxillectomy defect and closure of the patency was achieved by the obturator framework.Copyright © 2022 Authors. All rights reserved.

POSITIVE IMPACT ON ENVIRONMENT DUE TO COVID-19 LOCKDOWNS IN PARTS OF INDIA: A REVIEW

Due to the pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) commonly known as COVID-19, a nationwide lockdown came into effect in India from 24th March midnight, 2020, which slowed down the movement of vehicles, operation of industries etc. Due to this reason a drastic change in the environment occurred and it caused the reduction of pollution level in the environment. The study mainly focuses on the positive impacts of lockdown in India. Studies have shown that after the implementation of lockdown, the level of the various major air pollution constituents of such as particulate matter (PM2.5, PM10, etc.), NO2, CO and ozone etc. in the air has reduced substantially. The air quality index data have clearly shown the difference in the level of air pollution between the year 2019 and 2020. The study was mainly focused on the comparison of air quality parameters such as particulate matter, NO2, CO and ozone etc. as well as the water pollution parameters such as Biochemical oxygen demand (BOD), chemical oxygen demand (COD) and dissolved oxygen (DO) for the River Yamuna and it was observed that there was substantial amount of positive change in pollutants after lockdown compared to what was before lockdown. The observations are carried out in atime frame manner such as before lockdown and after lockdown and results have been found with a huge difference in reduction of air pollution as well as water pollution.

Analysis of Contrast and Correlation between Deep Learning Algorithms for Diagnosis of COVID 19 from Lung Ultrasonography

Although identification of COVID-19 in patients from chest Computed Tomography (CT) scan has been the most prevalent approach, it exposes the patient to X-ray radiations and is not a suitable approach for frequent monitoring. Computer analysis of ultrasound pulmonary images is a relatively modern approach that shows promising ways to diagnose pulmonary states, which is a profitable and safer alternative to CT scan. Deep learning techniques for computerized study of Lung Ultrasound (LUS) images offer promising opportunities for identifying and diagnosing COVID-19. This paper aims to bring up a Convolution Neural Networking (CNN) model, which accurately predicts the condition of COVID-19 via the output produced lung ultrasound. Three models were developed using various parameters and were tested on the same dataset in order to compare each on standard statistical procedures. The best model achieved an accuracy of 94.67%, sensitivity 55% and specificity of 60% on the test data. © The Electrochemical Society

Subcutaneous Sarilumab for the Treatment of Hospitalized patients with Moderate to Severe COVID19 Disease: A Pragmatic, Embedded, Multi-Center Randomized Clinical Trial

Background. The aim of this pragmatic, embedded adaptive trial was to measure the effectiveness of subcutaneous sarilumab in addition to an evolving standard of care for clinical management of inpatients with moderate to severe COVID-19 disease (NCT04359901). The study is also a real-world demonstration of the realization of a prospective learning healthcare system. Methods. Two-arm, randomized, open-label controlled 5-center trial comparing standard care alone to standard care (SOC), which evolved over time, with addition of subcutaneous sarilumab (200 mg or 400 mg anti-IL6R) among hospitalized patients with moderate to severe COVID-19 not requiring mechanical ventilation. The primary outcome was 14-day incidence of intubation or death. The trial used a randomized play-the-winner design and was fully embedded within the EHR system, including the adaptive randomization process. Results. Among 417 patients screened, 162 were eligible based on chart review, 53 consented, and 50 were evaluated for the primary endpoint of intubation or death ( >30% of eligible patients enrolled) (Figure 1). After the second interim review, the unblinded Data Monitoring Committee recommended that the study be stopped due to concern for safety: a high probability that rates of intubation or death were higher with addition of sarilumab to SOC (92.6%), and a very low probability (3.4%) that sarilumab would be found to be superior. Conclusion. This randomized trial of patients hospitalized with COVID-19 and requiring supplemental oxygen but not mechanical ventilation found no evidence of benefit from subcutaneous sarilumab in addition to an evolving standard-of-care. The numbers of patients and events were too low to allow independent conclusions to be drawn, but this study contributes valuable information about the role of subcutaneous IL-6 inhibition in the treatment of patients hospitalized with COVID-19. The major innovation of this trial was the advancement of embedded, point-of-care clinical trials for FDA-approved drugs;this represents a realization of the learning healthcare system. Methods developed and piloted during the conduct of this trial can be used in future investigations to speed the advancement of clinical science.

The Latent Tuberculosis Infection Cascade of Care during the COVID-19 Pandemic Response in a Mid-Sized US City

Background. The COVID-19 pandemic response may unintendedly disrupt multiple public health services, including tuberculosis control programs. We aimed to assess the cascade of care of latent tuberculosis infection (LTBI) in an urban US city during the COVID-19 pandemic response. Methods. We conducted a retrospective cohort study of adult patients who presented for LTBI evaluation at the Hamilton County Public Health Tuberculosis Clinic in Ohio between 2019 and 2020. We defined 01/2019 to 02/2020 as the pre-COVID-19 response period, and 04/2020 to 12/2020 as the COVID-19 pandemic response period. We reviewed electronic medical records and extracted sociodemographic information, medical history, and follow-up and treatment data to define steps within the LTBI cascade of care. Logistic regressions were used to assess factors associated with LTBI treatment acceptance and completion, adjusted by potential confounders and COVID-19 period. Results. Data from 312 patients were included. There was a significant decrease in the number of monthly LTBI referrals (median, 18 vs. 8, p=0.02) and LTBI evaluations (median, 17.5 vs. 7, p< 0.01) during COVID-19. There was a decrease in the proportion of immigrants as indication for LTBI testing (30% vs. 9%;p< 0.01), and an increase in LTBI diagnoses based on interferon-gamma release assay (IGRA;30% vs. 49%;p< 0.01) during COVID-19. The proportion of people who were recommended LTBI treatment was similar before and during COVID-19 (76% vs. 81%, p=0.41), as well as the LTBI treatment acceptance rates (56% vs. 64%, p=0.28), and LTBI treatment completion rates (65% vs. 63%, p=0.85). In multivariate analysis, LTBI treatment acceptance was associated with Hispanic ethnicity, younger age, male sex, IGRA use, no comorbidities, and non-healthcare occupation, independent of COVID-19 period. LTBI treatment completion was associated with taking a rifamycin-containing regimen, independent of COVID-19 period. Conclusion. We observed a significant decline in the number of monthly LTBI referrals and evaluations during COVID-19. Our findings indicate an unintended negative impact of the COVID-19 response in LTBI screening efforts in our region. LTBI treatment acceptance and completion rates were not affected during COVID-19.

Teleconsultations for rheumatic diseases during CoVID-19 pandemic: Usefulness, patient response and prospects for future practice

Background/Purpose: Teleconsultations have been an important means of communicating with the patients due to the travel restrictions during the COVID-19 pandemic. We assessed its usefulness and patients' views on their future use. Methods: Patients who received teleconsultations using telephone and WhatsApp during the COVID-19 pandemic were screened and asked to fill an online questionnaire seeking their views regarding teleconsultations in terms of their usefulness, cost-effectiveness, feasibility for future use. Only those patients were included who were of age ≥18 years and had had at least 2 physical visits in the past at our hospital. Information regarding their demographic features, disease characteristics like diagnosis, duration of disease was also collected. For the final analysis, 230 responses out of the 410 participants were included for who all the desired information was available. Results: Among the 230 patients, mean age was 38 years with a mean duration of disease of 4.25 years, 68 (29%) were male, 190 (83%) had rheumatoid arthritis, 100 (43%) patients assessed their disease condition as bad/severe and 90 (39%) depended on others to use a smartphone for teleconsultations. Among these patients, 131 (57%) patients missed their scheduled OPD appointment, 115 (50%) reported worsening of symptoms, 81 (35%) needed to consult a local physician for their problems. Regarding teleconsultations, 142 (62%) patients reported benefit with the teleconsultation service and 181 (79%) graded it ≥3 on a scale of 1-5 where 5 meant very useful (Figure 1). A total of 161 (70%) patients wanted to use it for future consultations. The commonest reasons for choosing teleconsultation were ease of appointment (52%), avoiding the need of travelling (22%) and cost-effectiveness (22%). Conclusions: Teleconsultation is a useful alternative to physical consultation with a high satisfaction rate. It could be a useful costeffective tool in a resource limited setting of developing countries like India.

Understanding peoples’ sentiment during different phases of COVID-19 lockdown in India: A text mining approach

During a global pandemic like COVID-19, the success of governmental policies depends on the people’s sentiments and extended cooperation towards these policies. Therefore, this study explores the prevalent discourse in social media about different aspects of the COVID-19 pandemic and the policies to manage and control it. Data from Twitter collected between 25 March 2020 and 1 July 2020 was used for topic modelling and sentiment analysis. Natural language processing-based text mining techniques were used for analysis. This study first identified different frequent COVID-19related topics and then analyzed how the sentiments towards these topics differ across different phases of lockdown. Further, insights into how different topics were perceived by gender and age group are also discussed in this study. Finally, this study also analyzed how daily casualty due to COVID-19 influenced the public sentiments and number of daily tweets. The study provides a robust NLP-based text mining framework to predict the people’s sentiment during COVID-19 lockdown in India. The insights presented in this study can help the authorities mitigate the COVID-19 pandemic effectively and help different agencies in the face of similar pandemics in the future. Copyright © 2021, IGI Global.

The First Reported Case of COVID-19 Myocarditis Managed with Biventricular Impella Support

Introduction SARS-CoV-2, responsible for COVID-19, is a pandemic that has taken the world by storm. We present the only contemporary reported case of COVID-19 myocarditis leading to recovery with utilization of biventricular impella for temporary mechanical circulatory support. No cases have been reported regarding utilization of Bi-V impella as therapy for management of SARS-CoV-2.. Case Report We present a 35 year old-woman with history of systemic sclerosis who was found to have 5 days of generalized malaise associated with fevers and cough. On arrival she was found tachycardic at 112 bpm and febrile 101.8 F. She tested positive for COVID-19 via nasal CPR. Cardiac enzymes were found elevated on admission with troponin T elevated at 0.28. On day two of hospitalization patient had spontaneous PEA arrest secondary to hypoxemia. Transthoracic echocardiogram(TTE) revealed EF <10% and RV impairment which compare to prior which had normal ejection fraction. Labs showed elevated lactic acidosis of 10. Invasive hemodynamics assessment RA 21 mmHg, PA 32/23(mean 26 mmHg) and PCWP 18 mmHg. Calculated PAPi 0.76, CO 2.1 L/min and CI of 1.2 L/min/m