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Early detection of pneumonia in patients through effective medical imaging may enable timely remedial measures and reduce the severity of the infection. There is an increase in cases among new-borns, teenagers and also people with health issues in recent years. The COVID-19 pandemic also revealed the major impact pneumonia had on the lungs and the consequences of delayed detection. The presence of the infection in the lungs is examined through images of Chest X-ray, however, for an early diagnosis of the infection, this paper proposes an automated model as a more effective alternative. Convolutional Vision Transformer (CVT) which gives an accuracy of 97.13%, and is a robust combination of Convolution and Vision Transformer (ViT), is suggested in this paper as a potential model to detect pneumonia early in patients. © 2022 IEEE.
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Covid Security System is a non-contact sanitizer dispenser, that also monitors vital parameters such as temperature, heart rate, and spo2 sensors based on Internet of Things (IOT) data collection and processing. This device is vital in workplaces like hospitals, colleges, and many more. The system that has the capability to record human body temperature based on contactless mechanism efficiently with pandemic situation has looked up to usage of infrared thermometers. In this paper via our research we realize the human body temperature fast non-contact by utilizing infrared thermometer (MLX90614) along with a pulse oximeter using a pulse sensor (MAX30100) to measure the heart rate in real-time. Parameter like the oxygen level of the user is also rendered and stored on our designed IOT processing framework which can provide alerts both online or offline based on previous maintained records. In this research we have recorded parameters of the sample space comprising of 500 users. The main aspect of the research is the cost affectability where is the system can be easily interfaced with any existing framework of workplaces.
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Introduction: Left ventricular (LV) thrombus is a known complication of myocardial infarction (MI) and it usually occurs in areas of poorly contracting LV muscle as a result of endocardial injury with associated inflammation. There is a high risk of embolization within 3 months among patients with MI complicated by mural thrombus and this risk is maximum during the first 1-2 weeks. We report a case series of five patients who presented with acute coronary syndrome with LV apical thrombus and treated with triple anti-thrombotic therapy of rivaroxaban, aspirin, and clopidogrel. Case Series: Our series involves 5 cases who developed LV apical thrombus after acute coronary syndrome. Four patients had anterior wall ST-elevation MI (STEMI) whereas 1 patient had inferior wall STEMI. One of the patients with anterior STEMI also had COVID pneumonitis. All of these patients received triple anti-thrombotic therapy consisting of tab Aspirin 75 mg OD, tab clopidogrel 75 mg OD, and tab rivaroxaban 20 mg OD for 3 months duration. Repeat ECHO after 3 months showed complete resolution of LV thrombus in all of our cases. Discussion: LV thrombus reported in STEMI patients is from 1.6% up to 39% in various studies. The incidence of LV thrombus is on decreasing trend as a result of modern revascularization strategies. The role of novel oral anticoagulants (NOACs) in treating LV thrombus is scant as compared to oral Vitamin K antagonists (VKAs) like warfarin. The current recommendation for anticoagulation in the presence of a LV thrombus after acute coronary syndrome is with VKAs for up to 6 months. Conclusion: Although there is uncertainty in decision-making regarding antithrombotic therapy, our case series demonstrate that triple antithrombotic therapy with NOACs results in resolution of LV thrombus without any additional bleeding events in patients presenting with acute coronary syndrome. NOACs have an advantage of not requiring PT/INR monitoring and have less bleeding complications. Further large-scale research or randomized controlled trials are needed to find the optimal therapies in such cases. © 2022 by the Author(s).
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Introduction: The COVID-19 pandemic has been a major public health concern throughout the world. Various ventures of vaccine candidates are being studied rigorously in this regard and one such candidate is the receptor binding domain (RBD) of spike protein which interacts with angiotensin converting enzyme 2 (ACE2) on the host cell's membrane. Exploiting this interaction, many scientists across the world attempted to develop mRNA vaccine against SARSCoV- 2. A major lacuna associated with mRNA vaccines is their delivery through a suitable carrier, especially given the stability issues associated with mRNA vaccines. Aims & Objectives: The aim of our research is to develop an efficient mode of delivery of the self-amplifying mRNA (saRNA) against COVID 19. We have developed small vesicles from erythrocyte ghosts, known as nanoerythrosomes, which are in the nanometre range and focussed on development of nanoerythrosomes for delivery of mRNA-based vaccines. Material(s) and Method(s): Nanoerythrosomes were prepared from erythrocytes using osmotic and ultrasonic frequency stress and loaded with saRNA vaccine candidate. Thereafter, the nanoerythrosomes were characterized using Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM) to confirm their homogeneity, integrity and size. The mRNA loaded nanoerythrosomes were used to deliver the mRNA in Vero E6 cells to evaluate its uptake. Result(s): The characterization of nanoerythrosomes using DLS and TEM revealed their size in the range of 100-200 nm. The delivery mediated by nanoerythrosomes was comparable to the Lipofectamine mediated uptake of saRNA indicating the excellent delivery efficacy of nanoerythrosomes. The added advantage of nanoerythrosomes mediated delivery is that they are rapidly taken up from blood by macrophages of the reticuloendothelial system (RES) that is present in liver, lung, and spleen. Thus the combination of saRNA and nanoerythrosomes can accelerate the uptake and antigen presentation in reticuloendothelial system and will provide an outstanding platform for the development of SARS-CoV2 vaccine. Conclusion(s): We developed a new approach to deliver mRNA vaccine candidates using nanoerythrosomes and successfully demonstrate its efficacy in vitro. This strategy can be further extended for the delivery of other vaccine candidates. (Figure Presented).
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Background: For rheumatoid arthritis (RA) patients, hydroxychloroquine (HCQ) is a staple treatment. Concerns about its cardiovascular safety have been raised after reports of its use and fatal arrhythmias in individuals with coronavirus illness 19. Aims and objectives: To examine the relationship between HCQ use and corrected QT (QTc) length in RA patients. Material(s) and Method(s): Hundred subjects (age >= 18 years) were studied after dividing them in to Cases (n=50;patients with RA taking HCQ) and Control (n=50;patients without RA not taking HCQ) at the Department of General Medicine of a tertiary care center in Madhya Pradesh. Patient characteristics and laboratory measures, including rheumatoid factor hemoglobin, white blood cells count, platelets, erythrocyte sedimentation rate (ESR), random blood sugar, urea, Creatinine, SGOT, SGPT, serum electrolytes, calcium, and magnesium level, were assessed. QTc length was obtained with the help of 12-lead ECG. Result(s): Incidence of QTc prolongation in patients with RA was 11%. Odds for prolonged QTc interval for patients with age >50 years was 3.500 (95% CI = 0.865-14.155), serum calcium <8 was 2.400 (95% CI = 0.540-10.666), and ESR >20 was 0.756 (95% CI = 0.640-0.892). A significant positive correlation was obtained between prolonged QTc with age (r=0.283;p=0.046). Conclusion(s): There is a significant increase in risk of QTc prolongation with the use of HCQ in patients with RA. Copyright © 2022, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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In the past two years, numerous researches are done on how lockdowns across the world affected air quality;however, less research is done on how geolocation, geo-climate, anthropogenic activities had such impacts. National and regional shutdowns at various lockdown phases are crucial for evaluating such impacts. The goal of the current study was to examine the effects of geographic location, geo-climate, and human activity on Particulate Matter (PM10 and PM2.5) concentration and air quality about COVID-19-induced lockdowns of Mumbai and Delhi, two economically significant megacities in India with contrasting climatic conditions. Based on the incidents where restricted economic activity led to lockdowns, the importance of meteorological and economic activity in controlling air quality was evaluated. To understand spatial distribution, variability, trend, consistency analysis and National Air Quality Index (NAQI) of PM10 and PM2.5 data were collected from the Central Pollution Control Board (CPCB) monitoring system. To account for variation in various urban morphological units and gauge their responses, dispersion analysis was used. Kernel Density Estimation (KDE) plots were used to study how PM affected NAQI. From the analysis, it was clear that (1) nationwide lockdown was more fruitful in Delhi while regional lockdown in Mumbai since air quality improvement rate was substantially high in Mumbai in regional lockdown, 2021, (2) Mumbai city maritime location and long open sea coast help to reduce pollution levels while Delhi's continental location is crucial for being higher pollution levels, (3) control of meteorological factors was not found very significant, however, it was found relatively greater in Delhi, (4) air quality was found to be extremely poor in industrial and commercial areas during unlocking periods, but sensitively greater improvement was also found during lockdown periods, indicating crucial anthropogenic impact on air quality, and (5) rate of air quality improvement was highly correlated with different economic contributors. As a result, this study came to the conclusion that conditions with controlled demand can improve the air quality.
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Background: The immune system defends the host against many harmful microorganisms. The immune system has developed to contain various specialized cell types, signaling molecules, and functional responses to deal with this wide range of threats. In Covid-19 infections immune system is the key component for prevention of the disease. Hospital admission and duration of stay due to covid 19 infection have a considerable physical, financial, and psychological burden for the individual, family, and country. Diet has been shown to have a vital role in boosting one's immunity. Non vegetarian diet is traditionally considered to be immunity boosting as it is rich in protein, vitamins, and micronutrients. Aims and objective: To study the effect of dietary pattern on duration of hospital stay in patients with respiratory Covid illness Material and Methods: This was a double blind retrospective cohort study comprising of 113 patients tested positive in RTPCR for SARS-CoV-2 and admitted at DCH located at super specialty hospital of Jayarogya Group of Hospitals, Gwalior, Madhya Pradesh, was studied retrospectively between July 2020 to October 2020. Patients were divided based on diet pattern into Group A (patients following a vegetarian diet;n=70) and Group B (patients following a non-vegetarian diet;n=43). The outcome was measured as the duration of hospital stay and comparison of diet type, age, and gender of patients. All these patients were discharge stable and case files of deaths were excluded. Non vegetarian diet was defined as inclusion of eggs, meet, fish in the routine diet whereas a vegetarian diet was exclusion of these items. Result: Out of 113 patients, most (61.94%) had a vegetarian diet, whereas 43 (38.06%) had a non-vegetarian diet. Duration of hospital stay was more in patients in Group A (10.71±5.5 days) than Group B (8.4± 4.7 days), p=0.0302. Hospital stay was longer (11.05 days) in older patients (>50 years) compared to younger patients (≤50 years) (9.2 days) (table 3). In Group A, hospital stay was longer in those with age >50 years (11.4 days) compared to those with age ≤50 (9.2 days). On the contrary, older patients had shorter hospital lengths (9.9 days) than younger patients (10.09 days) in Group B (p value =). Conclusion: A significantly shorter hospital stay was observed in patients of respiratory covid infection following a non-vegetarian diet with Covid-19 infection.
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Introduction: Pharmacovigilance (PV) is the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine related problem. Objective: In November 2021, the North American Society of Pharmacovigilance (NASoP), a Chapter of the International Society of Pharmacovigilance (ISoP), launched PV courses for the education of North American stakeholders, in collaboration with Eu2P academic institutions. Methods: The Am2P program (Am2P) follows WHO-ISoP Core Elements of a Comprehensive Modular Curriculum and subscribes to the Innovative Medicines Initiative (IMI) Education and Training quality standards, jointly developed by Eu2P and other IMI Education and Training projects to foster quality in lifelong learning and continuing professional development. Convenient online education in PV supports the mission of ISoP to foster PV scientifically and educationally and enhance the safe and proper use of medicines worldwide. Am2P was designed by experienced PV experts from multiple institutions within NASoP, in partnership with Eu2P instructors, to comprise North America-focused online courses that benefit from existing Eu2P material, education technology, and academic accreditation. Results: Am2P offers two academic options: the Certificate degree and the Short Course certificate of achievement in PV. Four modular course programs are available on the Am2P website (https://www. am2p-courses.com) providing education on core and specialized PV topics with a focus on North America: Basic Pharmacovigilance (PV) & PV regulations;PV for Biologics;External databases/Real World Data/Real World Evidence;Benefit-Risk assessment. Program approval is ensured by the Eu2P Executive Board including academic representatives of the 6 Eu2P degree-awarding universities. Am2P and Eu2P Certificate Courses hold the same academic value. A regular Certificate course involves 75h student workload over three months, recognized as 3 ECTS (European-Credit Transfer and Accumulation System) credits, equivalent to 1.5 American credits. Am2P Short Courses are bite-sized courses to provide or reinforce solid, current knowledge in PV focused on North America. Conclusion: Am2P is a partnership between NASoP and Eu2P to build a set of North America-focused online courses offered in PV. Am2P offers accredited PV training of the highest standard, focused on North America, as an extension of the Eu2P program. Online PV training addresses needs of new entrants to PV, and seasoned personnel.
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Deep learning approach for detecting various respiratory diseases hasbeen challenging and mostdemanding research area. Withrapidly increase in number of patients suffering from respiratory diseases quick method hasbecome necessary for classification and detection of respiratory diseases. This survey paper offers a comparative study of various deep learning techniques that can use chest X-raysfordetection of various thoracic diseases.There is possibility of severe respiratory failure in some thoracic diseases if they are not treated in initial stages. Many digital image processing techniques,machine learning and deep learning models have been developed for this purpose[17]. Different forms of existing deep learning techniques including convolutional neural network (CNN), visual geometry group based neural network (VGG-16 and VGG-19) have been developed for respiratory disease prediction. But these all models have some limitations that they do not cover all respiratory diseases including Covid-19, Viral pneumonia and Tuberoculosis on single platform. Therefore, we propose our customized new deep learning model Clx-Net by using data augmentation technique to enlarge the area of available dataset[1][2] to make model more efficient with less time consumption per epoch and provide localization to identify infected region by examining chest X-ray images. Our focus is to develop a new unique deep learning based model Clx-Net which will be able to detect almost all major respiratorydiseases including Covid-19. It will simplify the detection of respiratory diseases and also find the location of infected chest area to make task easy for radiologists.
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Background: Nearly 22% of children in Philadelphia live in foodinsecure (FI) households, often leading to reliance on inexpensive, nutrient-poor foods, and associated poor health outcomes. Eating patterns developed in childhood carry into adulthood, indicating the importance of early development of healthy eating behaviors. Conducted in partnership with our local WIC office, this study explores: 1) experiences with produce access among low-income families with young children in West Philadelphia, and 2) caregiver preferences for food assistance in order to inform future programming. Methods: We ed basic demographic and contact information from the electronic health record for families of children under the age of 5 from an urban, pediatric primary care center who are WIC-eligible. We recruited 30 caregivers to participate in semi-structured phone interviews to understand experiences with produce access and explore preferences for programs aimed at increasing produce consumption. All interviews were digitally recorded and transcribed. We used content analysis with constant comparison to code interviews inductively and identified emerging themes through an iterative process. Results: 30 caregivers with an average of 3 children per household and a 61% rate of FI participated in our qualitative study. A major theme that emerged from the data is a preference among caregivers for their children to eat more produce, although there were many barriers to produce access, including: limited availability, convenience, cost, difficulty shopping with young children, and time constraints. Barriers exacerbated by the COVID-19 pandemic included lack of childcare, decreased access to WIC benefits due to office closures, and fear of visiting stores. Owning a vehicle, and receiving both SNAP and WIC benefits improved ability to purchase produce. Features of an ideal food program included: delivery-based, wide variety of fruits and vegetables offered, ability to self-select produce, and inclusion of recipes and produce-oriented children's activities. Additionally, participants suggested that a program would be most helpful if free or covered by food benefits, but that a small fee may be appropriate for those able to afford it. Conclusion: Our study demonstrates desire for better access to fresh produce among WIC-eligible families, and highlights multiple barriers, which have been worsened by COVID-19. Caregivers described a preference for delivery-based, low-or-no cost food programs to increase produce access and intake among children.
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Ever since the COVID-19 pandemic, higher education witnessed a paradigm shift in the teaching-learning strategies everywhere from the original way where everything was largely conducted face-to-face. Teachers, educators, and students had to suddenly move to the virtual mode to continue their classes in schools, institutes, and universities. Recently, many published studies have revealed the utmost need to improve teaching strategies, particularly in an online lecture setting. However, the major impediment was observed in higher educational institutions (HEIs) where teachers had to conduct laboratory experiments in hard sciences, particularly in physics, chemistry and, biochemistry. Of these subjects taught in graduate classes, chemistry is a complex subject. A chemistry learner needs to acquire hands-on experience, especially when performing organic preparations and instrumental analyses. Chemistry teachers believed that nothing could ever replace a traditional laboratory setting, but now the situation has changed to a certain extent. It has always been argued that students do not learn by merely clicking on simulated glassware and instruments. In a typical organic chemistry laboratory, students prepare organic compounds, purify them, and determine various properties of the pure compounds. Students gain experience by trial-error while adding reagents in organic preparation, devising reaction mechanisms, observing the physical properties of purified compounds, and even separating complex mixtures. Virtual laboratories cannot replace all these with a mere simulator, but when one deals with corrosive chemicals and advanced instrumental methods, it seems a plausible solution to augment them with traditional laboratories. It was found that using advanced level of online screen experiments improved students understanding and also helped them score well in their laboratory assessments. Virtual simulations cannot replace traditional laboratories since many experiments require hands-on tool abilities, smelling, seeing colored complexes, and trial-error strategies. It was also observed that experiments that require costly instruments can be carried as a remote trigger, paving the way to augment virtual experiments in the future chemistry laboratory. The chapter discusses the pedagogical design for graduate students in a virtual chemistry laboratory and live demonstrations performed in the traditional laboratory. In this chapter chemistry experiments based on organic synthesis, stereochemistry and spectroscopy on a virtual screen have been studied. The different modalities of conducting virtual screen experiments, assessment strategies, and government initiatives are also highlighted. This chapter concludes with current and future trends of virtual chemistry laboratories with highlights on the barriers, opportunities, and key measures to resolve them. © 2022 selection and editorial matter, Muhammad Mujtaba Asad, Fahad Sherwani, Razali Bin Hassan, and Prathamesh Churi;individual chapters, the contributors.
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UMMASevere acute respiratory syndrome coronavirus2 (SARS-CoV-2) is highly communicable and pathogenic coronavirus that come out in December 2019 and has caused a pandemic of acute respiratory disease, named ‘coronavirus disease 2019’ (COVID 19), which intimidate public health and safety. According to World Health Organization (WHO), infection is known as COVID-19. With the start of the COVID-19 pandemic, 10 vaccines against SARS-CoV-2 have been approved for at least limited use, with over sixty others in clinical trials. This swift achievement has generated excitement and arrives at a time of great need, as the number of COVID-19 cases worldwide continues to rapidly increase. Two vac-cines are currently approved for full use, both built on mRNA and lipid nanotechnology platforms, a success story of mRNA technology 20 years for making. For cancer patients, questions put up for the safety and efficacy of these vaccines in the setting of immune alterations engendered by their therapies. We discuss in this article on leading COVID-19 vaccine candidates and vaccination of patients.
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Human's inhale oxygen which is then transported to the lungs, where it is then delivered into the bloodstream. As a result, breathing entails inhaling oxygen and exhaling carbon dioxide, which a healthy individual accomplishes roughly 25000 times every day. COVID-19, Pneumonia, and Lung Opacity all cause the lungs to stop working properly, which can lead to respiratory failure. Some diseases can be fatal;COVID-19 is one of the deadly diseases that the world is now dealing with. For the detection of lung disease, different prediction models are developed using deep learning algorithms, and their performances are computed and assessed using various performance metrics. The proposed methodology comprises of analyzing the performance of the CNN model after it has been trained on a dataset of 8,462 images. During the performance training, the proposed model obtained an accuracy rate of 90.83 percent. The study also discusses how the pre-trained models VGG-16 and ResNet-50 were implemented and evaluated for the dataset. The Flask app has also been used to create a user interface that accepts the user's X-ray images as input and forecasts lung illness as an output. © 2022 IEEE.
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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19) pandemic has become a global health issue. Recently, the SARS-CoV-2 strain (B.1.617 double mutant variant) has raised alarms in India and other nations. B.1.617 variant was found to contain two key mutations (L452R and E484Q) in the RBD region of the spike protein. In this work, we have focussed on the effect of the double mutations in spike protein on its binding to the host cell receptor protein, angiotensin-converting enzyme 2 (ACE2). From the molecular dynamics simulation, we observed that the L452R and E484Q double mutant (DM) in spike protein utilizes unique strategies to achieve stable binding to ACE2 compared to the spike protein's wild type (WT). Using MM-GBSA/MM-PBSA algorithms, we found that the binding affinity between spike protein-containing DM and ACE2 is high (GBTOT =-47.09 kcal mol-1, PBTOT=-19.93 kcal mol-1) in comparison with spike protein WT and ACE2 (GBTOT =-31.79 kcal mol-1, PBTOT=-6.33 kcal mol-1). Stable binding of spike protein to ACE2 is essential for virus entry. They should understand interactions between them while designing drugs and treatment modalities to target or disrupt this interface. © 2022 by the authors.
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One of the main challenges in controlling the spread of COVID19 pandemic is to diagnose infection early. The most reliable method RT - PCR takes several hours to give results. Although the Anti-Body (Serological) test gives the results in a few hours, it is not accurate, and hence it is not reliable. Moreover, they are invasive. Another issue with these methods is that the number of labs performing these tests are very limited. It will be beneficial if the already existing clinical infrastructure is used for diagnosing COVID19 accurately in real time. Recently chest CT images are used by researchers to diagnose the COVID19 with impressive accuracy. The state of the art method for detecting COVID19 using CT chest images involves Deep Learning. Deep Learning is expected to provide accurate and reliable results only when the model is trained on a large data set. Due to non-availability of a large data set the existing models have been trained on a smaller size data set. Therefore it would be better to design a model to give good accuracy with reliability. To achieve accuracy along with reliability we proposed a COVID19 detection model with the combination of deep learning model and the traditional machine learning model. The novelty of the proposed model is the fusion of image quality and deep learning. The proposed method outperformed the state of the art method in terms of accuracy, recall and F1 score (more than 99 % in almost all the metrics) on a benchmark data set. The efficacy of the selected features and also explainability of the method are demonstrated through various tests. © 2021 ACM.
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Background: Since 2019 the National Allergy Strategy (NAS) 250K youth project has run annual camps to support school-aged teens living with severe allergies. In 2021, the COVID-19 pandemic presented several challenges for conducting camps. To reduce the risk of potential COVID-19 exposure, the NAS conducted a 250K fun day for school-aged teens, supported by local peer mentors, staff and volunteers. This study compares confidence levels for a range of allergy based self-management indicators, between the fun day and camp offerings. Method: The 250K fun day was held in Perth, Western Australia, in February 2021. Perth-based NAS staff and volunteer health professionals attended. School-aged teens and peer mentors from Perth were invited to participate. Several meetings with volunteers and catering staff were held prior. Findings: Fourteen school-aged teens with severe allergies and 1 peer mentor participated in the fun day, and 14 school-aged teens and 8 peer mentors participated in the 2020 camp. Confidence levels were measured using a participant survey. Table 1 provides a comparison of the results of the 2021 fun day and the 2020 camp. Conclusion: The 250K fun day helped connect young people with food allergy. The fun day as a one-day event substantially improved confidence levels in allergy self-management, however, did not increase confidence to the same level as the 2020 camp. Should COVID-19 continue to restrict access to camps, the fun day model represents a good option to engage youth and still provide significant benefit to participants.
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Aim of Object: During the COVID-19 pandemic, the entire world is experiencing a mortality situation;most people are battling against the corona virus, but some individuals have already suffered from cardiovascular problems. For improved patient care, adequate information and comprehension of the relationship between cardiovascular disorders and COVID-19 is required. The dominant clinical manifestations of the corona virus infection are on the respiratory system. In this instance, the acute cardiac injury is the most often reported cardiac abnormality, in which the degree of cardiac output is increased, troponin levels rise, and mostly it is found in about 8% to 12% of patients. The involvement of viral cardiomyocytes and systemic inflammation is the most prevalent mechanism for cardiac damage. The corona virus attaches itself and enters through angiotensin converting enzyme-II. Discussion and Conclusion: Recent articles on COVID-19 have revealed nothing regarding these individuals' cardiac vascular manifestations. This is a critical component of all that has a big influence on COVID-19 patients' cardiovascular systems. To fully comprehend the method and effects, more study is required.
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In the realm of infectious diseases, a pandemic is the worst-case scenario. When an epidemic is spread beyond a country's borders, then it is officially called pandemic. Humankind has always seen communicable diseases, but shift to aggregarion life made epidemic and later pandemic more possible. Malaria, tuberculosis, leprosy, influenzae [1, 2], and smallpox were some of them. The more civilized humans became, the more likely the pandemics became - like the first cholera pandemic in 1817 originated in Russia. In recent history, the world's one of the deadliest pandemics in 1918 was Spanish flu which struck 50 million deaths in Europe, USA, and parts of Asia. In 1981 AIDS, and then the world witnessed SARS- CoV-1 in 2003 in China, a form of coronavirus, a name which helps us recognize this new one of the most contagious pandemics the world has ever witnessed, called SARS-CoV-2 or popularly called COVID-19 or, as some say, Wuhan virus. SARS-CoV-2 was reported by China in late December 2019 with pneumonia-like symptoms of unknown origin. Without a vaccine available, it spread beyond borders, to more than 163 countries. COVID-19 has revealed vulnerabilities in the global communities' response to outbreaks of viruses, which has damaged the world's economy to the worst recession since the Great Depression. Shift of power and bringing the world to a standstill is something which none has ever imagined. Deaths, broken families, helplessness, fear and anxiety, uncertainty, and many more emotions were heaped on mankind. Economies suffered but the planet breathed, humans stopped but wildlife played. Life under COVID-19 brought blue skies and clean air, and many suffered but then many held them. Humans sought to learn and strive, sufferings created fighters, roadblocks paved new paths, and this horrendous experience changed the outlook and paved the perspective for a new world after COVID-19. © 2021 River Publishers. All rights reserved.
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Objectives: In the wake of COVID-19 pandemic, strict lockdown measures posed many challenges in managing chronic diseases such as hypertension and diabetes. The impact of lockdown on physical and biochemical parameters along with contributing factors was assessed. Design: Cross-sectional analytical study. Materials and Methods: One hundred and fifty consecutive patients with chronic illnesses attending medicine outpatient department during unlock down phase I were enrolled. A 5 point Likert scale was used to determine the effect on diet, exercise, pain, physical and psychological symptoms, and a personal interview to assess the contributing factors. Clinical examination and laboratory investigations were done to compare between pre and post lockdown status and appropriate statistical tests were used. Results: The mean age of the patients was 48.53 +/- 6.4 years with a female preponderance. Mean duration of illness was 8.93 +/- 2.4 years and majority had hypertension (21%), diabetes (19%) or both (12%), hypothyroidism (18%), and gastroesophageal reflux disease (8%). While physical symptoms and pain did not show a significant change, 41.3% had worsening of psychological symptoms, 53.3% diet, and 70.6% exercise noncompliance. Weight, blood pressure, lipids, serum thyroid-stimulating hormone showed little change. Glycemic control was deranged in 72.5% with HbA1c increasing from 6.47 +/- 1.9 to 8.1 +/- 2.4 (P = 0.007). Contributing factors, 52.3% reported lack of exercise, 40% financial problems, 36% transport difficulties, and 30% unavailability of medicines. Conclusion: Lockdown negatively affected the management of chronic diseases with significant worsening of psychological symptoms, diet, and exercise adherence. Glycemic control worsened in diabetics. Lack of transport and unavailability of medicines were the significant contributing factors.