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Background: The COVID-19 outbreak in 2019 has presented in the form of pneumonia of unknown etiology in Wuhan. The complete clinical profile including the prevalence of different clinical symptoms of COVID-19 infection among Indian patients who develop a severe disease is largely unknown. This study is aimed to provide a detailed clinical characterization of the cohort of patients who visited our institute with signs and symptoms of COVID-19. Material(s) and Method(s): This was for inpatient hospital (inpatient) based prospective cohort study involving 520 COVID-19 patients admitted to the hospital. The adverse outcome included death and mechanical ventilation. Result(s): Total 520 participants enrolled in the study, (6.9%) participants died, (8.3%) participants required ICU and (5.5%) participants required mechanical ventilation. only signs and symptoms suggestive of severe respiratory system involvement or widespread infection were associated with adverse outcomes, T presence of dyspnoea, cyanosis and hypoxia. The most common chronic disease among patients with adverse outcomes were diabetes, hypertension and pre-existing respiratory disease, personal habit both smoking, and alcoholism was also associated with adverse clinical outcome. Conclusion(s): The adverse clinical outcome among COVID-19 patients is determined by several factors including advanced age, multi-morbidities, and the presence of severe respiratory symptoms.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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Background: Ever since the beginning of the COVID-19 pandemic, physicians started investigating the clinical features and lab markers that can assist in predicting the outcome among hospitalized COVID-19 patients. Aim(s): This study aimed to investigate the association between initial chest CT scan findings and adverse outcomes of COVID-19. Material(s) and Method(s): This was a single centre;hospital (inpatient) based prospective cohort study involving 497 COVID-19 patients admitted to the hospital. The adverse outcome included death and mechanical ventilation. We collected data about 14 identifiable parameters available for the HRCT scan. Result(s): Among 14 studied parameters, only 8 features differed significantly among the patients who had favourable and unfavourable outcomes. These features included number of lobes of lungs involved (3 versus 5, p = 0.008), CT Severity score (16 versus 20, p = 0.004), air bronchogram (p=0.003), crazy paving (p=0.029), consolidation (p=0.021), and pleural effusion (p=0.026). We observed that high CT scores coupled with the diffuse distribution of lung lesions were responsible for poor prognosis in most patients. Conclusion(s): Several features of HRCT when combined can accurately predict adverse outcomes among participants and help in triaging the patient for admission in ICU.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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During the COVID-19 pandemic, face masks, respirators, and personal protective equipment have become common preventive measures. However, the COVID-19 pandemic has highlighted the lack of efficient and reusable face masks worldwide. Immense efforts have been dedicated to designing antidust and antidroplet masks to ensure safe breathing. In this context, electrospun nanofibrous layers have attracted considerable attention for the fabrication of antidust and antidroplet masks. During long-term usage, water droplet layers can lead to pore blockages;this remains a major concern. In this study, a three-layered sandwich structure comprising a hydrophilic spongy layer, hydrophobic support layer, and antidroplet layer was developed to address this concern. Specifically, the structure comprised polyvinylidene fluoride-silica nanoparticles-perfluorooctyl trichlorosilane/polyethylene/polybenzimidazole (PVDF-Si-NPs-PFTOS/PET/PBI) electrospun nanofibrous layers. The PBI layer was utilized as soft, hydrophilic, skin-friendly layer, as supported by the PET layer for better mechanical stability. In addition, PVDF coated with micro-nano scale Si-NPs as modified with a PFTOS nonwoven electrospun layer was used for the antifouling, antidroplet, and splash resistance capabilities. This novel electrospun nanofibrous nonwoven three-layered sandwich structure (PVDF-Si-PFTOS/PET/PBI) exhibited high performance, with competitive antidroplet abilities. Accordingly, this research can be used to fabricate face masks with antidroplet and splash resistance for personal safety and protective equipment.
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Novel coronavirus (COVID-19) saw a daily major rise after August 2021. Health ministry of India shows more than 1000 deaths in 24 h. Reviewing this pandemic situation, there are again possibilities of lockdown in India. Daily updates of vaccinations, government permissions are changing day by day. Live updates and its insights should be reached to the common man. People are creating rumors about COVID-19. Social media like Twitter can ease the lifestyle in pandemic situations. The survey of COVID-19 sentiment analysis of Twitter data included in this paper. Novel techniques like BERT model, TextBlob, and VADER libraries are also discussed. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Introduction: While managing COVID-19 patients, the healthcare professionals are at higher risk for contracting the infection and also could be a potential source of transmitting the disease in the community unknowingly. Therefore awareness [knowledge, attitude, and practice (KAP)] among healthcare professionals becomes of utmost importance. Methods: We conducted this observational cross sectional study to evaluate the knowledge, attitude and perceived practices toward COVID-19 among HCWs using a self-administered questionnaire at tertiary level healthcare facility in western Rajasthan. The questionnaire was shared with all the healthcare professionals of the pre identified tertiary care facilities through electronic mail (e-mail) and the responses received were recorded and analyzed. Results: A total of 59 responses were recorded. Out of the total participants, 61% were aware of national COVID-19 helpline numbers, 54.2% answered correctly about Hydroxychloroquine prophylaxis, 13.6% answered appropriately on COVID-19 testing. Almost 96.6% acknowledged to wear a medical mask however only 55.9% participants answered correctly regarding using a face mask. 52.5% responded that ash collection as a ritual may be allowed after funeral (cremation) of the body of a COVID-19 patient. More than 90% of participants acknowledged to clean their hands > 6-10 times in a day. 72.9% of participants admitted to open the MoHFW website to keep themselves updated on COVID-19 in India and 66.1% have 'Aarogya Setu' application in their mobile phone. However only 23.7% have ever used central helpline number or email-ID to get information on COVID-19. Conlcusion: We concluded that healthcare professionals were aware of the management strategies and treatment protocol however there is significant differences in the KAP of HCW sub groups. It also becomes important to study the KAP in various other populations (general populations, close contacts of COVID-19 etc.) for planning effective intervention strategies for them.
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Introduction: COVID-19 spread was due to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Even today, COVID cases are being continually recorded. On this basis, it can be said that there is still the danger of COVID-19 cases getting increased at a rapid rate. There is no way of distinguishing the clinical findings and radiological findings of secondary fungal infection from that of COVID-19 pneumonitis and pneumonia. Aim: To Assess the MRI Evaluation of Cases of Mucormycosis after COVID-19”. Material and Methods: In the current study, the researcher conducted an observational study at Pacific Medical College, Udaipur, Rajasthan, India. Data for all the confirmed mucormycosis cases among patients with and without COVID-19 reported from September 2020 to December 2020, for the current study was collected. The researcher used SPSS Statistics 21.0 for performing an analysis of the data obtained from the health care centre. The descriptive statistics were measured and analysed using frequencies, mean, standard deviations, and median. Results: Out of the 286 cases, 65% (N = 185) had CAM (COVID-19 Associated Mucormycosis), with the mean age of 52 (SD = 16) years. Furthermore, 75% (N = 214) of the entire study population was male;and the remaining 25% (N = 72) were female. The prevalence of CAM was 0.28% and the range was 0.04% to 0.60%;on the other hand, CAM prevalence in ICU patients was determined to be 1.9% and the range was o.68% to 2%. Conclusion: From the current results, it can be concluded that Uncontrolled Diabetes Mellitus, found to be among 63% of the participants, was one of the common diseases in both CAM as well as non-CAM groups. In addition, the rhino-orbital area was among the most well-known sites of mucormycosis, with 58% participants, followed by rhino-orbital-cerebral, pneumonic, and other such areas.
ABSTRACT
In December 2019, a disease known as COVID-19 outbroke in some part of China which killed a bunch of people in that area. Till Mid-March, the disease spread all over the world killing more people. Due to this, World Health Organization (WHO) had to declare this decease as a pandemic. Therefore, scientists from all over the world were working very hard, giving their best everyday in order to make an anti-dote of this disease but it was expected to take alot of time and it even took. Now, government allowed the citizens to continue their normal way of living but still they made some protocols which was to be followed such as sanitization of hands on a regular interval, maintaining two-yard distance from each other, wearing masks, etc. Considering those protocols, we have evolved a Face-masks Detection System with a view to be useful in figuring out whether or not a person is wearing a mask or not inside the public locations which include Temples, Airports, and so on. The face masks detection database contains a mask and further to the facial snap shots, we've used OpenCV to carry out actual-time face detection from live streaming thru webcam. We have used the database to create a COVID-19 face mask detector from a computer view the use of Python, OpenCV, and Tensor Flow and Cameras. We present an in-intensity reading software that could come across conditions where a face mask isn't always used well. Our software incorporates a two-section configuration of the Convolutional Neural Network (CNN) that could hit upon hidden and unidentified faces and may point-out with pre-hooked up CCTV cameras. This allows in monitoring safety violations, promote using face mask, and ensures a safe running environment. © 2021 IEEE.
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Coronavirus disease-19 (COVID-19)-infected patients are at risk to develop severe opportunistic infections, especially fungal infections. The incidence of mucormycosis has increased in patients who are recovering from COVID-19 and now it has become an epidemic in India. In the background of the COVID-19 pandemic, we present a case series of seven patients with mucormycosis and their risk factor profile. Six of our patients had nonketotic poorly controlled glycemic status. All patients were mild or asymptomatic as far as COVID-19 clinical symptoms are concerned, but they had high inflammatory markers such as interleukin 6 (IL-6), ferritin, and D-dimer, which are commonly seen in a cytokine storm. Hyperglycemia and COVID-19 infection were consistent features in our patients. We found that COVID-19 patients with poor glycemic control and high inflammatory markers are at high risk for mucormycosis infection. However, the duration from the diagnosis of COVID-19 and the development of symptoms of mucormycosis was varied from 1 to 12 days (mean- 5.71). There was no correlation of the level of IL-6 or D-dimer with the early onset of mucormycosis. We also did not find any correlation of mucormycosis with other proposed risk factors such as oxygen therapy, steam inhalation, or prolonged steroid therapy, since four of our patients had never received steroids in any form and three had received only mild dosages of steroid. The sample size for statistical analysis was inadequate. However, a randomized clinical trial or larger observational study is needed to establish this observation.
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The COVID-19 pandemic continues to spread and impact the well-being of the global population. The front-line imaging modalities computed tomography (CT) and X-ray play an important role for triaging COVID-19 patients. Considering the limited access to resources (both hardware and trained personnel) and decontamination, CT may not be ideal for triaging suspected subjects. Artificial intelligence (AI) assisted X-ray based applications for triaging and monitoring COVID-19 patients in a timely manner with the additional ability to delineate the disease region boundary are seen as a promising solution. Our proposed solution differs from existing solutions by industry and academic communities. We demonstrates a functional AI model to triage by inferencing using a single x-ray image, while the AI model is trained using both X-ray and CT data. We report on how such a multi-modal training improves the solution compared to X-ray only training. The multi-modal solution increases the AUC (area under the receiver operating characteristic curve) from 0.89 to 0.93 for the classification between COVID-19 and non-COVID-19 cases. It also positively impacts the Dice coefficient (0.59 to 0.62) for segmenting the COVID-19 pathology. © 2021, Springer Nature Switzerland AG.
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Coronavirus has affected the entire global community owing to its transmission through respiratory droplets. This has led to the mandatory usage of surgical masks for protection against this lethal virus in many countries. However, the currently available disposable surgical masks have limitations in terms of their hydrophobicity and reusability. Here, we report a single-step spray-coating technique for the formation of a superhydrophobic layer of single-walled carbon nanotubes (SWCNTs) on a melt-blown polypropylene (PP) surgical mask. The sprayed SWCNTs form a nanospike-like architecture on the PP surface, increasing the static contact angle for water from 113.6° ± 3.0° to 156.2° ± 1.8° and showing superhydrophobicity for various body fluids such as urine, tears, blood, sweat, and saliva. The CNT-coated surgical masks also display an outstanding photothermal response with an increase in their surface temperature to more than 90 °C within 30 s of 1 sun solar illumination, confirming its self-sterilization ability. Owing to the cumulative effect of the superhydrophobicity and photothermal performance of the SWCNTs, the CNT-coated masks show 99.99% higher bactericidal performance toward Escherichia coli than pristine masks. Further, the virucidal ability of the SWCNT-coated mask, tested by using virus-like particles, was found to be almost 99% under solar illumination. As the spray-coating method is easily scalable, the nanotube-coated mask provides cost-effective personal protection against respiratory diseases. © 2021 American Chemical Society.
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We are living in the digital era, where most of the hospitals in the developed nations are keeping the medical records of the patients and as a result, most of the traits of the COVID-19 infected individuals are present in the digital form. Based upon the data thus generated, which is present on various platforms over the internet. In this chapter, an effort has been made to propose an artificial intelligence-based self-testing technique that can predict the patients who should go for COVID-19 testing. This chapter presents a belief rule-based expert system to predict the likelihood of the person to be tested for COVID-19. The system thus generated can easily pre-screen humans without the intervention of any second individual. Based upon the classification results the individual can be further tested to firm the presence of COVID-19 infection. This method will be cost-effective, plus it will also result in inefficient utilization of the scarce resource of medical testing kits. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Understanding the pathophysiology of the coronavirus disease 2019 (COVID-19) infection remains a significant challenge of our times. The gingival crevicular fluid being representative of systemic status and having a proven track record of detecting viruses and biomarkers forms a logical basis for evaluating the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The study aimed to assess gingival crevicular fluid (GCF) for evidence of SARS-CoV-2 in 33 patients who were deemed to be COVID-19 positive upon nasopharyngeal sampling. An attempt was also made to comparatively evaluate it with saliva in terms of its sensitivity, as a diagnostic fluid for SARS-CoV-2. GCF and saliva samples were collected from 33 COVID-19-confirmed patients. Total RNA was extracted using NucliSENS easyMAG (bioMérieux) and eluted in the elution buffer. Envelope gene (E gene) of SARS-CoV-2 and human RNase P gene as internal control were detected in GCF samples by using the TRUPCR SARS-CoV-2 RT qPCR kit V-2.0 (I) in an Applied Biosystems 7500 real-time machine. A significant majority of both asymptomatic and mildly symptomatic patients exhibited the presence of the novel coronavirus in their GCF samples. Considering the presence of SARS-CoV-2 RNA in the nasopharyngeal swab sampling as gold standard, the sensitivity of GCF and saliva, respectively, was 63.64% (confidence interval [CI], 45.1% to 79.60%) and 64.52% (CI, 45.37% to 80.77%). GCF was found to be comparable to saliva in terms of its sensitivity to detect SARS-CoV-2. Saliva samples tested positive in 3 of the 12 patients whose GCF tested negative, and likewise GCF tested positive for 2 of the 11 patients whose saliva tested negative on real-time reverse transcription polymerase chain reaction. The results establish GCF as a possible mode of transmission of SARS-CoV-2, which is the first such report in the literature, and also provide the first quantifiable evidence pointing toward a link between the COVID-19 infection and oral health.