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1.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925435

ABSTRACT

Objective: We characterized the effect of a 12-week community-based boxing exercise program on motor and non-motor symptoms in people with Parkinson's disease (PWP). Background: Non-motor symptoms, including depression and apathy, are common in Parkinson's disease (PD), with significant impact on quality of life and independence. Apathy, in particular, can be difficult to treat with pharmacotherapeutics. Design/Methods: This was a prospective observational study. PWP underwent a 12-week designed community-based boxing program. The following assessments were performed by a movement disorders neurologist at baseline and after completion of the program: MDS-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) modified version (since this was performed virtually due to COVID-19 pandemic), MDS Non-Motor Rating Scale (MDS-NMS), Hamilton Depression Rating Scale (HDRS), Lilli Apathy Rating Scale (LARS), Parkinson's Disease Questionaire-39 (PDQ-39), and Schwab and England Activities of Daily Living scale (SE-ADL). Pre- and post-assessments were compared using paired T-test;only participants who completed the program and both assessments were analyzed. Results: Twenty-four PWP enrolled in the boxing program, out of which 14 agreed to be a part of the study and completed assessments. All participants were ambulatory and functionally independent at baseline. MDS-NMS (p=0.003), HDRS (p=0.04), and MDS-UPDRS III modified (p=0.0003) improved significantly after the intervention. LARS (p=0.25), PDQ-39 (p=0.07), and SE-ADL (p= 0.16) did not change. Anecdotally, participants reported an improvement in motivation. Conclusions: PWP who participated in a community-based boxing program had improvements in motor exam, non-motor symptoms, and depression. Using a larger sample size, future studies should assess the impact of such an intervention on apathy.

2.
6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022 ; : 1625-1633, 2022.
Article in English | Scopus | ID: covidwho-1922681

ABSTRACT

The evolution of digitization and technology has increased the amount of data shared online, inevitably leading to the spread of false information. The issue has skyrocketed as COVID-19 spread across the globe and carried with it a sea-full of fake news. Recent technological advances, such as automatic text generators, have exacerbated the problem by interpolating synthetic text into the fake news. Current fake news detection approaches do not take into account the validity of synthetic news (machine-generated news), thus classifying all machine-generated material as fake. In this paper, the first-ever synthetic news classification model using CT-BERT is implemented, and a framework is proposed that not only distinguishes between human-authored and machine-generated text, but also considers the veracity of text to detect fake news. Moreover, a novel COVID-19 based synthetically generated dataset has been introduced by fusing synthetic text generated by GPT-2 and Grover model. Further, whether the GPT-2 and Grover models are vulnerable to adversarial attacks or not has been investigated. An accuracy of 98.2% and 92.4% respectively in the fake news classification of human-authored and machine-generated text have been achieved. © 2022 IEEE.

3.
Topics in Antiviral Medicine ; 30(1 SUPPL):350, 2022.
Article in English | EMBASE | ID: covidwho-1880027

ABSTRACT

Background: Sexually transmitted infection (STI) diagnosis serves as an important linkage to HIV testing and pre-exposure prophylaxis (PrEP) for adolescents. The COVID-19 pandemic disrupted sexual health services for young people, with a potential consequence of increasing undiagnosed STIs. This study aimed to describe STI testing changes and estimate undiagnosed STI cases during the pandemic. Methods: We analyzed electronic medical records for chlamydia, gonorrhea, and trichomonas testing encounters from six pediatric primary care clinics in Philadelphia, July 2014-November 2020. We assessed whether testing was asymptomatic screening, risk-based testing, or symptomatic testing, and whether any result was positive. We evaluated STI trends over time, comparing pre-pandemic (before March 1st, 2020) and pandemic periods (after March 1st, 2020). Missed STI cases during the pandemic were estimated using decreases in patient volume and asymptomatic screening as compared to the previous year. Generalized linear mixed-effects models estimated the effects of patient-level and neighborhood-level characteristics on STI outcomes. Results: 35,548 STI testing encounters were analyzed, including 2,958 during the pandemic period. The median patient age was 17.5 years, 57% of patients were female, and 84% were Black/African American. Mean monthly STI testing encounters decreased from 479/month pre-pandemic to 329/month during the pandemic. Test positivity increased from 12.5% pre-pandemic to a peak of 27.5% in April 2020. The percent of STI tests performed as asymptomatic screening dropped from 72.5% pre-pandemic to a nadir of 54.5% in April 2020 (Figure). We estimate that the decrease in asymptomatic screening in the pandemic period would be associated with 159 missed cases (23.8% of expected cases) based on patient volume from the previous year. In multivariate models controlling for testing type (asymptomatic screening, risk-based testing, or symptomatic testing), the odds of test positivity were 50% higher during the pandemic (OR: 1.50, p<0.001). Conclusion: STI test positivity increased during the pandemic while asymptomatic screening decreased. Test positivity was higher for asymptomatic patients, suggesting increased STI prevalence. These changes likely resulted in a substantial number of undiagnosed STIs, representing missed opportunities for PrEP linkage. Efforts are needed to re-establish and sustain access to STI services for adolescents in response to disruptions caused by the pandemic.

4.
JK Science ; 23(4):170-174, 2021.
Article in English | EMBASE | ID: covidwho-1866137

ABSTRACT

Mucormycosis is a serious, but rare opportunistic, invasive and life-threatening fungal infection primarily caused by Rhizopus arrhizus with very high case fatality. Recently, its alarming rise in the number among COVID-19 patients mostly with uncontrolled diabetes and those who received excessive administration of steroids for the treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection has raised interest among the scientific community to learn more about the said disease. The current review describes, its epidemiology, clinical presentation, risk factors, warning signs, diagnostic test and available preventive and treatment modalities for its effective management.

5.
European Journal of Molecular and Clinical Medicine ; 9(3):2809-2818, 2022.
Article in English | EMBASE | ID: covidwho-1820648

ABSTRACT

Aim: To evaluate neutrophilic lymphocyte ratio and lymphocyte monocyte ratio as prognostic markers in COVID 19. Material and method: The present retrospective observational studyconducted in the department of Medicine, Government Medical College, Jammu for a period of one year. The study comprised of 100 Covid 19 RT PCR positive cases admitted patient in ICU as well as Ward, in covid care centre of Government Medical College, Jammu. Patients characteristics were obtained from the hospital covid care centre satisfying inclusion criteria from electronic medical records and demographic, clinical, laboratory data were extracted included age, sex clinical features, signs and symptoms, comorbidities, exposure history, oxygen support during hospitalization, duration of oxygen support during hospitalization,imaging features of the chest (CT scoring), laboratory findings (Hemogram, Total leucocyte count, differential counts, NLR and LMR. Complete blood count including NLR and LMR collected at day of admission and day 3 of admission and documented on a standardized proforma. Two outcomes were evaluated: “discharge” or “died.” Results:In majority (53%) of patients, ventilation given was high flow followed by bipap (21%), ventimask (19%) and ventilator (5%). Ventilation given was room air in only 2 out of 100 patients (2%). In present study, only 10 out of 100 patients (10.00%) died.Discriminatory power of neutrophil lymphocyte ratio (AUC 0.865;95% CI: 0.781 to 0.925) was excellent and discriminatory power of lymphocyte monocyte ratio (AUC 0.791;95% CI: 0.698 to 0.867) was acceptable. Among both the parameters, neutrophil lymphocyte ratio was the best predictor of CTSI severity at cut off point of >3.57 with 86.50% chances of correctly predicting CTSI severity. Conclusion: It can be concluded from the results that NLR may be a rapid, widely available, useful prognostic factor in the early screening of critical illness in patients with confirmed COVID-19.

6.
JK Science ; 23(4):168-169, 2021.
Article in English | EMBASE | ID: covidwho-1813066
7.
European Journal of Molecular and Clinical Medicine ; 9(1):1051-1058, 2022.
Article in English | EMBASE | ID: covidwho-1695168

ABSTRACT

Background: Mucormycosis is a rare disease of immunocompromised adults largely restricted to the diabetic community with uncontrolled hyperglycaemia. In the second wave of Covid, in multiple cities over the Indian Peninsula, this much dreaded “black fungus” has afflicted many individuals who suffered from covid or were recovering from it. Aim: To establish the risk factors, clinical presentation, diagnostic sensitivities, radiological survey of different types of mucormycosis in SARS Cov 2 patients. Methods: Seventeen patients with covid infection admitted in tertiary care hospital with diagnosed mucormycosis between Nov 2020 to June 2021 via histopathological or culture confirmation. This is a cross-sectional observational study where detailed assessment of clinical profile, biochemical markers and sensitivities of diagnostic procedures was done. The data then collected and was made into a master chart and subjected to statistical analysis. Fischer exact test was used for statistical anaylsis. Result:In total of 17 patients,mean blood glucose levels were compared at the onset of symptoms of covid and mucormycosis werestatistically significant with (P=0.001). Out of 17 patients, 11 were rhino-orbital mucormycosis, four had rhino-orbito-cerebral mucormycosis and 2 had pulmonary mucormycosis.HbA1c >8 had significant correlation(P=0.009) with rhino-orbital and rhino-orbito-cerebral mucormycosis whilehigher total dosage of steroids was associated with pulmonary mucormycosis (P= 0.015. Sensitivity of culture was 64.7% in our study while histopathology was considered gold standard. Conclusion: Our study shows strong correlation between the long term as well as short term glycaemic control with the onset of rhino-orbital mucormycosis while dosage and duration of steroids with pulmonary mucormycosis.

8.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-327024

ABSTRACT

The waning effectiveness of the COVID-19 vaccines and the emergence of a new variant Omicron has given rise to the possibility of another outbreak of the infection in India. COVID-19 has caused more than 34 million reported cases and 475 thousand deaths in India so far, and it has affected the country at the root level, socially as well as economically. After going through different control measures, mass vaccination has been achieved to a large extent for the highly populous country, and currently under progress. India has already been hit by a massive second wave of infection in April-June, 2021 mainly due to the delta variant, and might see a third wave in the near future that needs to be controlled with effective control strategies. In this paper, we present a compartmental epidemiological model with vaccinations incorporating the dose-dependent effectiveness. We study a possible sudden outbreak of SARS-CoV2 variants in the future, and bring out the associated predictions for various vaccination rates and point out optimum control measures. Our results show that for transmission rate 30% higher than the current rate due to emergence of new variant or relaxation of social distancing conditions, daily new cases can peak to 250k in March 2022, taking the second dose effectiveness dropping to 50% in the future. Combination of vaccination and controlled lockdown or social distancing is the key to tackling the current situation and for the coming few months. Our simulation results show that social distancing measures show better control over the disease spread than the higher vaccination rates.

9.
4th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1662198

ABSTRACT

An electrocardiogram (ECG) is used to monitor electrical activity of the heart. ECG data with 12 leads can help in detecting various cardiac (heart) problems. One of the significant factors that contribute to various cardiac diseases is work/personal stress. Use of various machine and deep learning approaches to analyse ECG data has yielded promising results in the field of predictive and diagnostic healthcare with less human error or bias. In our study, 10sec of 500Hz, 12-lead ECG samples were collected from the healthcare workers, who were involved directly or indirectly in taking care of COVID-19 patients. The present study was designed to determine whether Healthcare workers were stressed by using only ECG as input to a deep learning model. To the best of our knowledge, no earlier ECG based study has been carried out to identify stressed persons among the healthcare workers who are giving support to COVID-19 patients. In this study, ECG data of healthcare workers giving services to COVID-19 patients is utilized. This data was collected from four tertiary academic care centres of India. A modified version of AlexNet is utilized on this data that is able to identify a stressed healthcare worker with 99.397% accuracy and 99.411% AUC score. Successful deployment of such systems can help governments and hospital administrations make appropriate policy decisions during pandemics. © 2021 IEEE.

10.
Fabad Journal of Pharmaceutical Sciences ; 46(3):311-324, 2021.
Article in English | Scopus | ID: covidwho-1628181

ABSTRACT

The ongoing outbreak of the cOviD-19 is a significant threat to global health and the economy. This disease is a highly contagious pathogenic disease caused by severe acute respiratory syndrome coronavirus 2 (sARs-cov-2). The virus has a high reproduction rate, due to that it is highly transmittable and has turned into a catastrophe. scientists and researchers worldwide are exaggerating every possible approach to limit the spread of this malicious disease. An abrupt rise has been reported in the number of cases due to newly mutated strains like sARs-cov-2 vUi 2020/12/01. to date, no specific drug is effective in the complete eradication of this dangerous disease but, some broad-spectrum antivirals such as Remdesivir and lopinavir are being used in the management of this ailment. Also, every possible effort has been made in the development of vaccines for preventing the outbreak of this deadly virus. The BNt162b2 by Pfizer and m-RNA-1273 by Moderna have been recently launched into the market, which have shown undesirable effects in geriatrics leading to mortality. in this review, we have tried to highlight important aspects of the cOviD-19 that will aid in global awareness and will help the researchers to investigate possible ways to eradicate this menace and design new moieties for its effectual management. © 2021 Society of Pharmaceutical Sciences of Ankara (FABAD). All rights reserved.

11.
European Journal of Public Health ; 31:1, 2021.
Article in English | Web of Science | ID: covidwho-1610192
12.
European Journal of Public Health ; 31:15-15, 2021.
Article in English | Web of Science | ID: covidwho-1610191
13.
Cancer Research, Statistics, and Treatment ; 4(1):78-87, 2021.
Article in English | Scopus | ID: covidwho-1598006

ABSTRACT

Computed tomography (CT) imaging has been reported to be a reliable tool for the evaluation of suspected cases and follow-up of confirmed cases of coronavirus disease 2019 (COVID-19). Despite the generation of a considerable amount of imaging data related to COVID-19, there is a need for an updated systematic review and meta-analysis pertaining to the questions of clinical significance. We aimed to analyze the correlation between abnormal chest CT findings and disease severity in patients with COVID-19. We searched for case series/studies published in the English language until March 24, 2020 that reported the clinical and chest CT imaging features of confirmed cases of COVID-19 in the PubMed database. A total of 208 studies were screened, and 71 were finally included in the meta-analysis. Study characteristics and relative risk (RR) estimates were extracted from each article and pooled using the random-effects meta-analysis model. There were a total of 6406 patients studied in a total of 71 studies;the male to female ratio was 1.08:1, and the mean age was 45.76 years;of these, 2057 patients from 14 studies were categorized into severe (24.3%) and mild (75.7%) disease groups. Imaging features that were more frequently noted in patients with severe disease than in those with mild disease included bilateral lung involvement (88.7% vs. 49.8%), scattered distribution (80.4% vs. 46.5%), multiple lobe involvement (95.7% vs. 59.6%), consolidation (88.3% vs. 60.3%), crazy-paving pattern (45.4% vs. 27.6%), air-bronchogram sign (29.7% vs. 15.1%), interlobular septal thickening (84.2% vs. 55.8%), and subpleural line (36.8% vs. 26.4%) differences between the two disease groups were statistically significant (P < 0.001). For 3778 patients in 29 studies, a significant pooled RR estimate was associated with abnormal chest CT findings in patients with COVID-19 (RR, 5.46%;95% confidence interval [CI], 3.72%-8.04%;I 2 = 86%). Individual assessment of the CT features revealed that a significant pooled RR estimate was associated with pure ground-glass opacity (GGO) (RR, 1.63%;95% CI, 1.12%-2.38%;I 2 = 79%), while lower pooled RR estimates were associated with CT features like crazy-paving pattern (RR, 1.37%;95% CI, 1.10%-1.71%;I 2 = 60%), consolidation (RR, 0.47%;95% CI, 0.32%-0.7%;I 2 = 83.5%), GGO with consolidation (RR, 0.73%;95% CI, 0.52%-1.02%;I 2 = 75%), and air-bronchogram sign (RR, 0.58%;95% CI, 0.36%-0.96%;I 2 = 94%). In conclusion, the number, location, extent, and type of radiological lesions are associated with COVID-19 progression and severity, suggesting the feasibility of using CT imaging in the assessment of disease severity in all age groups and efficient allocation of resources for patient management at the institutional level. © 2021 Cancer Research, Statistics, and Treatment ;Published by Wolters Kluwer - Medknow.

14.
Cancer Research, Statistics, and Treatment ; 4(1):12-18, 2021.
Article in English | Scopus | ID: covidwho-1595631
15.
Cancer Research, Statistics, and Treatment ; 4(2):256-261, 2021.
Article in English | Scopus | ID: covidwho-1591745

ABSTRACT

Background: Chest computed tomography (CT) is a readily available diagnostic test that can aid in the detection and assessment of the severity of the coronavirus disease 2019 (COVID-19). Given the wide community spread of the disease, it can be difficult for radiologists to differentiate between COVID-19 and non-COVID-19 pneumonia, especially in the oncological setting. Objective: This study was aimed at developing an artificial intelligence (AI) algorithm that could automatically detect COVID-19-related abnormalities from chest CT images and could serve as a diagnostic tool for COVID-19. In addition, we assessed the performance and accuracy of the algorithm in differentiating COVID-19 from non-COVID-19 lung parenchyma pathologies. Materials and Methods: A total of 1581 chest CT images of individuals affected with COVID-19, individuals affected with non-COVID-19 pathologies, and healthy individuals were included in this study. All the digital images of COVID-19-positive cases were obtained from web databases available in the public domain. About 60% of the data were used for training and validation of the algorithm, and the remaining 40% were used as a test set. A single-stage deep learning architecture based on the RetinaNet framework was used as the AI model for image classification. The performance of the algorithm was evaluated using various publicly available datasets comprising patients with COVID-19, patients with pneumonia, other lung diseases (underlying malignancies), and healthy individuals without any abnormalities. The specificity, sensitivity, and area under the receiver operating characteristic curve (AUC) were measured to estimate the effectiveness of our method. Results: The semantic and non-semantic features of the algorithm were analyzed. For the COVID-19 classification network, the sensitivity, specificity, accuracy, and AUC were 0.92 (95% confidence interval [CI]: 0.85-0.97), 0.995 (95% CI: 0.984-1.0), 0.972 (95% CI: 0.952-0.988), and 0.97 (95% CI: 0.945-0.986), respectively. For the non-COVID classification network, the sensitivity, specificity, and accuracy were 0.931 (95% CI: 0.88-0.975), 0.94 (95% CI: 0.90-0.974), and 0.935 (95% CI: 0.90, 0.965), respectively. Conclusion: The AI algorithm developed in our study can detect COVID-19 abnormalities from CT images with high sensitivity and specificity. Our AI algorithm can be used for the early detection and timely management of patients with COVID-19. © 2021 Cancer Research, Statistics, and Treatment ;Published by Wolters Kluwer - Medknow.

16.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1514722

ABSTRACT

Background COVID-19 pandemic was accompanied by an Infodemic (overabundance of information, including misinformation and disinformation, both online and offline);in response to this Infodemic, WHO launched the EARS platform (Early AI-assisted Response with Social Listening), showing real-time information about how people are talking about COVID-19 online. This information is intended to serve health information professionals to understand narratives and needs of the general public, in order to inform policy or communications decisions. Methods Data is collected daily from online conversations in publicly available sources, including Twitter, online forums, and blogs in English, French, Spanish and Portuguese, for 20 pilot countries. Once the data is collected, it is processed and classified into 39 categories, according to a set of pandemic public health taxonomy. The classification is made based on semi-supervised machine learning. Results Top 5 categories across regions are Covid-19 vaccine, Transmission settings, Personal measures, Testing and Industry (industry refers to the impact of the pandemic on the economy). We find that conversations around Covid-19 vaccines usually rank in the second or third position in all regions and represent 9%-12% of the conversation. Conclusions The configuration and application of the EARS platform has enabled progress towards more scalable and sustainable social listening to inform Infodemic management and response, compared to previous methods which were more manual, required data scientists in the team, or had fewer analytics capabilities. Future work will focus on gradually adding more data sources which can expand coverage and representativity. Key messages Discuss social listening methods for greater accountability to affected populations. Formulate insights into how digital media and information technology can be better utilized for more rapidly responding to the evolving needs of communities.

17.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1514635

ABSTRACT

Issue The World Health Organization describes an infodemic as an “overabundance of information - good or bad - that makes it difficult for people to make decisions for their health.” Description of the problem On April 7-8, 2020, the WHO Information Network for Epidemics (EPI-WIN) held a global online to crowdsource ideas from an interdisciplinary group of experts to form a novel COVID-19 infodemic response framework. The online consultation comprised of four plenary sessions and a brainstorming session conducted entirely online. Nearly 1500 individuals from over 100 countries and territories spanning social scientists, epidemiologists, staff from ministries of health and institutes of public health, registered for the consultation. Results A set of 50 proposed actions for a framework for managing infodemics in health emergencies was developed that will provide guidance for governments and public health institutions to take in five key areas of action that emerged from the consultation: strengthening evidence and information simplifying and explaining what is known fact-checking and addressing misinformation amplifying messages and reaching the communities and individuals who need the information quantifying and analysing the infodemic, including information flows, monitoring the acceptance of public health interventions, and assessing factors affecting behaviour at individual and population levels strengthening systems for infodemic management in health emergencies Lessons Everyone has a role to play Read the Call for Action Sign the Call for Action https://www.who.int/news/item/11-12-2020-call-for-action-managing-the-infode Key messages The confusion due to Infodemic can lead people to ignore public health measures and take risks that can cause serious harm. Recognizing this WHO convened an interdisciplinary group of experts 7-8 April 2020 virtually to form a novel COVID-19 infodemic response framework.

18.
European Journal of Public Health ; 31, 2021.
Article in English | ProQuest Central | ID: covidwho-1514513

ABSTRACT

Background The Infodemic (too much information including false or misleading information in digital and physical environments) during the COVID-19 pandemic has led to confusion, risk-taking and behaviors that can amplify outbreaks, and reduce effectiveness of pandemic response efforts. To address this challenge, the WHO Information Network for Epidemics (EPI-WIN), in collaboration with research partners, developed a public health Infodemic intelligence analysis methodology for weekly analysis of digital media data to identify, categorize, and understand key concerns expressed in online conversations. Methods Thirty-five keyword-based searches (per language) using Meltwater Explore and Google Trends were created and grouped according to a set of pandemic public health taxonomy categories developed specifically for this analysis. The taxonomy has five thematic categories of conversation about COVID-19 and public health response: (1) the cause of the illness, (2) the illness, (3) the treatment, (4) the interventions and (5) Information. Results The two most recurring topics to attract increasing interest were Vaccines and Asymptomatic transmission followed by Immunity, Cause of the virus, Vulnerable communities and Reduction of movement, and Risk factors based on demographics and risk of misinformation. Conclusions The application of this taxonomy to online social listening week-on-week resulted in a better in-time understanding of the evolution and dynamics of high velocity conversations about COVID-19 globally during the pandemic and proposes a quantifiable approach to support planning of risk communication response. Key messages Describe widespread innovation in social listening methods for greater accountability to affected populations. Formulate insights into how digital media can be better utilized for more rapidly responding to the evolving needs of communities.

19.
Journal of the American College of Surgeons ; 233(5):S116, 2021.
Article in English | EMBASE | ID: covidwho-1466550

ABSTRACT

Introduction: COVID-19 has created experiential barriers for surgical learners to interact at the bedside for teaching/case presentations. We hypothesized that an international Grand Rounds using the Microsoft HoloLens2 extended reality (XR) headset creates an improved bedside-learning experience compared with traditional Grand Rounds formats. Methods: In December 2020, we hosted (through partnership with the University of Michigan and Imperial College of London) the world’s first International Grand Rounds experience using the HoloLens2 XR headset broadcasting transatlantic bedside rounding on 3 complex surgical patients to an international audience of 154 faculty, residents, and medical trainees. Participants completed qualitative pre- and post-event surveys. Results: Of the 154 participants, 96 (62%) completed pre-surveys and 70 (45%) completed both the pre-and post-surveys. Respondents (average age 39.3 years [43% women;57% men;80 US;16 UK]) included 30 medical students, 30 faculty, 7 residents, and 29 hospital administrators. Pre-event survey: 76% had little or no experience before with XR devices;92% thought development/implementation of XR medical curricula was valuable;and 96% felt tele-rounding using XR technology was important for the current era. Post survey: 98% respondents thought the ability to visualize bedside clinical findings, imaging, and lab-tests via XR rounding was highly valuable and this novel XR international Grand Rounds format was superior to traditional Grand Rounds. Conclusion: Almost all (98%) participants in the world’s first International Grand Rounds on a Mixed Reality Headset felt this immersive extended reality virtual experience allowed visualization of clinical findings, imaging, and labs at the patient’s bedside and was superior to a traditional Grand Rounds format.

20.
Chest ; 160(4):A176, 2021.
Article in English | EMBASE | ID: covidwho-1457781

ABSTRACT

TOPIC: Cardiovascular Disease TYPE: Medical Student/Resident Case Reports INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) myocarditis has recently been described in case reports. A systematic review in early 2021 found fourteen case reports of myocarditis or myopericarditis secondary to this viral infection. We describe an interesting case of proven non-ischemic cardiac dysfunction in the setting of acute infection. Despite steroid treatment, which has been suggested to have favorable outcomes, our patient did not survive. CASE PRESENTATION: We present a case of a 77-year-old man with extensive electrophysiologic and ischemic cardiac disease who presented to the hospital for generalized weakness, malaise, and shortness of breath. The patient's cardiac history was significant for atrial flutter s/p ablation, coronary artery disease s/p coronary artery bypass graft in the distant past, peripheral artery disease s/p right lower extremity revascularization, and carotid stenosis s/p carotid endarterectomy. SARS-CoV-2 PCR test was positive. The patient had increasing hypoxia which required non-invasive ventilation and eventually, tracheal intubation and mechanical ventilation. The hospital course was complicated by the development of persistent chest pain associated with elevated cardiac enzymes. EKG showed diffuse ST-segment depressions. An echocardiogram revealed diffuse left ventricular hypokinesis and a reduced ejection fraction of 20% which was not present previously. In this setting, the patient was ruled in for acute coronary syndrome and underwent cardiac catheterization. Cardiac catheterization demonstrated patent grafts and no significant obstructive disease. A presumptive diagnosis of myocarditis was made. The patient's clinical status deteriorated despite optimal medical treatment, and he developed hemodynamically unstable atrial fibrillation that did not respond to pharmacologic treatment or cardioversion and resulted in cardiogenic shock and, ultimately, his death. DISCUSSION: SARS-CoV-2 myocarditis has been described in select case reports internationally. Many of these cases are described in patients with no previously identified comorbid conditions. This case suggests that in patients with underlying electrophysiologic dysfunction, SARS-CoV-2 myocarditis is associated with poor outcomes. CONCLUSIONS: The mechanism of the effect of SARS-CoV-2 on the heart is unclear and includes myocarditis or myopericarditis. In our patient, cardiac catheterization which was performed during his hospitalization confirmed no ischemic disease and suggested the presence of myocarditis which was ultimately fatal in the setting of refractory cardiogenic shock. Further research is needed into the optimal management of myocarditis associated with SARS-CoV-2. REFERENCE #1: Sawalha K, Abozenah M, Kadado AJ, et al. Systematic Review of COVID-19 Related Myocarditis- Insights on Management and Outcome. Cardiovasc Revasc Med. Feb 2021;23:107-113. REFERENCE #2: Purdy A, Ido F, Sterner S, et al. Myocarditis in COVID-19 presenting with cardiogenic shock: a case series. Eur Heart J Case Rep. Feb 2021;5(2):ytab028. REFERENCE #3: Fried JA, Ramasubbu K, Bhatt R, et al. The Variety of Cardiovascular Presentations of COVID-19. Circulation. 2020;141(23):1930-1936. DISCLOSURES: No relevant relationships by Sravani Gajjala, source=Web Response No relevant relationships by Stacey Jou, source=Web Response No relevant relationships by Zein Kattih, source=Web Response No relevant relationships by Rosaline Ma, source=Web Response No relevant relationships by Akhilesh Mahajan, source=Web Response No relevant relationships by Vinayak Shenoy, source=Web Response

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