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Problem: Several large studies have demonstrated that COVID-19 pregnant individuals are at a significant risk for severe disease and adverse pregnancy outcomes. The mechanisms underlying these phenomena remain to be elucidated and are the focus of our project. Although fetal and placental infection is rare, placental abnormalities and adverse pregnancy outcomes associated with placental dysfunction in COVID-19 cases have been widely reported. In particular, placental thrombosis and lesions consistent with maternal vascular malperfusion (MVM) of the placenta are common in individuals with COVID-19. Since thrombotic complications have been associated with COVID-19, it is not surprising that pregnant individuals with COVID- 19 are at risk for placental thrombosis. Method of Study: Placentas were evaluated histologically. Extracellular vesicles were isolated by serial centrifugation. Result(s): Adverse pregnancy outcomes associated with these placental lesions, including hypertensive disorders of pregnancy (gestational hypertension and preeclampsia), small for gestational age (SGA, birthweight < 10th percentile for gestational age), and preterm birth (PTB, < 37 weeks) are significantly increased among pregnant individuals with COVID-19. Placental infection with SARSCoV- 2 is uncommon, but multiple inflammatory and metabolic factors are likely to affect the placenta, including circulating extracellular vesicles (EVs) derived from various organs that have been associated with COVID-19 pathology and disease severity.We have analyzed over 500 placentas from COVID-19 pregnancies and found marked changes in placental morphology, characterized by abnormal maternal and fetal vessels, intervillous thrombi, and fibrin deposition, even in the face of mild or asymptomatic disease. We detected increased levels of small EVs in maternal serum from COVID-19 cases compared to controls and increased levels of mitochondrial DNA in EVs from COVID-19 cases. In in vitro experiments, we found increased oxidative stress in uterine endothelial cells and primary trophoblasts. Syncytialization of trophoblast cells following exposure to EVs from pregnant COVID-19 patients was markedly reduced. RNAseq of trophoblast cells exposed to EVs from pregnant COVID-19 patients revealed disruption of multiple pathways related to mitochondria function, oxidative stress, coagulation defects, and inflammation. Timing of infection during pregnancy (first, second, and third trimester) altered EV size distribution, cargo content, and functional consequences of trophoblast EV exposure. Conclusion(s): Our studies show that COVID-19 infection during pregnancy has profound effects on placenta morphology and function. It remains to be determined what the long-term consequences are on the offspring.
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BACKGROUND: Patients with Multisystem Inflammatory Syndrome in Children (MIS-C) and Kawasaki disease (KD) have overlapping clinical features. We compared demographics/clinical presentation, management, and outcomes of patients by evidence of prior SARS-CoV-2 infection. METHODS: The International KD Registry (IKDR) enrolled KD and MIS-C patients from sites from North, Central and South America, Europe, Asia and Middle East. Evidence of prior infection was defined as: Positive (+ve household contact or positive PCR/serology), Possible (suggestive clinical features of MIS-C and/or KD with negative PCR or serology but not both), Negative (negative PCR and serology and no known exposure), and Unknown (incomplete testing and no known exposure). RESULTS: Of 2345 enrolled patients SARS-CoV-2 status was Positive for 1541 (66%) patients, Possible 89 (4%), Negative 404 (17%) and Unknown for 311 (13%) patients. Clinical outcomes varied significantly between the groups, with more patients in the Positive/Possible groups presenting with shock, having admission to Intensive Care, receiving inotropic support, and having longer hospital stays. Regarding cardiac abnormalities, patients in the Positive/Possible groups had a higher prevalence of left ventricular dysfunction, while patients in the Negative and Unknown groups had more severe coronary artery abnormalities. results CONCLUSION: : There appears to be a spectrum of clinical features from MIS-C to KD with a great deal of heterogeneity, and one primary differentiating factor is evidence for prior acute SARS CoV2 infection/exposure. SARS-CoV-2 Positive/Possible patients had more severe presentations and required more intensive management, with a greater likelihood of ventricular dysfunction but less severe coronary artery adverse outcomes, in keeping with MIS-C.
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Background: One of the most dreaded complications of COVID pneumonia is post-COVID residual lung fibrosis and lung function impairment. Objectives: To find out the extent and type of pulmonary function abnormality using spirometry, diffusion capacity, and 6-minute walk test and to co-relate with the clinical severity at the time of infection, in patients who have recovered from COVID19 pneumonia, in a tertiary care hospital in India. Materials and Methods: This is a prospective, cross-sectional study with a total 100 patients. Patients who have recovered from COVID pneumonia after one month of onset of symptoms and before 3 months who come for follow-up and have respiratory complaints undergo pulmonary function test will be recruited in the study. Results: In our study, the most common lung function abnormality detected was restrictive pattern in 55% of the patients (N = 55) followed by mixed pattern in 9% of patients (N = 9), obstructive in 5% of patients (N = 5), and normal in 31% of patients (N = 31). In our study, total lung capacity was reduced in 62% of the patients and normal in 38% of the patients and diffusion capacity of lung was reduced in 52% of the patients recovered from 52% of the individuals. Also, a 6-minute walk test was reduced in 15% of the patients and normal in 85% of the patients. Conclusion: Pulmonary function test can serve as an important tool in both diagnosis and follow-up of post-COVID lung fibrosis and pulmonary sequalae.
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Much of today's data are represented as graphs, ranging from social networks to bibliographic citations. Nodes in such graphs correspond to records that generally represent entities, while edges represent relationships between these entities. Both nodes and edges in a graph can have attributes that characterize the entities and their relationships. Relationships are either explicitly known ( like friends in a social network), or they are inferred using link prediction (such as two babies are siblings because they have the same mother). Any graph representing real-world data likely contains nodes and edges that are abnormal, and identifying these can be important for outlier detection in applications ranging from crime and fraud detection to viral marketing. We propose a novel approach to the unsupervised detection of abnormal nodes and edges in graphs. We first characterize nodes and edges using a set of features, and then employ a one-class classifier to identify abnormal nodes and edges. We extract patterns of features from these abnormal nodes and edges, and apply clustering to identify groups of patterns with similar characteristics. We finally visualize these abnormal patterns to show co-occurrences of features and relationships between those features that mostly influence the abnormality of nodes and edges. We evaluate our approach on datasets from diverse domains, including historical birth certificates, COVID patient records, e-mails, books, and movies. This evaluation demonstrates that our approach is well suited to identify both abnormal nodes and edges in graphs in an unsupervised way, and it can outperform several baseline anomaly detection techniques.
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Background: Fever is a common clinical manifestation of COVID-19 infection. Fever has also been associated with unmasking Brugada pattern ECG in patients and may result in life-threatening arrhythmia. Little is known regarding COVID-19 associated Brugada pattern ECG. There is paucity of data and guidance in how to manage these patients. Method(s): To identify all published case reports, the latest Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed. A literature search was conducted using PubMed, EMBASE, and Scopus through September 2021. A systematic review was performed to identify the incidence, clinical characteristics, and management outcomes of COVID-19 patients with a Brugada pattern ECG. Result(s): A total of 18 cases were collected. The mean age was 47.1 years and 11.1% were women. No patient had prior confirmed diagnosis of Brugada syndrome. The most common presenting clinical symptoms were fever (83.3%), chest pain (38.8%), shortness of breath (38.8%), and syncope (16.6%). All 18 patients presented with type 1 Brugada pattern ECG. Four patients (22.2%) underwent left heart catheterization, and none demonstrated the presence of obstructive coronary disease. The most common reported therapies included antipyretics (55.5%), hydroxychloroquine (27.7%), and antibiotics (16.6%). One patient (5.5%) died during hospitalization. Three patients (16.6%) who presented with syncope received either an implantable cardioverter defibrillator or wearable cardioverter defibrillator at discharge. At follow up, thirteen patients (72.2%) had resolution of type 1 Brugada pattern ECG. Conclusion(s): COVID-19 associated Brugada pattern ECG is rare. Most patients may see resolution of the ECG pattern once their symptoms have improved. Increased awareness and timely use of antipyretics is warranted in this population.
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Background: Identification of athletes with cardiac inflammation following COVID-19 can prevent exercise fatalities. The efficacy of pre and post COVID-19 infection electrocardiograms (ECGs) for detecting athletes with myopericarditis has never been reported. We aimed to assess the prevalence and diagnostic significance of novel 12-lead ECG patterns following COVID-19 infection in elite soccer players. Method(s): We conducted a multicentre study over a 2-year period involving 5 centres and 34 clubs and compared pre COVID and post COVID ECG changes in 455 consecutive athletes. ECGs were reported in accordance with the International recommendations for ECG interpretation in athletes. The following patterns were considered abnormal if they were not detected on the pre COVID-19 infection ECG: (a) biphasic T-waves;(b) reduction in T-wave amplitude by 50% in contiguous leads;(c) ST-segment depression;(d) J-point and ST-segment elevation >0.2 mV in the precordial leads and >0.1 mV in the limb leads;(e) tall T-waves >=1.0 mV (f) low QRS-amplitude in >3 limb leads and (g) complete right bundle branch block. Athletes exhibiting novel ECG changes underwent cardiovascular magnetic resonance (CMR) scans. One club mandated CMR scans for all 28 (6%) athletes, despite the absence of cardiac symptoms or ECG changes. Result(s): Athletes were aged 22+/-5 years (89% male and 57% white). 65 (14%) athletes reported cardiac symptoms. The mean duration of illness was 3+/-4 days. The post COVID ECG was performed 14+/-16 days following a positive PCR. 440 (97%) athletes had an unchanged post COVID- 19 ECG. Of these, 3 (0.6%) had cardiac symptoms and CMRs resulted in a diagnosis of pericarditis. 15 (3%) athletes demonstrated novel ECG changes following COVID-19 infection. Among athletes who demonstrated novel ECG changes, 10 (67%) reported cardiac symptoms. 13 (87%) athletes with novel ECG changes were diagnosed with inflammatory cardiac sequelae;pericarditis (n=6), healed myocarditis (n=3), definitive myocarditis (n=2), and possible/probable myocarditis (n=2). The overall prevalence of inflammatory cardiac sequelae based on novel ECG changes was 2.8%. None of the 28 (6%) athletes, who underwent a CMR, in the absence of cardiac symptoms or novel ECG changes revealed any abnormalities. Athletes revealing novel ECG changes, had a higher prevalence of cardiac symptoms (67% v 12% p<0.0001) and longer symptom duration (8+/-8 days v 2+/-4 days;p<0.0001) compared with athletes without novel ECG changes. Among athletes without cardiac symptoms, the additional yield of novel ECG changes to detect cardiac inflammation was 20% (n=3). Conclusion(s): 3% of elite soccer players demonstrated novel ECG changes post COVID-19 infection, of which almost 90% were diagnosed with cardiac inflammation during subsequent investigation. Most athletes with novel ECG changes exhibited cardiac symptoms. Novel ECGs changes contributed to a diagnosis of cardiac inflammation in 20% of athletes without cardiac symptoms.
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Background: Severe acute respiratory syndrome coronavirus 2 (SARSCoV2) has been associated with several neuro-ophthalmic manifestations. We report a case of bilateral longitudinally extensive optic perineuritis suspected due to SARSCoV2. Case Presentation: A 32-year-old woman developed headaches, photophobia, pulsatile tinnitus, and blurred vision 8 d after having a positive SARS-CoV-2 qualitative polymerase chain reaction (PCR) testing for coronavirus disease 2019 (COVID-19). She was diagnosed with and treated for idiopathic intracranial hypertension (IIH) elsewhere. Repeat evaluation at our institution showed a poor visual acuity in both eyes with Frisen grade II papilledema and cotton wool spots on fundoscopic examination. Orbital magnetic resonance imaging (MRI) showed bilateral longitudinally extensive optic nerve sheath enhancement. Repeat lumbar puncture revealed an elevated cerebrospinal fluid (CSF) opening pressure and protein, a finding that is incompatible with the diagnosis of IIH. Myelin oligodendrocyte glycoprotein, aquaporin-4 (AQP4)-IgG antibodies, and other serological tests for optic neuritis were unremarkable. Her visual acuity partially improved after corticosteroids. With the growing association of demyelinating disorders and COVID-19, unremarkable serological workup, and temporal relation of the patient's symptoms to the infection, we believe that her diagnosis is SARS-CoV-2 associated bilateral optic neuritis. Conclusion(s): There is a growing association between demyelinating disorders and COVID-19 and COVID-19 vaccination, and it is essential to recognize CSF abnormalities that are incompatible with a diagnosis of IIH, such as increased protein in our case, and may lead to an incorrect diagnosis.Copyright © 2023 The Authors. Clinical and Experimental Neuroimmunology published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society for Neuroimmunology.
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Objective: To analyze the clinical characteristics of fatal cardiac adverse events associated with chloroquine, which was recommended for the antiviral treatment of novel coronavirus pneumonia, and provide reference for clinical safe drug use. Method(s): The fatal cardiac adverse events associated with chloroquine were searched from the World Health Organization global database of individual case safety reports (VigiBase). The clinical characteristics of the individual cases with well-documented reports (VigiGrade completeness score >=0.80 or with detailed original reports) were analyzed. The adverse events were coded using the systematic organ classification (SOC) and preferred term (PT) of Medical Dictionary for Regulatory Activities (MedDRA) version 22.1 of International Conference on Harmonization (ICH). Result(s): Up to 23 February 2020, a total of 45 reports of fatal heart injuries related to chloroquine were reported in VigiBase, which were from 16 countries. Of them, 30 reports were fully informative. Among the 30 reports,20 cases developed fatal cardiac adverse events after a single large dose of chloroquine. Of them, 17 cases' fatal cardiac adverse events were caused by overdose of chloroquine (15 cases were suicide or suspected suicide, and 2 children took chloroquine by mistake);3 cases' fatal cardiac adverse events were caused in clinical treatment;18 cases showed arrhythmia and cardiac arrest;6 cases showed prolonged QRS wave or QT interval;6 cases were with hypokalemia, including 4 severe ones. Among the 30 reports, 10 cases developed fatal cardiac adverse events after multiple administration of chloroquine, of which 4 cases were treated with chloroquine for 23 days to 2 months and died of heart failure, cardiac arrest or myocardial infarction;6 cases were treated with chloroquine for 20 months to 29 years and all of them had cardiomyopathy, which were confirmed by endomyocardial biopsy to be caused by chloroquine in 3 cases. Conclusion(s): Cardiac toxicity was the primary cause of fatal adverse events caused by chloroquine;the main manifestation of single large dose of chloroquine was arrhythmia and the manifestation of multiple administration was cardiomyopathy.Copyright © 2020 by the Chinese Medical Association.
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Background: Several studies described occurrence of myocarditis after SARS-CoV-2 vaccination in pediatric patients. Weaimed to characterize the clinical course of myocarditis following SARS-CoV2 vaccination including follow-up data within the prospective German registry for suspected myocarditis in children and adolescents "MYKKE." Method: Patients younger than 18 years with suspected myocarditis and onset of symptoms within 21 days followingSARS-CoV2 vaccination were enrolled within the MYKKE registry. The suspect of myocarditis is valid in patients with clinical symptoms and diagnostic findings typically seen in myocarditis. Clinical data are monitored at initial admission and duringshort-term and long-term follow-up. Result(s): Between July 2021 and August 2022, a total of 48 patients with a median age of 16.2 years (IQR: 15.2-16.8)were enrolled by 13 centers, 88% male. Onset of symptoms occurred at a median of 3 days (IQR: 2-7) after vaccine administration, most frequently after the second dose (52%). Most common symptoms at initial admission were anginapectoris (81%), fatigue (56%), dyspnea (24%) and documented arrhythmias (17%). Initial ECG abnormalities included ST-elevation (48%) and T-wave inversion (23%). Elevated Tropon in was observed in 32 patients (67%) and in 19 cases (40%)NT-proBNP was above the normal range with a median level of 171 pg/mL (IQR: 32-501). 11 (23%) patients presentedwith mildly reduced systolic function at initial echocardiography or cardiac MRI. In 40 patients cardiac MRI and/orendomyocardial biopsy was performed (83%) and diagnosis of myocarditis could be verified in 27 cases (68%). Thirty-nine patients underwent short-term follow-up with a median of 2.8 months (IQR: 1.9-3.9) after discharge. 19 patients (49%)presented with either clinical symptoms (n = 9) and/or diagnostic abnormalities (n = 16) at follow-up. 12 patients (38%)still had medical treatment. Except for one patient with malign arrhythmias (ventricular tachycardia), no major cardiac adverse events were observed during initial admission and follow-up. Conclusion(s): Our data confirm that SARS-CoV-2 vaccine-related myocarditis is characterized by a mild disease course. However, after short-term follow-up a considerable number of patients still presented with symptoms and/or diagnostic abnormalities. Data on long-term follow-up are awaited.
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Coronavirus (COVID19) is a highly contagious virus which had already killed thousands of people and infected millions more throughout the world. One of the primary challenges that medical practitioners encounter in the realm of healthcare is correctly diagnosing patients conditions and infections. So far, the gold standard screening method RT-PCR test which has been designed to detect covid-19 which only has a positive rate ranging between 30 precent and 60 percent. As a result, a system that can accurately identify images and diagnose or anticipate diseases is needed. As a result, we set out to swiftly create a compact CNN architecture capable of recognizing COVID-19-infected individuals. Different CNN architectures are suggested in this paper to extract information from X-rays which further classified into Covid-19, pneumonia, or healthy. Here, we have used two datasets from publically available repositories that are Kaggle and Mendeley [1] [2]. To see how the size of datasets affects CNN performance, we train the suggested CNNs with both the original and enhanced datasets where datasets are splitted into ratios of 80:20 and 70:30 and the comparison is shown. Also suggested CNN model is compared with the five state-of-Art pre-Trained models (VGG-16, ResNet50, InceptionV3, EfficientNetB2, DenseNet121) with the same datasets and splitting ratios. we have also used Some visualization methods through which we can get an exact idea of how CNN functions and the explanation behind the network's decisions. This study suggests a model for classifying COVID-19 patients but makes no claims about medical diagnostic accuracy. © 2022 IEEE.
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Purpose of Review: This review aims to summarize the available literature to identify the incidence and risk factors for persistent interstitial lung abnormalities (ILAs) following hospitalization for COVID-19. The current and prospective treatment options are reviewed in an effort to help pulmonary practitioners care for this burgeoning patient population. Recent Findings: Statistical modeling suggests that 11.7% of all patients hospitalized with COVID-19 have irreversible fibrotic features on long-term follow-up imaging. Summary: The available evidence suggests that up to 30% of patients have ILAs following COVID-19 hospitalization. The radiographic abnormalities improve or resolve in a majority of these patients. However, estimates suggest that up to one-third of these patients have irreversible fibrotic features. Clinical trials of the impact of anti-fibrotic agents are ongoing. As there continue to be thousands of COVID-19 hospitalizations in the USA each week, the management of post-COVID ILAs will become a common problem for the pulmonary practitioner.
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Kawasaki disease (KD) is an acute vasculitis with an intrinsic risk of severe involvement of coronary arteries. The worldwide spread of KD and the importance of early diagnosis for preventing cardiovascular complications have ascertained the need for updating guidelines for prompt disease recognition and treatment efficacy assessment. All KD patients who comply with the definition of classic or atypical disease should be treated with intravenous immunoglobulin (IVIG) soon after diagnosis. The objective of our narrative review was to analyze the medical literature about case reports with atypical KD in relation to diagnosis and potential identification of predictors of non-responsiveness to IVIG. Our analysis has shown that the seminal challenge in KD management is the timeliness of diagnosis, although both extreme variability and transience of clinical manifestations make this goal difficult. A non-negligible percentage of patients, especially in the first 6 months of life, might have atypical manifestations of KD, whose painstaking differential diagnosis may be tricky. Many attempts to develop universal scoring systems and detect children at higher risk of IVIG resistance have been rather unsuccessful. Additionally, KD may show different evolutions according to unraveled demographic, genetic, or epigenetic factors. Further research is needed to elucidate all open questions about KD and clarify the long-term outcome of its potential complications.
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PurposeThe authors examine the short-term stock market reaction surrounding US layoffs during the coronavirus disease 2019 (COVID-19) period. The authors' specific interest is on any changes that may be observed in US stock markets during the COVID-19 outbreak. This information will help us assess the extent to which policymakers adopted at time revenue and expenditures measures to minimize its negative impact.Design/methodology/approachThe authors study the linkage between layoffs announced by firms and stock markets in US for the COVID-19 period between March 2020 and October 2020. This period shows important economic figures;a huge number of job cuts announced by blue-chip companies listed in the New York Stock Exchange (NYSE) due to widespread economic shutdowns. The authors examine whether and to what extent stock markets in US have reacted to layoff announcements during the COVID-19 pandemic using an event-study methodology.FindingsThe study's results show that US layoffs during the pandemic did not cause any abnormalities on the stock returns, either positive or negative. Based on the mean-adjusted volume, the authors find that layoffs increase the stocks' trading volume, especially on the event date and the day following the event. US stocks become more volatile on the days following the event. Interestingly, on the event date, the authors find that stocks get the highest abnormal volatility;however, the result is statistically insignificant.Practical implicationsThe authors suggest that layoffs announcements follow the business cycle quite closely in most industries. The study's results have implications for investors, regulators and policymakers as they permit to examine the effectiveness of the measures adopted.Social implicationsThe study's results show that policymakers reduced uncertainty implementing intensive measures quickly and should follow similar policy in the future pandemic and/or unexpected events.Originality/valueThis paper contributes to the literature in two directions: First, to the best of the authors' knowledge this is the first study that provides empirical evidence and assesses the extent to which a major global shock such as the COVID-19 pandemic may have altered the reaction of US stock markets to layoff announcements. Second, this is the first study on this topic that examines volume and volatility abnormalities, while the authors check the robustness of the findings with different methods to calculate abnormal returns.
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Introduction: Post-COVID-19 autoimmune encephalitis is a rare manifestation following COVID-19. Most cases have not demonstrated solid evidence regarding their pathogenesis. Some believe it to be an immune process. Case presentation: In this case report, we present a case of a young female who presented to our emergency department with visual, auditory, and olfactory hallucinations after successfully treating COVID-19 two weeks prior to this visit. On examination, her vital signs were stable, but she was agitated, distressed, and hallucinating. Neurological examinations were normal. Laboratory investigations, including autoimmune profiles, were all negative. Magnetic resonance imaging of the brain showed non-specific changes in the bilateral frontal area. Electroencephalography (EEG) showed lateralized rhythmic delta activity (LRDA) arising more from the right occipital lobes. Autoimmune psychosis was suspected due to psychosis, abnormal imaging, and abnormal EEG findings. She was given corticosteroids and antipsychotic medication. Her symptoms improved within ten days. On follow-up, she remained well without any return of psychosis. Conclusion(s): Possible autoimmune pediatric encephalitis following COVID-19 is a rare entity that has scarcely been reported. The majority of the cases were reported to have been related to stress following the infection. To establish the correct diagnosis, an extensive workup, including an autoimmune profile, lumbar puncture, magnetic resonance imaging, and electroencephalography, is recommended.Copyright © 2022 The Author(s)
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Introduction: For detecting myocardial injury in severe and critical COVID-19, the electrocardiogram (ECG) is neither sensitive nor specific;but in a resource-poor environment, it remains relevant. Changes in the ECG can be a potential marker of severe and critical COVID-19 to be used for predicting not only disease severity but also the prognosis for recovery. Method(s): The admitting and interval ECGs of 1,333 COVID-19 patients were reviewed in a two-year, single-center, retrospective cohort study. Each was evaluated for 29 pre-defined ECG patterns under the categories of rhythm, rate, McGinn-White and RV overload patterns, axis and QRS abnormalities, ischemia/infarct patterns, and AV blocks before univariate and multivariate regression analyses for correlation with disease severity;need for advanced ventilatory support;and in-hospital mortality. Result(s): Of the 29 ECG patterns, 18 showed a significant association with the dependent variables on univariate analysis. Multivariate analysis revealed that atrial fibrillation, HR >100 bpm, low QRS voltage, QTc >500msec, diffuse nonspecific T-wave changes, and 'any AMI' ECG patterns correlate with disease severity;need for advanced ventilatory support and in-hospital mortality. S1Q3 and S1Q3T3 increased the odds of critical disease and need for high oxygen requirement by 2.5-3 fold. Fractionated QRS increased odds of advanced ventilatory support. Conclusion(s): The ECG can be useful for predicting the severity and outcome of more than moderate COVID-19. Their use can facilitate rapid triage, predict disease trajectory, and prompt a decision to intensify therapy early in the disease to make a positive impact on clinical outcomes.
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Objectives: The study aims to determine the association between electrocardiographic abnormalities and in-hospital mortality of patients with Coronavirus Disease 2019 (COVID-19) infection admitted in a tertiary hospital in the Philippines. Material(s) and Method(s): We conducted a retrospective study of confirmed COVID-19-infected patients. Demographic, clinical characteristics, and clinical outcomes were extracted from the medical records. Electrocardiographic analysis was derived from the 12-lead electrocardiogram (ECG) recorded upon admission. The frequencies and distributions of various clinical characteristics were described, and the ECG abnormalities associated with in-hospital mortality were investigated. Result(s): A total of 163 patients were included in the study, most were female (52.7%) with a median age of 55 years old. Sinus rhythm (40%), nonspecific ST and T wave changes (35%), and sinus tachycardia (22%) were the frequently reported ECG findings. The presence of any ECG abnormality was detected in 78.5% of patients and it was significantly associated with in-hospital mortality (p = 0.038). The analysis revealed a statistically significant association between in-hospital mortality and having atrial fibrillation or flutter (p = 0.002), supraventricular tachycardia (SVT) (p = 0.011), ventricular tachycardia (p = 0.011), third-degree atrioventricular block (AVB) (p = 0.011), T wave inversion (p = 0.005) and right ventricular hypertrophy (RVH) (p = 0.011). Conclusion(s): The presence of any ECG abnormality in patients with COVID-19 infection was associated with in-hospital mortality. ECG abnormalities that were associated with mortality were atrial fibrillation or flutter, SVT, ventricular tachycardia, third-degree AVB, T wave inversion, and RVH. Supporting Documents Association of electrocardiographic abnormalities with in-hospital mortality in adult patients with COVID-19 infection TARRANZA, Jannah Lee [1];RAMIREZ, Marcellus Francis [1,2];YAMAMOTO, Milagros [1] 1 Section of Adult Cardiology, Department of Internal Medicine, University of Santo Tomas Hospital, Manila, Philippines 2 Division of Electrophysiology, Section of Adult Cardiology, Department of Internal Medicine, University of Santo Tomas Hospital, Manila, Philippines.
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Backgrounds: To report the first case of left optic neuritis and perineuritis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) BNT162b2 mRNA vaccination. Case presentation: A 39-year-old woman was referred and admitted to our hospital due to transient left visual field abnormality with left ophthalmalgia and headache 12 days after the first vaccination dose of SARS-CoV-2 (BNT162b2). On admission (Day 2), she presented with left ophthalmalgia and headache without any other neurological deficits including the movement of eyeballs, visual field, visual acuity, or nystagmus. MRI on Day 2 suggested slight left optic neural swelling;Gadolinium-enhanced MRI on Day 4 revealed left optic perineuritis. Test for serum anti-aquaporin 4 antibody was negative, whereas anti-myelin oligodendrocyte glycoprotein (MOG) antibody was positive. She was diagnosed with left optic perineuritis after SARS-CoV-2 mRNA vaccination. Her visual disturbance never recurred and her ophthalmalgia and headache subsided only with anti-inflammatory agents. Discussion(s): Many cases of optic neuritis associated with vaccinations have been reported except for SARS-CoV-2 BNT162b2 mRNA. To our knowledge, only one neuromyelitis optica case was associated with anti-MOG antibody. Therefore, we propose that SARS-CoV-2 mRNA vaccination may induce transient optic neuritis and perineuritis, associated with anti-MOG antibody in the present case. Conclusion(s): This is the first case of left optic neuritis and perineuritis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) BNT162b2 mRNA vaccination.Copyright © 2022
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Much of today's data are represented as graphs, ranging from social networks to bibliographic citations. Nodes in such graphs correspond to records that generally represent entities, while edges represent relationships between these entities. Both nodes and edges in a graph can have attributes that characterize the entities and their relationships. Relationships are either explicitly known (like friends in a social network), or they are inferred using link prediction (such as two babies are siblings because they have the same mother). Any graph representing real-world data likely contains nodes and edges that are abnormal, and identifying these can be important for outlier detection in applications ranging from crime and fraud detection to viral marketing. We propose a novel approach to the unsupervised detection of abnormal nodes and edges in graphs. We first characterize nodes and edges using a set of features, and then employ a one-class classifier to identify abnormal nodes and edges. We extract patterns of features from these abnormal nodes and edges, and apply clustering to identify groups of patterns with similar characteristics. We finally visualize these abnormal patterns to show co-occurrences of features and relationships between those features that mostly influence the abnormality of nodes and edges. We evaluate our approach on datasets from diverse domains, including historical birth certificates, COVID patient records, e-mails, books, and movies. This evaluation demonstrates that our approach is well suited to identify both abnormal nodes and edges in graphs in an unsupervised way, and it can outperform several baseline anomaly detection techniques. © 2022 Copyright held by the owner/author(s).
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BACKGROUND: The COVID-19 vaccine is effective in preventing severe cases of COVID-19. For women, gynecological adverse events, such as menstrual irregularities and irregular bleeding, could be a concern after COVID-19 vaccination. In this study, we investigated gynecological adverse events in the vaccinated Japanese female population. METHODS: We conducted a survey-based study with health-care workers, including medical doctors and nurses, medical coworkers, and medical university faculty, staff, and students, at a single medical school and affiliated hospital in Japan. We used McNemar's test and network analysis. RESULTS: Overall, we obtained 819 responses, and 424 were from females. After the exclusion of contradictory answers, 309 surveys were finally considered appropriate for the analysis. The frequencies of abnormal bleeding were 0.6%, 1.0%, and 3.0% for the first, second, and third doses, respectively. An irregular menstrual cycle was more common than abnormal bleeding: 1.9%, 4.9%, and 6.6% for the first, second, and third doses, respectively. Network analysis revealed that abnormal bleeding and an irregular menstrual cycle were not associated with other adverse reactions. CONCLUSION: The present study showed that the effects of COVID-19 vaccination on menstruation seem limited.
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COVID-19 Vaccines , COVID-19 , Female , Humans , BNT162 Vaccine , Menstruation Disturbances , Menstrual CycleABSTRACT
Although mental health issues and other behavioral disturbances do not always rise to the level of medical diagnostic criteria, the qEEG and neuron feed back community has demonstrated that multiple symptoms and behaviors in both clinical and nonclinical populations can be improved by EEG biofeedback. Neurophysiological changes and EEG abnormalities are often nonspecific to symptoms and expressed behaviors due to known confounds such as genetics, life experience, health status, brain injury, and now pandemic-related psychosocial stressors and neurological tissue damage from SARS-CoV2 infection. The traumatic brain injury field is familiar with this problem, widely acknowledging that no two TBIs are alike. Neurofeedback offers compelling potential to improve psychosocial and cognitive-affective functioning for millions who are suffering, without the use of medications, and the need has never been greater. However, despite a half-century of development in the field, neurotherapy has not expanded beyond its status as a boutique practice, with only about 7,500 practitioners in the United States at present. A lack of consensus regarding evaluations and protocol development has created confusion and mistrust in the scientific community and the public. Potential practitioners must navigate a steep learning curve and invest significant time and money in training, equipment, and continuing education. Current models are often dependent on complex clinical decision-making to determine which metrics are included in the feedback process. These decisions are in turn dependent on clinician training, equipment capabilities, and experience. Experienced clinicians continue to debate which failure mode in the brain should determine the feedback protocols used on any given subject. Within the last decade the complexity of protocol determination has exponentially increased as new modalities introduced various forms of external stimulation to drive brain processes or interrupt habitual circuit behaviors. Conventional models for assessing the effect of neuron feed back protocols have been insufficient to evaluate the constellation of outcomes reflecting changes in both homeostatic (internal) and allostatic (responses to external stimuli) processes, as can be demonstrated in a recent publication. Many interventions have not adequately appreciated and accounted for the complexity of the systems involved in producing any one component of EEG signal or in allowing for adequate response from a wide range of brain failure modes. A new model of delivery is emerging which can provide affordable, accessible, effective neurotherapy. This presentation will describe an artificial intelligence-driven approach that can individualize therapy on a large scale. We will discuss the evolution of prior neuron feed back paradigms and review recently published data that support the efficacy and rationale for using an integrated model of allodynamic, multinetwork neuron feed back training. These data will demonstrate that it is possible, using an algorithm-driven systemic paradigm, to individualize results within a heterogenous population of neurophysiologically dysfunctional brains..