Fear of COVID-19 among critical care nurses of public hospitals in Lahore: empirical evidence during third wave

The world has seen a pandemic that dis-rupted life. Till now there are aftershocks of COVID-19 such as Omicron instilling fear among individuals. Healthcare staff is on alert specifically the nurses have suffered a lot mentally due to this issue by developing fatigue. The study was conducted during the deadly 3rd COVID-19 wave. The data were collected by developing the questionnaire of the previously validated measures related to the variables under study from nurses working in the intensive care unit, critical care unit, and floor wards of COVID-19 at Services Hospital, Lahore. A total of 140 questionnaires were used for data analysis. The study used Statistical Package for Social Sciences for frequency and descrip-tive statistics. Whereas the outcomes of fear of COVID-19 were assessed by using the latest Smart Partial Least Squares software which allows to assess the complex research frameworks. The results of the study revealed that the fear of COVID-19 results in poor quality of life among nurses and fatigue. Resilience among nurses can reduce the negative consequences but did not get statistical support.

COVID-19 Vaccination during Pregnancy: A Structured Electronic Medical Record Data Study

Objectives: To compare pregnancy loss rates, preterm birth rates and gestational age at delivery in women vaccinated against COVID-19 during pregnancy vs. those unvaccinated. Method(s): Data were captured from Dorsata Prenatal, an electronic medical record (EMR) system that captures obstetrical data for tens of thousands of pregnancies annually. Patients who delivered between February 11, 2021-June 2, 2022, were included. The vaccinated group included women who had at least one COVID-19 vaccination documented in their EMR between 30 days prior to pregnancy and delivery. The unvaccinated group included women without a COVID-19 vaccination documented. The primary outcome measure was gestational age (GA) at delivery. We analyzed the data using chi-square tests, with significance set at p<0.01. Result(s): A total of 51,994 pregnant women were identified-7,947 (15.3%) in the vaccinated group and 44,047 (84.7%) in the unvaccinated group. Vaccination rate varied by race (Asian: 19.7%;White: 17.3%;Black: 11.2%, P<0.001), ethnicity (Latino: 8.6%;Not-Latino: 18.7%;P<0.001), marital status (Married: 19.2%;Single: 8.8%;P<0.001), mother's age (>=35 years: 20.0%;<35 years 14.2%;P<0.001), and region (Northeast: 19.2%;South: 15.2%;West: 9.1%;P<0.001). The vaccinated group had significantly lower rate of preterm delivery (Gestational Age [GA]<37 weeks;vaccinated: 7.8% vs. unvaccinated: 9.6%;P<0.001), and significantly lower rates of pregnancy loss (GA<20 weeks;vaccinated: 1.1% vs. unvaccinated: 4.1%;P<0.001). Conclusion(s): This is one of the largest real-world studies to date in women who received the COVID-19 vaccination during pregnancy. Vaccination rates varied significantly across race/ethnicity. Vaccinated patients had lower preterm delivery and pregnancy loss rates compared with unvaccinated patients.Copyright © 2023

E-Education Application Using Flutter: Concepts and Methods

In this fast-paced world, education is the passport to a better future, as tomorrow belongs to those who prepare for it today. This research aims to bridge the gap between tutees and tutors. It also aims to develop the mind of tutees in order to shape their future character, calibre, and character. COVID-19 has altered our perspective regarding education;based on our research, illiteracy is a significant problem in Pakistan. In addition, finding a mentor with the right skills, experience, and reliability is the most challenging aspect of finding mentorship for yourself or your children. Our in-person and online survey analysis revealed that peer tutoring allows for higher student response rates and feedback, leading to better academic achievement. In addition, it provides students with more opportunities to practice specific skills, which leads to higher retention rates. With the help of the peer-Tutoring concept, when a student teaches another student a topic, it also helps the tutor and tutee gain a deeper understanding of it. There is a positive impact on education in Pakistan because of peer tutoring. As a result, we incorporate this approach into the application to provide tutees with an education and the idea of training their minds to think from tutors who have more experience and knowledge about the relevant field. It would be helpful to identify factors that could make these campaigns more effective with further research. © 2023 IEEE.

Demographic features and outcomes in critically ill mechanically ventilated COVID-19 patients with respiratory failure in a resource limited ICU setting Report from a tertiary care center in Karachi

Background: Studies done on severe COVID-19 have revealed a wide heterogeneity in intensive care clinical outcomes across various countries. We aimed to identify the demographic features and outcomes of mechanically ventilated COVID-19 patients with respiratory failure in Pakistan in resource limited settings. Methods: This was a cross-sectional study conducted at the COVID-19 Intensive care unit (ICU) of Jinnah postgraduate medical center in Karachi, Pakistan. 86 patients who received mechanical ventilation in a period of five months from 1/2/2021 till 30/6/2021 were included in the study. Patient demographic characteristics, comorbidities, clinical manifestations of COVID-19 infection, laboratory values at the time of presentation (hemoglobin, Neutrophil lymphocyte ratio, platelets, glomerular filtration rate, C-reactive protein, D-dimers, Ferritin, liver function tests and electrolytes) and mode and duration of ventilation, final outcome (survivor vs. non-survivor) and cause of death in non-survivors were recorded. Data was analysed using SPSS 26. Patient characteristics were compared among those who died early before 7 days with those who survived for more than 7 days using P sample t-test. Results: 86 patients, who required mechanical ventilation because of severe respiratory distress not alleviated by non-invasive methods of ventilation, were included in the study. 66.3% (n=57) were males and 33.7% (n=29) were females. Mean age was 59 (SD 12). The most common comorbidities were diabetes mellitus and hypertension 44.2% (n=38) each. Only 3 (3.4%) of mechanically ventilated patients were extubated and 1 patient was eventually discharged home on room air. The mortality rate was 98.8% and only one patient survived. The most common causes of death were respiratory failure (86%, n=74), renal failure (48.8%, n=42) and sepsis (18.6%, n=16). Conclusion: Mortality in COVID-19 patients who require mechanical ventilation is very high in resource limited settings because of the lack of essential medications, specialized teams and established protocols of ICU management and is not related to the demographic characteristics and comorbidities of patients and severity of disease at presentation. © 2022 Authors.

Alpha Fusion Adversarial Attack Analysis Using Deep Learning

The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN classification model is developed for classifying COVID-CT images. Secondly, an alpha fusion attack is generated to fool the classification model. The alpha fusion attack is tested in the last phase on a modified LSTM-based CNN (CNN-MLSTM) model and other pre-trained models. The results of CNN models show that the accuracy of these models dropped greatly after the alpha-fusion attack. The highest F1 score before the attack was achieved is 97.45 And after the attack lowest F1 score recorded is 22%. Results elucidate the performance in terms of accuracy, precision, F1 score and Recall. © 2023 CRL Publishing. All rights reserved.

A crisis within a crisis: Role of COVID-19 pandemic in poor compliance of Community-based Management of Severe Acute Malnutrition among children younger than five years in Pakistan

Introduction In order to attain Sustainable Development Goal 2 (SDG-II) of eradicating malnutrition among children by 2030, Pakistan has initiated a Community-based Management of Severely Acute Malnutrition (CMAM) program. This program has been established at the public level to detect and treat uncomplicated Severely Acute Malnourished (SAM) children at an early stage. However, during the outbreak of COVID-19, very poor compliance with the CMAM program was observed. Consequently, the nutritional quality of children's diets has deteriorated, with malnutrition rates expected to rise. Therefore, this study has been set up to evaluate the effect of the COVID-19 lockdown on the health of SAM children and compliance with the CMAM program. Methodology This study used a multicenter cross-sectional design in District Dera Ghazi Khan's rural areas located in the Southern Province of Punjab. Data were collected from the parents/guardians of SAM children through the researcher-administrated questionnaire. The sample size was 196, and data were analyzed through SPSS version 25. Results The majority of the children enrolled were males (52.5%), had fathers aged between 41 and 50 years (52.0%), mothers aged between 21 and 30 years (52.5%), had illiterate fathers (40.1%), illiterate mothers (73.8%) and had a monthly household income of PKR <15,000 (91.1%). All of the respondents mentioned that COVID-19 affected them in one way or the other (100.0%), with a majority of them did not visit the hospital during COVID-19 for their SAM child (52.5%) as they were afraid of COVID-19 (63.2%) and/or they lacked access to transport for visiting a hospital (93.4%). Bivariate analysis revealed that the father's age (P = 0.02) and income (P = 0.00) is associated with the perceived effect of COVID-19 on income. In contrast, only the gender of the child (P = 0.00) is related to the visit to the hospital, and the gender of the child (P = 0.01) and mother's literacy (P = 0.00) is associated with the choice of treatment from any other setup, including Hakeem and Peer. Conclusion This study concludes that health emergencies like the COVID-19 pandemic pose a significant barrier to access to healthcare services and subject a more vulnerable state to already vulnerable groups like SAM children. To lessen their vulnerability, initiatives like mobile health care services should be introduced, especially for socially disadvantaged communities, localities, and groups on regular basis and for future emergencies.

Vocal Fold Paralysis Following COVID-19 Vaccination in a Patient on Hemodialysis

Introduction: With the increase in number of the people receiving COVID-19 vaccination, different adverse effects associated with vaccine are being described. While vocal fold paresis (VFP) after both COVID-19 disease and COVID-19 vaccination has been rarely reported, data on this entity in dialysis population is still lacking. We present a case of VFP in a hemodialysis patient following the administration of Pfizer-BioNTech COVID-19 vaccine. Case Description: 45-year-old West Indian female with DM, HTN and End Stage Kidney Disease 2/2 Focal Segmental Glomerulosclerosis s/p kidney transplant that failed after 16 years (on low dose tacrolimus) requiring to start hemodialysis presented to the ED with complaints of voice hoarseness with dysarthria and throat itching that started ~30- 45 minutes after having received the first dose of Pfizer-BioNTech COVID-19 vaccine. She underwent Fiberoptic Indirect Laryngoscopy that showed widely patent airway with mobile vocal cords bilaterally. Symptoms were thought to be secondary to a reaction to the vaccine vs mild GERD. She received steroids and was discharged home within 24 hours after symptomatic improvement on steroid therapy. Her voice normalized within a week. Six months later, she received the second dose of Pfizer-BioNTech vaccine, ~30 minutes after which again developed dysphonia and dysarthria. This time, she was found to have bilateral VFP with incomplete closure. Steroid therapy was reinitiated and is slowly being tapered. Her dysarthria has improved;however, she continues to have hoarseness of voice even after 9 months of having received 2nd dose of vaccine. She has not received the booster dose of vaccine. Discussion(s): Current guidelines recommend booster doses of COVID-19 vaccine for immunocompromised individuals including those on dialysis. The benefits of vaccination markedly outweigh the risk of very rarely reported development of VFP after vaccination. Further research is needed to determine the prevalence of this complication in dialysis patients and to elucidate the underlying mechanisms leading to it.

Kidney Biopsy Proven Thrombotic Microangiopathy in a Heart Transplant Recipient

Introduction: Thrombotic Microangiopathy (TMA) after non renal solid organ transplantation is very rare. While few cases of TMA following liver and lung transplants have been published, it has been very rarely reported following orthotopic heart transplant (OHT). We report the first case of kidney biopsy proven De Novo TMA after OHT. Case Description: 58-year-old male with non ischemic cardiomyopathy undergoes OHT in Jan 2021. He had normal renal function pre transplantation. Post-operatively he had pericardial effusion and in that setting developed oliguric AKI from ATN requiring dialysis. His renal function recovered and was discharged without dialysis. He was on tacrolimus, MMF and steroid regimen. Frequent heart biopsies were negative for rejection. In March 2021 the patient was admitted for GI bleed and again noted to have AKI. However, during this episode he developed proteinuria of over 2gm, new compared to previous urine studies. He was discharged with a serum creatinine of 2.6mg/dL. By July 2021 renal function worsened and he underwent a renal biopsy on 7/30/21 which showed acute and chronic TMA, related to calcineurin inhibitor use. Viral causes and other medications were ruled out (CMV, BK, adenovirus, SARs-COV2). Tacrolimus was held and he was initiated on Everolimus. Genetic and complement testing revealed normal complement levels, an elevated SC5b-9 complex, heterozygous for the APOL1 gene mutation (c.[1024A>G;1152T>G] p.[Ser342Gly;Ile384Met] (G1 allele)), and heterozygous for the CFHR5 gene mutation, suggestive for complement mediated TMA. He was initiated on Eculizumab. After two doses of Eculizumab he was again admitted with acute respiratory failure requiring intubation secondary to mTOR induced pneumonitis. His renal function worsened and he was reinitiated on dialysis. After a multidisciplinary discussion, he was transitioned to cyclosporine for immunosuppression. He continues to be on dialysis and cyclosporine with eculizumab without other non-renal findings of TMA. He is currently being evaluated for kidney transplantation. He has no signs of OHT rejection on heart biopsies. Discussion(s): The early identification and treatment of TMA in OHT is important in preventing further complications associated with it. Although rare as compared to other solid organ transplants, it is essential to maintain TMA as a differential diagnosis for AKI following OHT.

Concerns of University Students Regarding COVID-19 Lockdown: An Online Cross-Sectional Survey in Karachi, Pakistan

Aim: To assess the concerns of university students regarding COVID-19 lockdown. Methods: A Cross-Sectional online survey was conducted among student population living in different socio-economical areas of Karachi. Information was gathered on their age, gender, education level, occupation status, area of residence, and knowledge about lockdown due to Covid-19. These variables were examined according to the socio-economic status of the area where students reside. Results: A total of 200 subjects above 20 years were interviewed out of which data was analyzed for 160 subjects. The majority of students were between the ages of 20-25 years, females, Muslims, and unemployed. According to 86.9% of students COVID- 19 can be prevented by avoiding contact and almost 74.4% students were in favor of lockdown further 37.5% students wanted no gaps between lockdowns. In this study, 31.3% spent time using phones while 15% spent time reading while 22% of the students spent their time in physical activity. Almost 66.3% of students did not develop any psychological problems. About 77.5% did not face any financial problems. Conclusion: Most of the respondents were in favor of lockdown as COVID-19 spread can be prevented by avoiding contact. Study highlighted COVID-19 lockdown had no effect on mental health of the respondents. This study will help in creating awareness regarding lockdown. It will enlighten new arenas for public health experts and stakeholders to develop new strategies, and interventions and predict a preparedness program plan for future Pandemic.

Minimal Change Disease Relapse After SARS-CoV-2 Booster Vaccine

Immune dysregulation has been postulated as a pathogenetic mechanism for minimal change disease (MCD) and several vaccines have been reported to act as a trigger for relapse. While cases of both de-novo MCD and MCD relapse have been reported following severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) mRNA vaccinations, we report, to the best of our knowledge, the first case of MCD relapse following booster dose of Pfizer-BioNTech SARS-CoV-2 vaccine. 63-year-old Italian male, with history of nephrotic syndrome secondary to kidney biopsy proven MCD, who had achieved complete remission with steroid therapy, had follow up labs done that showed spot urine protein: creatinine of 10.1 and albumin of 3.0g/dL. He had received the booster dose of Pfizer-BioNTech SARS-CoV-2 vaccine 2 weeks ago, and endorsed generalized weakness, puffiness over face, edema over upper extremities that appeared within a week after administration of the vaccine, and weight gain of 10 lbs over past week. Blood pressure was elevated (152/78 mmHg). He denied any recent infections, use of Nonsteroidal Anti-Inflammatory Drugs, or antibiotics. Other diagnostic work up revealed hypertriglyceridemia, normal serum creatinine. Serological work up for secondary causes of glomerular diseases was negative. He was initiated on oral prednisone therapy. Spot urine protein:creatinine decreased to 1.1, 2 weeks after initiation of steroids. Vaccination is a recognized trigger for relapse of nephrotic syndrome. mRNA vaccines are expected to produce a higher antibody response as well as increased production of cytokines and chemokines. This can lead to dysregulation in permeability factors that can result in relapsing glomerulonephritis. As data on adverse effects of SARS-CoV-2 vaccines continue to evolve, we suggest to closely monitor patients with history of nephrotic syndrome for relapse after receipt of the SARS-CoV-2 vaccine, including the booster dose. Further studies are needed to determine whether relapse of MCD is specific for SARS-CoV-2 mRNA vaccination and to decipher mechanisms for possible immune dysregulation in those patients. This may help in formulation of protocol for vaccination in patients with nephrotic syndrome and contribute to informed decision making.

Modified Anam-Net Based Lightweight Deep Learning Model for Retinal Vessel Segmentation

The accurate segmentation of retinal vessels is a challenging task due to the presence of various pathologies as well as the low-contrast of thin vessels and non-uniform illumination. In recent years, encoder-decoder networks have achieved outstanding performance in retinal vessel segmentation at the cost of high computational complexity. To address the aforementioned challenges and to reduce the computational complexity, we propose a lightweight convolutional neural network (CNN)-based encoder-decoder deep learning model for accurate retinal vessels segmentation. The proposed deep learning model consists of encoder-decoder architecture along with bottleneck layers that consist of depth-wise squeezing, followed by full-convolution, and finally depth-wise stretching. The inspiration for the proposed model is taken from the recently developed Anam-Net model, which was tested on CT images for COVID-19 identification. For our lightweight model, we used a stack of two 3 x 3 convolution layers (without spatial pooling in between) instead of a single 3 x 3 convolution layer as proposed in Anam-Net to increase the receptive field and to reduce the trainable parameters. The proposed method includes fewer filters in all convolutional layers than the original Anam-Net and does not have an increasing number of filters for decreasing resolution. These modifications do not compromise on the segmentation accuracy, but they do make the architecture significantly lighter in terms of the number of trainable parameters and computation time. The proposed architecture has comparatively fewer parameters (1.01M) than Anam-Net (4.47M), U-Net (31.05M), SegNet (29.50M), and most of the other recent works. The proposed model does not require any problem-specific pre- or post-processing, nor does it rely on handcrafted features. In addition, the attribute of being efficient in terms of segmentation accuracy as well as lightweight makes the proposed method a suitable candidate to be used in the screening platforms at the point of care. We evaluated our proposed model on open-access datasets namely, DRIVE, STARE, and CHASE_DB. The experimental results show that the proposed model outperforms several state-of-the-art methods, such as U-Net and its variants, fully convolutional network (FCN), SegNet, CCNet, ResWNet, residual connection-based encoder-decoder network (RCED-Net), and scale-space approx. network (SSANet) in terms of {dice coefficient, sensitivity (SN), accuracy (ACC), and the area under the ROC curve (AUC)} with the scores of {0.8184, 0.8561, 0.9669, and 0.9868} on the DRIVE dataset, the scores of {0.8233, 0.8581, 0.9726, and 0.9901} on the STARE dataset, and the scores of {0.8138, 0.8604, 0.9752, and 0.9906} on the CHASE_DB dataset. Additionally, we perform cross-training experiments on the DRIVE and STARE datasets. The result of this experiment indicates the generalization ability and robustness of the proposed model.

Sustainable supply chain management performance in post COVID-19 era in an emerging economy: a big data perspective

Purpose: Big data analytics capabilities are the driving force and deemed as an operational excellence approach to improving the green supply chain performance in the post COVID-19 situation. Motivated by the COVID-19 epidemic and the problems it poses to the supply chain's long-term viability, this study used dynamic capabilities theory as a foundation to assess the imperative role of big data analytics capabilities (management, talent and technological) toward green supply chain performance. Design/methodology/approach: This study was quantitative and cross-sectional. Data were collected from 374 executives through a survey questionnaire method by applying an appropriate random sampling technique. The authors employed PLS-SEM to analyze the data. Findings: The findings revealed that big data analytics capabilities play a significant role in boosting up sustainable supply chain performance. It was found that big data analytics capabilities significantly contributed to supply chain risk management and innovative green product development that ultimately enhanced innovation and learning performance. Moreover, innovation and green learning performance has a significant and positive relationship with sustainable supply chain performance. In the post COVID-19 situation, organizations can enhance their sustainable supply chain performance by giving extra attention to big data analytics capabilities and supply chain risk and innovativeness. Originality/value: The paper specifically emphasizes on the factors that result in the sustainability in supply chain integrated with the big data analytics. Additionally, it offers the boundary condition for gaining the sustainable supply chain management. © 2022, Emerald Publishing Limited.

The impacts of the COVID-19 outbreak on the education sector: Evidence from Pakistan

The COVID-19 outbreak has prevented students from contributing towards the economic growth of Pakistan. It first disrupted the education system in China and later entered Pakistan to close all levels of educational institutions/sectors since the middle of March 2020. This study aims to highlight the COVID-19 outbreak's effects on educational sector in Pakistan. Pakistan's overall public sector expenditure as a percentage of GDP before the pandemic was already low as compared to regional level, but due to the pandemic, it has dropped down significantly. This study seeks to answer two important questions: (1) What are the impacts of COVID-19 outbreak on Pakistan? (2) Will the closure of educational institutions impact the economic growth of Pakistan? According to empirical and theoretical findings, the results show that the lack of school education for a long period of time will contribute towards unskilled human capital. The COVID-19 outbreak has impacted student learning activities, which may increase the dropout rates, loss of mental health, and consequently, may impact the economic growth of Pakistan later. © 2021, IGI Global.

Impact of telemedicine. Validation of video triage for acute stroke: Admission reduction, improved diagnostic accuracy beyond fast & reduction in variance of hyperacute intervention times

Background and Aims: As a consequence of the COVID-19 pandemic prehospital video assessment (PHVA) of possible stroke was commenced by University College London Hospital and London Ambulance Service. We compared the accuracy of this assessment tool against conventional screening with FAST. Methods: We examined the accuracy of PHVA from May 2020 to April 2021, together with final diagnoses, timings for treatment provided and ambulance crew primary assessment (FAST status) wherever this was recorded. Results: Of 1300 patients triaged, 600 (46%) were sent to HASU, 570 (44%) were AE diverts and 65 (5%) were sent to their local TIA clinic. 40 patients (3%) were returned to their LAS pathway and missing data was noted for 25 patients (2%). From 426 patients where FAST status was recorded, diagnosis of likely stroke/TIA was correct in 89% (278) of PHVA versus 55% (173) of FAST assessed cases. Correct identification of non-stroke was correct in 84% (96) of PHVA versus 65% (75) of FAST assessed cases. A positive predictive value of 93% (PHVA) versus 59% (FAST) and negative predictive value 96% (PHVA) versus 84% (FAST) is noted. 46 thrombolysis and 12 thrombectomy cases with median treatment time before and during PHVA of 35 minutes (Interquartile range (IQR)-26) vs 33 (IQR-15) and 136 (IQR-87) vs 125 (IQR-49) minutes respectively, were noted. Conclusions: PHVA has been validated further, showing superior accuracy to the existing FAST assessment and may improve hyperacute treatment times and their variance.

Efficacy of tocilizumab in critically ill COVID-19 patients: a retrospective cohort

Background & Objective: Covid-19 is a complex disease with unpredictable blended pattern, and it resembles the cytokine release syndrome (CRS), marked with vasculopathy, coagulopathy, ARDS, multi-organ failure, and aggressive rise of inflammation markers in the serum. Tocilizumab (TCZ) has been in use as an off-label drug due to its antagonist activity on IL-6 receptor. This study compared the efficacy of standard of care (SOC), and SOC along with TCZ, in critically ill COVID-19 patients. Methodology: In this retrospective cohort, we included 74 critically ill COVID-19 patients, aged between 18 to 90 y. Those who received only SOC were placed in the SOC group, while patients who received TCZ in addition to SOC, were placed in the TCZ + SOC group. The SOC included low molecular weight heparin (LMWH) 60 mg S/C OD, dexamethasone 6 mg IV OD, remdesivir (antiviral) 200 mg IV stat then 100 mg IV OD for 5 days and when needed 10 days, antibiotics for secondary infection e.g., Azithromycin 500 mg IV OD, in the presence of High flow Oxygen (HFO) or CPAP. X-rays chest, serum levels of lactate dehydrogenase (LDH), D-Dimers, ferritin, pro-BNP, C-reactive protein (CRP), total leukocyte count (TLC), renal and liver markers, serum electrolytes, sugar levels, and ABGs were obtained from the data, at the time of admission in ICU and on the 7th day of ICU stay. Results: 57% patients received only SOC while 43% received TCZ in addition to SOC. Improvement in hypoxia and radiological findings on day-7 was more in SOC' group than TCZ+ SOC' group (52% vs. 34% and 52% vs. 31% respectively), but it was not statistically significant. Overall improvement in inflammation markers on day-7 was similar in both groups with p = 0.925. Survival was 45% vs. 37.5% in SOC' vs. TCZ+ SOC' group respectively (p = 0.504). Conclusion: Tocilizumab does not alter the overall survival of critically ill COVD-19 patients. © 2021 Faculty of Anaesthesia, Pain and Intensive Care, AFMS. All rights reserved.

Bilateral Adrenal Gland Infarction in the Setting of COVID-19 Infection

A 71-year-old man with past medical history pertinent for chronic kidney disease stage III, hypertension, hyperlipidemia, atrial fibrillation (AF) on oral anticoagulation, and hypothyroidism presented with acute on chronic kidney disease (AoCKD), elevated transaminases and failure to thrive. COVID-19 polymerase chain reaction (PCR) was positive. Chest x-ray showed patchy bilateral airspace disease. Computed tomography (CT) of chest, abdomen, pelvis and magnetic resonance imaging (MRI) abdomen were unremarkable apart from Bilateral patchy infiltrates in the lungs. The patient did not require steroids and/or remdesivir as he was not hypoxic. He was discharged five days later on rivaroxaban. A week after discharge, he presented with worsening generalized weakness, worse in the lower extremities, culminating in a fall. On readmission, laboratory studies revealed rhabdomyolysis, AoCKD, and elevated transaminases. Additionally, a leukocytosis was present without symptoms concerning for infection. COVID-19 testing was repeated and was positive, with the remainder of the infectious workup including blood cultures being unremarkable. A repeat CT scan of chest, abdomen, pelvis with contrast demonstrated fat stranding around both adrenals concerning for infarction in the setting of COVID-19 infection (image 1). Subsequently, a morning cortisol was obtained, which was low concerning for adrenal insufficiency. This suspicion was confirmed with cosyntropin stimulation testing, which demonstrated adrenal insufficiency. He was started on hydrocortisone and fludrocortisone with improvement in symptoms over the next three days. Common causes of adrenal infarction and hemorrhage include thromboembolic disease, hypercoagulable states, HIT, physical trauma, the postoperative state, sepsis, and any cause of severe physiologic stress. We are still gaining insight into the multisystem disease manifestations of COVID-19 and its prothrombotic effects despite chronic oral anticoagulation therapy at prophylactic doses for other maladies like AF. Adrenal insufficiency due to infarction should be considered in patients who present with non-specific symptoms such as weakness, hypotension, electrolyte abnormalities, abdominal pain, nausea and/or vomiting in the setting of COVID-19 infection when other causes have been ruled out. Adrenal infarction has been reported in patients with COVID-19 infection, such as our patient. The adrenal glands are susceptible to infarction and hemorrhage due to their vascularity. It has been hypothesized that the hypercoagulable state wrought by SARS-CoV-2 viremia poses a particular risk to the adrenal microvasculature. In turn, reperfusion injury and hemorrhage can ensue due to anticoagulant therapy and secondary adrenal necrosis.

Digital civic participation and misinformation during the 2020 taiwanese presidential election

From fact-checking chatbots to community-maintained misinformation databases, Taiwan has emerged as a critical case-study for citizen participation in politics online. Due to Taiwan’s geopolitical history with China, the recent 2020 Taiwanese Presidential Election brought fierce levels of online engagement led by citizens from both sides of the strait. In this arti-cle, we study misinformation and digital participation on three platforms, namely Line, Twitter, and Taiwan’s Professional Technology Temple (PTT, Taiwan’s equivalent of Reddit). Each of these platforms presents a different facet of the elec-tions. Results reveal that the greatest level of disagreement occurs in discussion about incumbent president Tsai. Chinese users demonstrate emergent coordination and selective discussion around topics like China, Hong Kong, and President Tsai, whereas topics like Covid-19 are avoided. We discover an imbalance of the political presence of Tsai on Twitter, which sug-gests partisan practices in disinformation regulation. The cases of Taiwan and China point toward a growing trend where regular citizens, enabled by new media, can both exacerbate and hinder the flow of misinformation. The study highlights an overlooked aspect of misinformation studies, beyond the veracity of information itself, that is the clash of ideologies, practices, and cultural history that matter to democratic ideals. © 2021 by the authors;licensee Cogitatio (Lisbon, Portugal). tion 4.0 International License (CC BY).