Outcomes following application of high flow nasal cannula and non-invasive ventilation during the second COVID-19 wave in Singapore

Introduction: COVID-19 pneumonia can result in significant morbidity and mortality in affected individuals. Our audit aims to study the respiratory outcomes of patients with COVID-19 pneumonia following the use of HFNC and NIV during the second wave of the pandemic. Method(s): We analysed the outcomes of 94 patients admitted to a tertiary combined HDU/ICU with severe COVID-19 pneumonia requiring non-invasive support between July and December 2021. Result(s): 94 patients were admitted during the study period. ICU mortality rate was 22% (21/94), total in-hospital mortality was 38% (36/94). HFNC was used as first line respiratory support in 58/94 cases, of which 39.6% required intubation. Of those patients who failed HFNC, time to intubation was significantly higher in those patients who passed away than those who were intubated and survived (mean 6.08 days vs 2.86 days, p < 0.05 one sided T-test). In all patients, very late intubation defined as intubation > 5d post admission to ICU, occurred in 6/41 patients, of which the mortality rate was 100%. ROX score performed at 12 h post intubation was unable to discriminate those who succeeded with HFNC and those who required intubation (mean ROX 7.24 vs 7.9, p > 0.05). NIV was used in combination with HFNC pre-intubation in 5/23 HFNC cases with 100% mortality rate. Extubation failure rates were low (5/94) and use of tracheostomy was uncommon (4/94;all 4 survived ICU stay, 3 eventually died in hospital). Conclusion(s): HFNC failure with prolonged use of HFNC and use of multiple non-invasive device strategies before intubation was associated with a high risk of mortality. Conventional measurements of HFNC failure in the form of a 12 h ROX score could not assist the clinician in predicting those patients at risk of HFNC failure.

Effects of SARS-CoV-2 Membrane Glycoprotein on Host Pre-mRNA 3' Processing

Objective To investigate the effect of SARS-CoV-2 membrane protein on the processing of the 3' untranslated region (UTR) of the mRNA precursor (pre-mRNA) in host cells. Methods Based on the cell model of human lung epithelial cells A549, over-expression of the SARS-CoV-2 membrane protein was performed. The RNA-Seq high-throughput sequencing technique and bioinformatics methods was employed to analyze the systematic characterization of alternative polyadenylation (APA) events in host cells. Genes with significant APA events were uploaded to the Metascape database for functional enrichment analysis. In addition, alternative 3'UTR length of genes with APA events was verified by RT-qPCR. Then the target protein expression level was detected by Western blot. Results A total of 813 genes that were significant dynamic APA events in host cells that over-expressed SARS-CoV-2 membrane protein. These genes were enriched in cell biologicial processes such as the mitotic cell cycle and regulation of cellular response to stress. We further screened AKT1, which encodes a critical regulator involved in the above biological process, showing a 3'UTR lengthening in IGV software. RT-qPCR verified the trend of 3'UTR length changes of AKT1. Western blot showed the increased level of phosphorylated AKT1 protein in over-expressed group of M protein. Conclusion SARS-CoV-2 membrane protein potentially affects the 3' processing of host pre-mRNAs. AKT1, which is involved in a variety of viral biological processes, with 3'UTR lengthening, and its protein function was activated intracellularly. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

Determining the Factors that Affect Resistance to Digital News Subscription During the COVID-19 Pandemic

The subscription of digital services has increased due to the COVID-19 pandemic. However, this was not the same for digital news subscription which remained low. Therefore, this study looks to study the factors that influence the resistance to digital news subscription during the COVID-19 pandemic. In order to achieve this, the Innovation Resistance Theory was applied. Data was collected through an online survey that yielded 199 responses. Based on the results of the data analysis, two out of the five barriers were revealed to have insignificant relationships with resistance. With that said, value barrier, risk barrier, and image barrier were established as significant facilitators of resistance. Several insights were then proposed to news media companies. Moreover, this study fills the theoretical gap of comprehending the antecedents of resistance on digital news during the COVID-19 pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A microchamber-free and enzyme-free digital assay based on ultrabright fluorescent microspheres

Digital analysis is an effective single-molecule detection method and has attracted extensive attention in the field of bioassays. However, most digital assays require microchambers for signal compartmentalization. Herein, we developed a microchamber-free and enzyme-free digital assay by labeling paramagnetic beads directly with ultrabright fluorescent microspheres. In this assay, a DNA sandwich analysis was firstly performed on the bead to label a fluorescent microsphere. Then, the beads were loaded on the glass slide to form a monolayer film for signal readout. The whole analysis process does not require the participation of enzymes and the preparation of microchambers, which greatly simplifies the experimental steps and saves the costs. Furthermore, by introducing non-enzymatic hybridization chain reaction (HCR) and biotinylated DNA-conjugated gold nanoparticles (Au NPs-Bio), the capture efficiency and analytical sensitivity were improved. As a proof of concept, single-stranded DNA (ssDNA) of SARS-CoV-2 fragment was chosen as a model, and a detection limit of 1.5 fM was achieved. Spiked and recovery experiments on human serum and saliva samples validated the good performance of the proposed digital assay in real biological samples. The proposed assay provides a facile way of signal generation and readout for digital analysis. © 2023 Elsevier B.V.

A Scenario-Based Study of Doctors and Patients on Video Conferencing Appointments from Home

Telemedicine systems that involve the use of video conferencing technologies have been available for more than three decades. Yet, they have primarily been used for specialist appointments or within health care facilities. We are now seeing a shift with the proliferation of commercial technologies, such as smartphone apps that allow people to have appointments with a general practitioner from nearly any location for various reasons. Telemedicine has also seen an uptake due to the COVID-19 pandemic. However, little is known about how doctors and patients perceive smartphone-based telemedicine systems, what types of medical ailments are best suited for these systems, what sociotechnical challenges might emerge through their usage, and how systems should be designed to best meet the needs of both doctors and patients. Thus, we applied a scenario-based design method by presenting a set of medical situations to both general practitioners and patients, and conducted contextual interviews with them to investigate their thoughts on video-based appointments for a range of medical situations. Results show that video consultations using smartphone apps could raise challenges in delivering appropriate care and utilization, conducting camera work to assist different types of examinations, supporting doctor-patient relationship creation and maintenance, allowing doctors to maintain control over the appointment, as well as protecting patients' and doctors' privacy. This suggests the need to create designs that can support particular workflows, relationship building, safety and privacy protection, and camera work for varying contexts. © 2022 Association for Computing Machinery.

An Improved EfficientNet Model and its Applications in Pneumonia Image Classification

Since the outburst of COVID-19, the medical system has been facing great challenges due to the explosive growth in detection and treatment needs within a short period. To improve the working efficiency of doctors, an improved EfficientNet model of Convolutional Neural Network (CNN) was proposed and applied for the diagnosis of pneumonia cases and the classification of relevant images in the present study. First, the acquired images of pneumonia cases were divided to determine the zones with target features, and image size was limited to improve the training speed of the network. Meanwhile, reinforcement learning was performed to the input dataset to further improve the training effect of the model. Second, the preprocessed images were inputted into the improved EfficientNet-B4 model. The depth and width of the model, as well as the resolution of the input images, were determined by optimizing the combination coefficient. On this basis, the model was scaled, and then its ability in extracting the features of deep-layer images was strengthened by introducing the attention mechanism. Third, the learning rate was adjusted by using the Adaptive Momentum (ADAM), and the training efficiency of the model was accelerated. Finally, the test set was inputted into the trained model. Results demonstrate that the improved model could detect 98% of patients with pneumonia and 97% of patients without pneumonia. The accuracy rate, precision rate, and sensitivity of the model were generally improved. Lastly, the training and test results of VGGNet, SqueezeNet-Elus, SqueezeNet-Relu, and the improved EfficientNet-B4 models were compared and evaluated. The improved EfficientNet-B4 model achieved the highest comprehensive accuracy rate, reaching 92.95%. The proposed method provides some references to the application of the CNN model in image classification and recognition. © 2022 School of Science, IHU. All Rights Reserved.

Effects of SARS-CoV-2 Membrane Glycoprotein on Host Pre-mRNA 3 ' Processing

Objective To investigate the effect of SARS-CoV-2 membrane protein on the processing of the 3' untranslated region (UTR) of the mRNA precursor (pre-mRNA) in host cells. Methods Based on the cell model of human lung epithelial cells A549, over-expression of the SARS-CoV-2 membrane protein was performed. The RNA-Seq high-throughput sequencing technique and bioinformatics methods was employed to analyze the systematic characterization of alternative polyadenylation (APA) events in host cells. Genes with significant APA events were uploaded to the Metascape database for functional enrichment analysis. In addition, alternative 3'UTR length of genes with APA events was verified by RT-qPCR. Then the target protein expression level was detected by Western blot. Results A total of 813 genes that were significant dynamic APA events in host cells that overexpressed SARS-CoV-2 membrane protein. These genes were enriched in cell biologicial processes such as the mitotic cell cycle and regulation of cellular response to stress. We further screened AKT1, which encodes a critical regulator involved in the above biological process, showing a 3'UTR lengthening in IGV software. RT-qPCR verified the trend of 3'UTR length changes of AKT1. Western blot showed the increased level of phosphorylated AKT1 protein in over-expressed group of M protein. Conclusion SARS-CoV-2 membrane protein potentially affects the 3' processing of host pre-mRNAs. AKT1, which is involved in a variety of viral biological processes, with 3'UTR lengthening, and its protein function was activated intracellularly.

Prediction model of COVID-19 based on spatiotemporal attention mechanism

The continuous spread of the COVID-19 has brought profound impacts on human society. For the prevention and control of virus spreading, it is critical to predict the future trend of epidemic situation. Existing studies on COVID-19 spread prediction, based on classic SEIR models or naive time-series prediction models, are rarely considering the characteristics of complex regional correlation and strong time series dependence in the process of epidemic spread, which limits the performance of epidemic prediction. To this end, we propose a COVID-19 prediction model based on auto-encoder and spatiotemporal attention mechanism. The proposed model estimates the trend of COVID-19 by capturing the dynamic spatiotemporal dependence between the epidemic situation sequences of different regions. In particular, a spatial attention mechanism is implemented in the encoder section for every given region to capture the dynamic correlation between the epidemic situation time-series of the region and those of the related regions. Based on the leant correlation, an long short-term memory (LSTM) network is then applied to extract the epidemic sequential features for the given region by combining the recent epidemic situations of the region and the related regions. On the other hand, to better predict the dynamic of the future epidemic situation, temporal attention is introduced into an LSTM network-based decoder to capture the temporal dependence of the epidemic situation sequence. We evaluate the proposed model on several open datasets of COVID-19, and experimental results show that the proposed model outperforms the state-of-the-art models. The metrics of RMSE and MAE of the proposed model on the COVID-19 epidemic dataset of some European countries decreased 22. 3% and 25. 0%. The metrics of RMSE and MAE of the proposed model on the COVID-19 epidemic dataset of some Chinese provinces decreased 10. 1% and 10. 4%. © 2022 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

An Impending Thyroid Storm Caused by COVID-19 Infection

Background: Thyroid storm is an acute, potentially fatal complication of hyperthyroidism, usually manifested with tachycardia, hyperthermia, and altered mental status. Despite medical advancements, the mortality associated with thyroid storms remained 5% to 25%. Previously, cases of thyroiditis following COVID-19 infection have been reported. But the manifestation of COVID-19 infection as a thyroid storm is infrequent, and less than 5 cases have been reported to date. Case: A 72-year-old female with a remote history of breast cancer status post-mastectomy presented to the emergency department with the chief complaint of shortness of breath. She was found to have a history of fever eight days before the presentation;she was also complaining of non-productive cough, non-bloody, and non- bilious vomiting, myalgia, and fatigue. Home Covid Test was positive. On the day of the presentation, she received Regeneron infusion (casirivimab and imdevimab) and was discharged home. After a few hours, she represented to the hospital with chills and worsening of shortness of breath. She was found to be hypoxic on the presentation, was started on O2 supply, and transferred to the ICU. She received IV dexamethasone 6 mg and IV Remdesivir 200 mg on the first day, followed by 100mg for the next four days. On the fourth day following admission, she developed Atrial Fibrillation with a rapid ventricular response. The patient was somnolent and had loose bowel movements. Thyroid function tests were ordered;TSH was 0.02 and free T4 of 2.9. She stated she was never diagnosed with a thyroid disorder in the past. Thyroid function tests were ordered, which are mentioned in the table below. A thyroid-stimulating antibody assay was ordered to rule out Graves thyrotoxicosis, which turned out to be normal. Ultrasound of the thyroid gland didn't reveal any abnormalities. Conclusion: Although most patients remain euthyroid during COVID-19 infection, some may have shown transient thyroid derangements during the illness, which later turns out to be normal. Our case shows that a clinician should not take the thyroid derangements in COVID-19 lightly, as they can be the early signs of an impending thyroid storm. Our case guides the clinician to evaluate the thyroid function as soon as possible in any signs of overt hyperthyroidism. Due to the high mortality associated with thyroid storm, a clinician should have a high index of suspicion to diagnose the storm, such as in our case where other signs of hyperthyroidism are absent. Early treatment of thyroid storms becomes necessary to mitigate the mortality in such cases.Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.

FPDP: Flexible Privacy-Preserving Data Publishing Scheme for Smart Agriculture

The development of the Internet of Things (IoT) and 5th generation wireless network (5G) is set to push the smart agriculture to the next level since the massive and real-time data can be collected to monitor the status of crops and livestock, logistics management, and other important information. Recently, COVID-19 has attracted more human attention to food safety, which also has a positive impact on smart agriculture market share. However, the security and privacy concern for smart agriculture has become more prominent. Since smart agriculture implies working with large sets of data, which usually sensitive, some are even confidential, and once leakage it can expose user privacy. Meanwhile, considering the data publishing of smart agriculture helps the public or investors to real-timely anticipate risks and benefits, these data are also a public resource. To balance the data publishing and data privacy, in this article, a privacy-preserving data aggregation scheme with a flexibility property uses ElGamal Cryptosystem is proposed. It is proved to be secure, private, and flexible with the analysis and performance simulation.

Complete genome sequencing and traceability analysis of SARS-CoV-2 in Binhai New Area, Tianjin

Objective: To analyze the whole genome traceability and variation analysis of SARS-CoV-2 in local COVID-19 outbreaks in Binhai New Area, Tianjin. Methods: The whole-genome high-throughput sequencing was performed on throat swab samples collected from one local asymptomatic infected person and five confirmed cases of COVID-19 in Binhai New Area of Tianjin from November 7 to December 5, 2020. The sequencing data were assembled by De novo. MAFFT v7.0 multiple sequence alignment program and MEGA X software were used to compare the above data and construct phylogenetic tree (Neighbor-joining method). Results: The genetic similarity between the sequences of 6 SARS-CoV-2 strains and Wuhan reference sequence (Wuhan-Hu-1) was greater than 99.9%. Two of six strains were genetically identical, conform to the L-Lineage European Branch Ⅱ.1(America Branch)/B.1;The other four strains had the same genes and were in line with the characteristics of L-Lineage European Branch Ⅰ/B.1.1.These six strains belonged to different evolutionary branches and two different transmission chains. There were 18 nucleotide mutation sites in sequences of six SARS-CoV-2 strains, eight of which were synonymous mutation sites, nine of which were missense mutation sites, resulting in nine amino acid mutation sites, and important mutation sites of RDRP-P323L and S-D614G were found in all of the six samples. Conclusions: In this study, there were two COVID-19 outbreaks in Binhai New Area of Tianjin, and the sequences of six SARS-CoV-2 strains belonged to different evolutionary branches and two different transmission chains. It might come from porters' contact with imported cold chain items contaminated with SARS-CoV-2 from different sources. All the sequences of six SARS-CoV-2 strains had P323L and D614G mutations, which indicated that the virus mutation and transmission ability were stronger. The surveillance of important employees of the cold chain in Tianjin and local and imported cases should be continuously strengthened. Copyright © 2021 by the Chinese Medical Association.

Respiratory disease, and treatment / thematic poster session pneumothorax as a sars-cov-2 outcome in previously healthy lungs: A single-center case-control retrospective study

Introduction: SARS-CoV-2 infection ranges from self-limiting viral illness to acute respiratory distress syndrome. Diffuse alveolar injury from SARS-CoV-2 increases risk of alveolar rupture. Pneumothorax is a rare complication that has been documented in the literature. Objective: The study aims to investigate the significance of pneumothorax as a complication in patients with previously healthy lungs with acute respiratory failure due to SARS-CoV-2 infection. Methods: This is a case-control study of adult patients without existing lung disease managed for acute respiratory failure who developed pneumothorax as a complication of the disease. Patients with iatrogenic or traumatic pneumothorax, history of chronic lung disease, or previous pneumothorax were excluded. To avoid sample bias from excluding possible false-negatives, the control group (documented SARSCoV- 2 negative) also included patients from the same time period without SARS-CoV-2 testing and a remote unexposed group from a year before. Chi-square analysis was used to determine the relationship between the development of pneumothorax and SARS-CoV-2 infection, with the null hypothesis being no difference in the frequency of pneumothorax among positive SARS-CoV-2 patients and negative SARS-CoV-2 patients. Results: One-hundred-and-thirty charts of patients with symptoms of SAR-CoV-2 were reviewed. Thirty-four patients were documented to be SARS-CoV-2 positive, twelve of which had pneumothorax as a complication of the disease, ninety-one percent of whom were mechanically-ventilated. The control group had ninety-six patients with documented SARS-CoV-2 negative tests, were untested, or part of the historical group. Six patients from the control group had pneumothorax as a complication, two of which were negative for SARS-CoV-2, and three were untested. A Chi-square analysis yielded an X2 statistic of 17.7549 with a p-value of 0.000025.Discussion: Pvalue rejects the null hypothesis in 0.1, 0.05, and 0.01 levels of significance which means that there is a statistically significant difference in the frequency of pneumothorax between the case and control groups. Calculations were done under the assumption that those with negative SARS-CoV-2 tests were indeed free of the virus. There is a probability of underestimation as the tests used may have not been 100-percent sensitive. The four cases of pneumothorax in the control group may have been false-negatives as these patients exhibited imaging findings suggestive of SARS-CoV-2 pneumonia and were likely infected with the virus as well.Conclusion: Pneumothorax is a significant complication in patients without existing lung disease who develop acute respiratory failure and SARS-CoV-2 infection. It should be anticipated and suspected when clinical deterioration occurs especially in mechanically-ventilated patients. .

Examining the effectiveness of telehealth delivery modality on caregiving self-competency

Background: Prior to the COVID-19 pandemic, we demonstrated that in-person caregiver training (I-CareD bootcamp) improved knowledge, increased self-efficacy and achieved high satisfaction in dementia caregivers. Given restrictions imposed by the pandemic, we adapted and implemented a virtual delivery model of the I-CareD bootcamp. We targeted Spanish-speaking caregivers given the known difficulty in accessing caregiver training in this underserved population. Methods: We invited Spanish-speaking caregivers of persons with dementia to attend in-person or virtual caregiver training through partnerships with community-based organizations in Los Angeles County. For both in-person and virtual (Zoom) formats, we compared caregivers' self-reported levels of caregiving competence before and after attendance bootcamps to explore differences in outcomes between the two delivery modalities. Results: Sixty Spanish-speaking dementia caregivers attended a total of four dementia caregiver bootcamps. The majority of attendees are female (87%), middle-aged (50%), and were family caregivers (45%). 31caregivers attended the in-person bootcamps, and 29 attended virtually. We administered the Caregiving Competence Scale (CCS;Skaff, 1992), measuring self-perceived adequacy of a caregiver's performance to attendees of all bootcamps. The CCS consists of four items on a 4-point Likert-type scale ranging from 'very much' to 'not at all.' 54 caregivers completed the caregiving competence scale (range: 0-16) pre-and post-training sessions. Pre-bootcamp self-competence levels showed no significant difference between in-person (M = 11.92, SD = 3.16) and virtual (M =13.000, SD = 2.94) modalities (t(52) = -1.46, p >.05). Post-bootcamp group comparison also showed no significant differences (in-person: M=13.06, SD=2.19;virtual: M=14.31, SD=1.46;t(45) = -1.30, p >.05) between the two delivery modalities. Conclusions: Spanish-speaking caregivers' self-reported self-competency pre-and post-training revealed comparable improvements in both in-person and virtual delivery modalities. Our preliminary results suggest the potential efficacy of virtual caregiver training delivery modality for caregivers in the era of COVID-19.

Shifting from in-person to virtual programming to provide intergenerational social support for patients with dementia: The virtual TimeOut@ucla program

Background: TimeOut@UCLA is an intergenerational program that recruits and mobilizes college student volunteers to provide weekly one-on-one social interaction sessions with older adults with Alzheimer's disease and related dementias (ADRD). We previously demonstrated that our in-person program alleviates loneliness among seniors, offers caregivers respite, and strengthens student interest and knowledge in aging. In response to the COVID-19 pandemic, we modified the delivery of our program to an innovative virtual format. The aim of this preliminary study was to evaluate the success of this transition. Methods: Following focused training on aging and dementia, college students volunteered 1-2 times week for 10 week sessions. Each student was paired with a cognitively-impaired older adult based on shared interests and/or cultural/language backgrounds. Using Zoom as the virtual platform, students led seniors through online activities and engaged in conversation over about 60 minutes each session. The program was evaluated through virtual session auditing, qualitative outcome data in the form of student and caregiver interviews, and quantitative data in the form of student and caregiver surveys. Results: Between March and December 2020, 41 students and 38 seniors participated in the program. Preliminary caregiver surveys indicated improved mood, focus, and quality of life for 100% of participants with dementia (N=10). Moreover, 100% of caretakers reported the most important benefit to be observing their loved ones enjoying conversation and the opportunity to relax and gain relief from the monotonous routine. The students (N=17) experienced a significant (P < 0.001) increase (31 points on a 170-point scale) on the Dementia Attitude Scale. More data will be presented from ongoing data collection. Conclusion: Innovative interventions may address the unintended consequences of the Covid-19 mitigation measures. Virtual TimeOut@UCLA provides an innovative way to alleviate loneliness in older adults with ADRD through intergenerational interactions. Additionally, it provides a rewarding way for young adults to develop interest, knowledge, and skills to interact with cognitively-impaired older adults.

Therapeutic Drug Monitoring and Individualized Medication of Ribavirin

Ribavirin is a widely used nucleoside antiviral drug. During the epidemic of coronavirus disease 2019 (COVID-19), ribavirin was recommended for empirical treatment in the Clinical Management of Human Infection with COVID-19 (trial guidance v6). However, due to the large inter-individual variations in dose-response relationship, and extremely long terminal half time, it is necessary to perform therapeutic drug monitoring and individualized dose adjustment for ribavirin in special populations. In this article, the pharmacokinetics and therapeutic drug monitoring of ribavirin in different populations are reviewed in order to provide reference for clinical rational use and individualized medication of ribavirin for treatment of COVID-19. Copyright 2020 by the Chinese Pharmaceutical Association.