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Since the breakout of Corona Virus Disease 2019 (COVID-19), the global fight against influenza has begun. Various technologies have been developed to support the fast-growing contactless service market, and hence contactless services are rapidly becoming a new growth strategy. In particular, the retail service industry most urgently needs contactless service technology. A representative technical case is the self-checkout machine, which can reduce labor costs and provide customer satisfaction. We present a solution in this article. We propose a hand gesture recognition contactless self-checkout system, which is a hand gesture recognition model based on YOLOv5s. The hand gesture recognition mAP (0.5) value reaches 0.995, the mAP (0.5:0.95) value reaches 0.865, and the F1 score is 0.96, together with the accuracy and recall rate is close to 1. Compared with the excellent algorithm YOLOx-s, the FPS value of YOLOv5s can reach 123 (YOLOx-s is 108). In addition, the model can be used to detect recorded static and dynamic hand gestures in real-time. Practical results show that the YOLOv5s can effectively recognize hand gestures and realize the contactless checkout process.
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Objective: To investigate the blood glucose control of diabetic patients during the Coronavirus disease 2019 (COVID-19) epidemic, and to explore the factors affecting blood glucose. Method(s): Three hundred and fifty patients with diabetes mellitus hospitalized in the Endocrinology Department of the Second Affiliated Hospital of Air Force Military Medical University from 2017 to 2019 were selected, and we send questionnaires (a self-made questionnaire containing 39 questions, Zung anxiety self-assessment scale, Zung depression self-assessment scale) to the patients through WeChat group. After the effective questionnaires were collected, the patients were divided into good blood glucose control group (fasting blood glucose <=7 mmol/L and 2 h postprandial blood glucose <=10 mmol/L) and poor blood glucose control group (fasting blood glucose>7 mmol/L and/or 2 hours postprandial blood glucose>10 mmol/L). Chi square test or Fisher exact probability method and t test were used to compare the differences between the two groups. In Multi-factor logistic regression, the backward regression method was performed. Result(s): A total of 310 questionnaires were collected, 4 of which did not meet the requirements were eliminated, and a total of 306 valid questionnaires were analyzed. There were 108 cases (35.3%) in the well-controlled group and 198 cases (64.7%) in the poorly controlled group. Compared with well-controlled group, there was a higher percentage of patients with aged >=45 years, diabetes course >=5 years, combined with chronic complications of diabetes, weekly exercise time during the epidemic period<150 min,weekly monitoring of blood glucose frequency <=1 to 2 times and sleep disorders during the epidemic, anxiety, and depression in poorly controlled group, and there were statistically significant differences (P<0.05).The above 8 factors with P<0.05 were included in the logistic regression model. Diabetes course >=5 years, weekly exercise time during the epidemic<150 min, sleep disturbance during the epidemic, weekly monitoring of blood glucose frequency <= 1 to 2 times, depression were risk factors for poor blood glucose control (P<0.05). Conclusion(s): During the epidemic period, the blood glucose level of diabetes patients was generally high. The factors that affected blood glucose control included a long course of diabetes, short exercise time, low monitoring frequency of blood glucose, sleep disorders, and depression.Copyright © 2020 by the Chinese Medical Association.
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Volatility forecasting, a central issue in financial risk modelling and management, has attracted increasing attention after several major financial market crises. In this article, we draw upon the literature on volatility forecasting and hybrid models to construct the Hybrid-long short-term memory (LSTM) models to forecast the intraday realized volatility in three major US stock indexes. We construct the hybrid models by combining one or multiple traditional time series models with the LSTM model, and incorporating either the estimated parameters, or the predicted volatility, or both from the statistical models as additional input values into the LSTM model. We perform the out-of-sample test of our Hybrid-LSTM models in volatility forecasting during the coronavirus disease 2019 (COVID-19) period. Empirical results show that the Hybrid-LSTM models can still significantly improve the volatility forecasting performance of the LSTM model during the COVID-19 period. By analysing how the construction methods may influence the forecasting performance of the Hybrid-LSTM models, we provide some suggestions on their design. Finally, we identify the optimal Hybrid-LSTM model for each stock index and compare its performance with the LSTM model on each day during our sample period. We find that the Hybrid-LSTM models' great capability of capturing market dynamics explains their good performance in forecasting. © 2023 John Wiley & Sons Ltd.
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Objective: To investigate the blood glucose control of diabetic patients during the Coronavirus disease 2019 (COVID-19) epidemic, and to explore the factors affecting blood glucose. Method(s): Three hundred and fifty patients with diabetes mellitus hospitalized in the Endocrinology Department of the Second Affiliated Hospital of Air Force Military Medical University from 2017 to 2019 were selected, and we send questionnaires (a self-made questionnaire containing 39 questions, Zung anxiety self-assessment scale, Zung depression self-assessment scale) to the patients through WeChat group. After the effective questionnaires were collected, the patients were divided into good blood glucose control group (fasting blood glucose <=7 mmol/L and 2 h postprandial blood glucose <=10 mmol/L) and poor blood glucose control group (fasting blood glucose>7 mmol/L and/or 2 hours postprandial blood glucose>10 mmol/L). Chi square test or Fisher exact probability method and t test were used to compare the differences between the two groups. In Multi-factor logistic regression, the backward regression method was performed. Result(s): A total of 310 questionnaires were collected, 4 of which did not meet the requirements were eliminated, and a total of 306 valid questionnaires were analyzed. There were 108 cases (35.3%) in the well-controlled group and 198 cases (64.7%) in the poorly controlled group. Compared with well-controlled group, there was a higher percentage of patients with aged >=45 years, diabetes course >=5 years, combined with chronic complications of diabetes, weekly exercise time during the epidemic period<150 min,weekly monitoring of blood glucose frequency <=1 to 2 times and sleep disorders during the epidemic, anxiety, and depression in poorly controlled group, and there were statistically significant differences (P<0.05).The above 8 factors with P<0.05 were included in the logistic regression model. Diabetes course >=5 years, weekly exercise time during the epidemic<150 min, sleep disturbance during the epidemic, weekly monitoring of blood glucose frequency <= 1 to 2 times, depression were risk factors for poor blood glucose control (P<0.05). Conclusion(s): During the epidemic period, the blood glucose level of diabetes patients was generally high. The factors that affected blood glucose control included a long course of diabetes, short exercise time, low monitoring frequency of blood glucose, sleep disorders, and depression.Copyright © 2020 by the Chinese Medical Association.
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Corporate managers are the central figures of corporate activity who can control the strategic direction of companies. The company's use of financial derivatives can avoid risks and has an important impact on the value of the company. This study examines A-share listed firms in Shanghai over the period 2011–2020, uses an OLS panel and a moderating effects model, and investigates the impact of financial derivatives on firm value from the perspective of managers' characteristics. We find that financial derivatives can significantly increase the enterprise value of Chinese listed companies, while exchange rate derivatives have a stronger impact on enterprise value. We also find that the higher the proportion of managers who hold shares and have a financial background, the better the effect of firms using financial derivatives. These research results are of great significance to the application of financial derivatives and provide companies with risk management decisions after COVID-19. © 2022 by the authors.
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With the spread of COVID-19 around the world, the education industry faces enormous challenges. Some colleges and universities have launched online teaching. Comprehensive online teaching and student health checkups help students complete the set teaching content and return to school as soon as possible. With the development of big data, combined with the epidemic risk we are facing, the rational use of big data and the internet for innovative online education has become a mainstream teaching method. Colleges and universities are not yet familiar with the development prospects and future of online education. Through the research of this paper, we can understand the combination of online education and the development of big data and promote its application in colleges and universities. Not only have innovative online education platforms such as MOOC and DingTalk been widely used, but innovative online education methods such as virtual classrooms also have been created. Based on the current epidemic background, this paper analyzes the development of online education, introduces the impact of the combination of online education and big data, and introduces innovative online education technologies and their effects. It helps online education under the influence of the new coronavirus epidemic, operating big data technology to analyze the current prospects and development of online education, showing the combination of big data technology and online education through the analysis of big data technology, and ending with more expectations on other aspects of the use of big data, which affects the online education industry as well as other industries. Finally, we summarize the combination of big data and innovative online education since the emergence of COVID-19 and introduce the concepts and methods of combining online education and big data technology in detail. The online education platform also makes a reasonable introduction. The thesis can be used to understand the problems and challenges faced by innovative online education in the context of the new coronavirus epidemic and look forward to the future on this basis. © 2022 The Authors
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Networked social influence and strategic information manipulation are two social mechanisms fueling misinformation spread in online communities. However, it is unclear how these two mechanisms differ in their impacts. We conducted social network analyses on two online communities sharing misinformation concerning refugees in 2016 and COVID-19 in 2020. The results robustly showed that online misinformation spread is transitive and positively associated with members' embedded authority (i.e., the extent to which members' information is exclusively shared within the focal community). At the same time, strategic misinformation sharing by members of high community loyalty (i.e., targeted information sharing within the community) is less likely to gain momentum. The impact of bots on misinformation is contingent. Findings suggest that networked social influence is a more powerful driver of misinformation spread than strategic information manipulation. © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.
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Purpose The disruption of routine treatment, including the interruption of medication, might be deteriorating chronic conditions during disasters such as the COVID-19 epidemic. This study aims to assess the effectiveness of patient-centered measures for patients with chronic diseases during the COVID-19 epidemic. Method This was a cross-sectional study to analyze the effectiveness of chronic disease prescriptions issued by hospital-based clinicians, prescription refilling rate, the utilization rate of reservation for picking-up medicine, and the rate of returning to the hospital for refilling prescriptions as scheduled at a tertiary care hospital in Taiwan by using chi-square test. The enrolled outpatients received managed care from January to June of 2019 and 2020. The SAS (v8.2) statistical software was used for analysis. Results The percentage of chronic disease prescriptions issued by physicians out of a total number of outpatient visits increased to 66.0% significantly, and the rate of patients who returned to the hospital to refill chronic disease prescriptions decreased to 52.4%. The utilization rate of reservation service for prescription refills increased significantly from 3.9% to 10.5%. There is a significant difference in age groups and specialties visited by patients who made prescription refill reservations. The top five specialties are cardiovascular medicine, metabolic diseases, and endocrinology, neurology, urology, orthopedics, and rehabilitation. The specialties with the highest increase in reservation rate are psychiatry, gastroenterology, gynecology and pediatrics, and rheumatology. Discussion Most of the chronic disease continuous prescription users are the elderly, but the elderly are at high risk of severe COVID-19. Adopted patient-centered measures for preparedness to go out with medication such as outdoor drug dispensing counters, walk or drive-through pharmacies and online reservations for prescription refilling were effective, which can help elderly with the stable chronic disease obtain medication on schedule and reduce the risk of coronavirus exposure. National Health Insurance Administration should add the prescription refilling records to health insurance cards for further evaluating medicine adherence when prescriptions are revised. © 2022, Gerontechnology. All Rights Reserved.
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INTRODUCTION: While there are endemic foci of Strongyloides in the southeastern United States, strongyloidiasis in the US is most commonly found in immigrants and military veterans who have lived in endemic regions. We report a case of reactivated disseminated strongyloidiasis in a critically ill COVID-19 patient. DESCRIPTION: A 46 year old undomiciled man with a medical history of hypertension was found down by a friend and brought to the hospital for evaluation of altered mental status. The patient immigrated from Mexico in 1991 and lived in Florida for several years working as a gardener. On presentation he complained of headaches, with tremors and tongue fasciculations noted on physical exam. He underwent treatment for alcohol withdrawal. His hospital course was complicated by COVID-19 pneumonia requiring intubation, and a subarachnoid hemorrhage that did not require acute neurosurgical intervention. Several days after completion of remdesivir and dexamethasone treatment for COVID-19, the patient's absolute eosinophil count increased from 20/ uL on admission to 340/uL with a peak at 1500/uL. The patient was found to have Strongyloides and ESBL Klebsiella in a bronchoalveolar lavage after a bedside bronchoscopy. Ivermectin 200ug/kg/day and meropenem 2g every 8 hours were started. The patient remained persistently comatose despite being off sedation and a relatively benign brain MRI that demonstrated resolving subarachnoid hemorrhages. Strongyloides were confirmed in the CSF nine days after initial discovery in the BAL. Albendazole 400mg BID was added to the regimen and meropenem was continued for possible culture negative bacterial meningitis in the setting of disseminated strongyloidiasis. HIV and HTLV-1 serology was negative. The patient remained in the ICU with poor neurological status and ongoing goals of care discussions with the family. DISCUSSION: Strongyloides hyperinfection is an uncommon complication with a high mortality rate, with meningeal involvement often described post-mortem. Prophylactic anti-parasitic agents can be considered for patients identified as high risk for chronic strongyloidiasis who are about to undergo corticosteroid treatments, including COVID-19 associated regimens.
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DM patients infected with COVID-19 are at risk for developing severe complications including DKA and/or HHS, with a more severe disease course and higher mortality compared to those without DM or hyperglycemia. As COVID-19 is evolving into an endemic risk for the population, it is important to determine patients at risk for COVID-19 complications and outcomes. The Riverside University Health System Medical Center (RUHS-MC)-DKA Outcomes Group (RUDOG) initiated a study to characterize patients admitted for fatal DKA and/or HHS before and during the pandemic.This was a retrospective cohort study reviewing medical records of non-pregnant adults age 18 or older admitted to the RUHS-MC for DKA and/or HHS from Mar 2020 to Feb 2021 ("pandemic") compared to the 3 preceding years ("pre-pandemic"). The descriptive statistics were used to determine the clinical characteristics of hospitalized adult patients with DKA and/or HHS. Information of patient characteristics was extracted from chart reviews. Categorical data were compared using Fisher's Exact Test. Numerical variables were assessed using Mann-Whitney Test.The mortality rate during the pandemic was 8.4% (30/335) versus 1.7% (5/285) in the pre-pandemic period. Most of the deaths (24/30) were COVID infected. On average, the cases of deaths during pandemic had DM for a longer duration. There was no difference regarding age, race, HgbA1c on admission, insulin use history, and rate of micro- or macrovascular complications comparing these periods. More patients had HTN (80%) and HF (23%) during pandemic compared to pre-pandemic (69.2% and 7.7%, respectively). Infection was the cause of death for 63% and 31% of patients admitted for DKA and/or HHS during the pandemic versus pre-pandemic.There is a clear global concern that COVID-19 will be an endemic infectious disease placing people with pre-existing conditions such as DM at increased risk for morbidities and death. Our study has clearly demonstrated that contracting COVID is a risk for increased incidence of DKA and/or HHS and mortality compared to pre-pandemic levels. In addition, we have shown that certain pre-existing comorbidities are associated with the mortality of DKA and/or HHS including HTN and HF with COVID infection. The duration of DM was longer among patients that died during pandemic, regardless of age, race, or HgbA1c on admission. This finding is intriguing as we did not see increased DKA and/or HHS based on the number of micro- or macrovascular complications suggesting duration alone may be a new risk determinant.Presentation: Saturday, June 11, 2022 1:00 p.m. - 3:00 p.m.
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Since the breakout of Corona Virus Disease 2019 (COVID-19), the global fight against influenza has begun. Var-ious technologies have been developed to support the fast-growing contactless service market, and hence contactless services are rapidly becoming a new growth strategy. In particular, the retail service industry most urgently needs contactless service technology. A representative technical case is the self-checkout machine, which can reduce labor costs and provide customer satisfaction. We present a solution in this article. We propose a hand gesture recognition contactless self-checkout system, which is a hand gesture recognition model based on YOLOv5s. The hand gesture recognition mAP (0.5) value reaches 0.995, the mAP (0.5:0.95) value reaches 0.865, and the Fl score is 0.96, together with the accuracy and recall rate is close to 1. Compared with the excellent algorithm YOLOx-s, the FPS value of YOLOv5s can reach 123 (YOLOx-s is 108). In addition, the model can be used to detect recorded static and dynamic hand gestures in real-time. Practical results show that the YOLOv5s can effectively recognize hand gestures and realize the contactless checkout process. © 2022 Technical Committee on Control Theory, Chinese Association of Automation.
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The five primary sites proposed for International Ocean Discovery Program (IODP) Expedition 395, which was postponed because of the COVID-19 pandemic, were cored during IODP Expedition 395C. The Expedition 395C operations, shipboard measurements, and sampling were adjusted to account for the absence of a sailing science party. The Expedition 395/395C objectives are (1) to investigate temporal variations in ocean crust generation at the Reykjanes Ridge and test hypotheses for the influence of Iceland mantle plume fluctuations on these processes, (2) to analyze sedimentation rates at the Björn and Gardar contourite drifts, as proxies for Cenozoic variations of North Atlantic deepwater circulation, and for uplift and subsidence of the Greenland-Scotland Ridge gateway related to plume activity, and (3) to analyze the alteration of oceanic crust and its interaction with seawater and sediments. During Expedition 395C, basalt cores were collected at four sites: U1554, U1555, U1562, and U1563. Sediment cores were also collected from these sites as well as from Site U1564, and casing was installed to 602 m at Site U1554. The amount of recovered cores, their preliminary descriptions, and the analyses of shipboard samples show that the results of Expedition 395C will fulfill a significant part of the Expedition 395 objectives. Basalts were collected from two V-shaped ridge and trough pairs, which will allow the investigation of the variability in mantle source and temperature causing this ridge/trough pattern. Basalt cores span an expected age range of 2.8–13.9 Ma, which will allow us to investigate the hydrothermal weathering processes. Sediments from the Björn drift were cored to basement, along with the uppermost 600 m of sediments from the Gardar drift. The data provided by Expedition 395C are a major advancement in achieving the work of Expedition 395. © 2022 Authors. All rights reserved.
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The COVID-19 pandemic has impacted a wide range of human activities, from food delivery habits to major moving and travel decisions. Results indicate multiple pandemic-related factors have influenced millions of relocation decisions by Americans (e.g., health risk, financial pressures, more space, and employment), and there are various positive economic and social outcomes of this influence (e.g., remote work and education), enabling more affordable living and opportunity. This paper addresses COVID-19 impacts on mobility, especially involving permanent relocations. Survey design and data analysis with U-Haul targeted customers in Austin, New York, San Diego, and Chicago to understand mobility, new moving dynamics, and motivations. © ASCE. All rights reserved.
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Background: Standard of care for HER2+ early/first-line metastatic BC (EBC/MBC) is P + H and concurrent chemotherapy (CT);PH FDC SC offers faster, more convenient admin vs intravenous (IV) P + H. COVID-19 has caused unprecedented strain on healthcare systems and disruption to cancer care;treatment (Tx) at home may: enable pts to continue cancer Tx;reduce exposure to COVID-19;free up hospital resources. This study's main objectives: to enable continuity of care during COVID-19;to assess safety of PH FDC SC given at home. Methods: This is an ongoing single-arm, hybrid, decentralized clinical trial (NCT04395508). Pts with HER2+ EBC/MBC who completed concurrent CT with P + H IV and are receiving/about to receive maintenance P + H IV, PH FDC SC, or H SC are switched to PH FDC SC given at home by a home health nursing provider (HHNP) until disease progression, unacceptable toxicity, pt withdrawal, or physician recommendation (pts with EBC will complete ≤18 cycles). The study endpoint is safety. A subset of pts took part in HARRIET, a substudy of at-home cardiac surveillance with artificial intelligence-guided cardiac ultrasound and optional 6L ECG acquired by an HHNP. Results: Data for 114 pts (1 male) were available at cutoff (Jan 19, 2022): 18 (16%) completed Tx;20 (18%) discontinued;76 (67%) remain on study;79 (69%) had a COVID-19 vaccine while on study. Median age was 49 years;pts were balanced between EBC (n = 55, 48%) and MBC (n = 59, 52%);received a median of 6 (EBC) and 8 (MBC) cycles;and were from metropolitan (n = 109), urban (n = 4), and rural (n = 1) areas. 11 pts tested COVID-19-positive during the Tx phase: 8 continued Tx after appropriate COVID-19 Tx and/or quarantine. Safety is summarized in the table. No new adverse events (AEs) emerged due to home admin. AEs of special interest were grade (gr) 1-2: admin-related reactions (n = 76, 67%), hypersensitivity (n = 5, 4%), cardiac dysfunction (n = 4, 4%), except 1 case of gr ≥3 diarrhea. AEs leading to study Tx discontinuation or interruption/dose reduction occurred in 3 (3%) and 15 (13%) pts. A subset of 7 pts completed at-home cardiac surveillance testing;quantitative assessment of left ventricular ejection fraction was feasible in 3 (43%);5 (71%) preferred at-home surveillance to clinic. Conclusions: In this preliminary analysis, safety of PH FDC SC at home was consistent with the established P + H safety profile, indicating that PH FDC SC at home is a viable option for continuing BC care during and beyond COVID-19.
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Background: Cardiotoxicity is frequently monitored when anti-HER2 treatment (Tx) is used and is a potential reason for discontinuation. As patients (pts) live longer, improved surveillance via low-interventional management is critical. Advances in digital tools and the impact of COVID-19 are accelerating opportunities for in-home care. We initiated cardiac monitoring at home in a subset of patients from study NCT04395508, which provides continuity of care during the pandemic and home administration of pertuzumab, trastuzumab and hyaluronidase-zzxf (PH FDC SC) for pts with HER2-positive breast cancer. Methods: Pts must be on/will receive maintenance intravenous pertuzumab + trastuzumab/PH FDC SC/subcutaneous trastuzumab post-chemotherapy completion. Up to 36 pts will be enrolled at Memorial Sloan Kettering Cancer Center and selected Mayo Clinic sites. Pts will undergo remote cardiac surveillance by a Home Health Nursing Provider via Caption Artificial Intelligence (AI)-guided ECHO and ECG (KardiaMobile 6L) after a reference in-clinic ECHO and 12-lead ECG. Images and tracing will be assessed centrally. Key objectives are to evaluate feasibility of LVEF assessment at home based on AI-guided cardiac ultrasound images acquired by novice users without prior ECHO experience and to evaluate feasibility, including recording frequency and signal quality, of an AI-guided ECG algorithm at home by the pt with nurse oversight. Results: Enrollment began Aug 2021. Conclusion: For healthcare systems, HARRIET can improve Tx monitoring to avoid premature discontinuation;is a step toward moving away from specialized sites to flexible healthcare delivery and lower cost of care;and can remove logistical, financial and workload barriers of scheduling in-person ECHO readings. For pts, it can optimize care and increase confidence in anti-HER2 Tx and can provide access to specialty care in the comfort of their own home.
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The COVID-19 pandemic has posed severe challenges that require collaborative efforts from multi-sector organizations. Guided by an institutional theory framework that considers how both organizational fields and national level contexts affect organizations' social partnership communication, the current study examines the COVID-19-related social partnership communication network on social media. The cross-national study using semantic network analysis and exponential random graph models (ERGMs) first maps the meaning of COVID-19 social partnership network, and then investigates the role of organizational fields and a country's political system, economic system, educational system, and cultural system on the formation of interorganizational communication ties surrounding the relief efforts of COVID-19. Results reveal the importance of the political system-such as the presence of populist government, economic disparity, and uncertainty avoidance cultural orientation in shaping the social media-based social partnership communication network. In addition, NGOs from multiple issue areas are actively engaged in the network, whereas corporations from manufacturing and financial industries are active players.
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Background Prior to the COVID-19 pandemic, about half of patients from populations that sought care in neurology tried complementary and integrative therapies (CITs). With the increased utilization of telehealth services, we sought to determine whether patients also increased their use of virtual CITs. Methods We examined datasets from two separate cross-sectional surveys that included cohorts of patients with neurological disorders. One was a dataset from a study that examined patient and provider experiences with teleneurology visits;the other was a study that assessed patients with a history of COVID-19 infection who presented for neurologic evaluation. We assessed and reported the use of virtual (and non-virtual) CITs using descriptive statistics, and determined whether there were clinical characteristics that predicted the use of CITs using logistic regression analyses. Findings Patients who postponed medical treatment for non-COVID-19-related problems during the pandemic were more likely to seek CITs. Virtual exercise, virtual psychotherapy, and relaxation/meditation smartphone applications were the most frequent types of virtual CITs chosen by patients. In both studies, age was a key demographic factor associated with mobile/virtual CIT usage. Interpretations Our investigation demonstrates that virtual CIT-related technologies were utilized in the treatment of neurologic conditions during the pandemic, particularly by those patients who deferred non-COVID-related care.
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Objective: Patients with diabetes mellitus (DM) infected with COVID are at risk for developing severe complications including diabetic ketoacidosis (DKA) and/or hyperosmolar hyperglycemic state (HHS)1. They may have a more severe disease course and higher mortality compared to those without DM or hyperglycemia2. The Riverside University Health System Medical Center (RUHS-MC)-DKA Outcomes Group (RUDOG) initiated a study to determine causes and outcomes before and during the pandemic in patients hospitalized for DKA and/or HHS. Methods: RUHS-MC is a safety net hospital serving patients in Riverside County, CA and 13.2% within Riverside County having DM4. This was a retrospective cohort study reviewing medical records of non-pregnant adults age 18 or older admitted to the RUHS-MC for DKA and/or HHS from Mar 2020 to Feb 2021 (“pandemic”) compared to the 3 years before the pandemic (“pre-pandemic”). The descriptive statistics were used to determine the clinical characteristics of hospitalized adult patients with DKA and/or HHS. Cause of death was extracted from chart reviews. Categorical data were compared using Fisher's Exact Test. Numerical variables were assessed using Mann-Whitney Test. Results: From Mar 2020 to Feb 2021, 289,450 residents in Riverside County had COVID infection and 3,767 died3. There was an annual average of 285±51 of DKA and/or HHS patients admitted pre-pandemic versus 355 patients during pandemic. The average deaths per year pre-pandemic was 5±2.6, which significantly increased to 30 deaths during pandemic. Most of the deaths (24/30) were COVID infected. On average, the cases of deaths during pandemic were noted to have DM for a longer duration, and had longer length of stay (LOS). Sixty-three percent and 31% of patients had DKA and/or HHS due to infection during the pandemic and pre-pandemic, respectively. Respiratory failure was the cause of death in 46.7% and 23.1% of the deaths in pandemic and pre-pandemic, respectively. Discussion/Conclusion: In RUHS-MC, the mortality rate of DKA and/or HHS was significantly higher during the pandemic compared to the prior 3 years. Most of the deaths during the pandemic time had COVID infection, developed DKA and/or HHS due to an active infection, and found to have respiratory failure as the cause of death suggesting COVID infection is the major driving force for death in patients admitted with DKA and/or HHS. Moreover, the duration of DM and LOS were longer among deaths during pandemic, which are consistent with prior studies that DM is a major risk for COVID infection and severe disease.
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This study draws on the social identity approach (SIA), to examine how political elites (i.e., members of the 116th United States Congress) communicated norms about mask-wearing on social media during the COVID-19 pandemic. Using Twitter data collected in 2020, we found that Republican members of Congress were significantly less likely to promote mask-wearing than Democratic members. We also observed some variations in norm-conforming behaviors among the members of each party. For Republicans, increased loyalty to the Trump leadership was significantly associated with a lower level of mask promotion. For Democrats, we found some evidence that loyalty to the party predicted higher levels of mask promotion. On the other hand, interactions with out-group members decreased adherence to party norms for both Republican and Democratic members of Congress. These findings allow us to better understand the social-psychological effects of party membership among political elites as well as the importance of leader-follower relationships and intergroup interactions.