Platelet-albumin-bilirubin score and neutrophil-to-lymphocyte ratio predict intensive care unit admission in patients with end-stage kidney disease infected with the Omicron variant of COVID-19: a single-center prospective cohort study.

OBJECTIVES: The objective of this study was to develop clinical scores to predict the risk of intensive care unit (ICU) admission in patients with COVID-19 and end stage kidney disease (ESKD). METHODS: This was a prospective study in which 100 patients with ESKD were enrolled and divided into two groups: the ICU group and the non-ICU group. We utilized univariate logistic regression and nonparametric statistics to analyze the clinical characteristics and liver function changes of both groups. By plotting receiver operating characteristic curves, we identified clinical scores that could predict the risk of ICU admission. RESULTS: Out of the 100 patients with Omicron infection, 12 patients were transferred to the ICU due to disease aggravation, with an average of 9.08 days from hospitalization to ICU transfer. Patients transferred to the ICU more commonly experienced shortness of breath, orthopnea, and gastrointestinal bleeding. The peak liver function and changes from baseline in the ICU group were significantly higher, with p values <.05. We found that the baseline platelet-albumin-bilirubin score (PALBI) and neutrophil-to-lymphocyte ratio (NLR) were good predictors of ICU admission risk, with area under curve values of 0.713 and 0.770, respectively. These scores were comparable to the classic Acute Physiology and Chronic Health Evaluation II (APACHE-II) score (p > .05). CONCLUSION: Patients with ESKD and Omicron infection who are transferred to the ICU are more likely to have abnormal liver function. The baseline PALBI and NLR scores can better predict the risk of clinical deterioration and early transfer to the ICU for treatment.

DiDang decoction improves mitochondrial function and lipid metabolism via the HIF-1 signaling pathway to treat atherosclerosis and hyperlipidemia.

ETHNOPHARMACOLOGICAL RELEVANCE: DiDang Decoction (DDD) is a traditional classical prescription that has been used to treat atherosclerosis (AS) and hyperlipidemia (HLP) in China. Nevertheless, the underlying mechanism of DDD remains unclear. AIM OF THE STUDY: To validate the mechanism of DDD in AS and HLP based on network pharmacology and in vitro experiments. MATERIALS AND METHODS: The chemical components of DDD were obtained from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) database and literature mining, and the disease targets of AS and HLP were obtained from the Gencards, OMIM, and DisGeNET databases. The intersection genes were imported into the STRING database to construct protein-protein interaction (PPI) network, and the DAVID database was used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Combined with the results of KEGG pathway analysis, the HIF-1 signaling pathway was selected for further in vitro experiments. RESULTS: The results showed that network pharmacology predicted 112 targets related to DDD treatment of AS and HLP, and the top 10 related pathways are: Lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Chemical carcinogenesis - receptor activation, Pathways in cancer, Proteoglycans in cancer, Fluid shear stress and atherosclerosis, HIF-1 signaling pathway, Alcoholic liver disease, PPAR signaling pathway, and Coronavirus disease-COVID-19. In vitro experiments showed that DDD effectively reduced lipid accumulation in FFA-treated L02 cells; DDD attenuated mitochondrial damage and reduced ROS content; DDD inhibited ferroptosis and apoptosis; DDD up-regulated the expression of HIF-1α, Glutathione Peroxidase 4(GPX4), and Bcl2 proteins, and down-regulated expression of Bax protein. CONCLUSION: DDD exerts therapeutic effects on AS and HLP through multiple targets and pathways, and improves mitochondrial function, reduces ROS content, inhibits ferroptosis and apoptosis by activating the HIF-1 signaling pathway, which provides reliable theoretical and experimental support for DDD treatment of AS and HLP.

Clinical characteristics and molecular epidemiology of human metapneumovirus in children with acute lower respiratory tract infections in China, 2017 to 2019: A multicentre prospective observational study.

Human metapneumovirus (HMPV) infection is one of the leading causes of hospitalization in young children with acute respiratory illness. In this study, we prospectively collected respiratory tract samples from children who were hospitalized with acute lower respiratory tract infection in six hospitals in China from 2017 to 2019. HMPV was detected in 145 out of 2733 samples (5.3%) from the hospitalized children. The majority of HMPV-positive children were under the age of two (67.6%), with a median age of one year. HMPV can independently cause acute lower respiratory tract infection in young children, while all patients showed mild clinical symptoms. Of all the co-infected patients, HMPV was most commonly detected with enterovirus (EV) or rhinovirus (RhV) (38.0%, followed by respiratory syncytial virus (RSV) (32.0%). The highest detection rate occurred from March to May in both northern and southern China. Out of 145 HMPV positive samples, 48 were successfully typed, of which 36 strains were subgrouped into subtypes A2c (75%), eight strains were included in subtype B1 (16.7%), and four strains were included in subtype B2 (8.3%). Moreover, 16 A2c strains contained 111-nucleotide duplications in the G gene. Twenty-seven complete HMPV genomes were successfully obtained, and 25 (92.6%) strains belonged to subtype A2c, whereas one strain was included in subgroup B1 and another was included in subgroup B2. A total of 277 mutations were observed in the complete genomes of 25 A2c strains. All results presented here improve our understanding of clinical characteristics and molecular epidemiology of HMPV infection in children.

Healthcare Workers' Attitudes toward Influenza Vaccination: A Behaviour and Social Drivers Survey.

This study aimed to understand the intention and correlation of receiving and recommending influenza vaccine (IV) among healthcare workers (HCWs) in China during the 2022/2023 season using the behavior and social drivers (BeSD) tools. A self-administered electronic survey collected 17,832 participants on a media platform. We investigated the willingness of IV and used multivariate logistic regression analysis to explore its associated factors. The average scores of the 3Cs' model were compared by multiple comparisons. We also explored the factors that potentially correlated with recommendation willingness by partial regression. The willingness of IV was 74.89% among HCWs, and 82.58% of the participants were likely to recommend it to others during this season. Thinking and feeling was the strongest domain independently associated with willingness. All domains in BeSD were significantly different between the hesitancy and acceptance groups. Central factors in the 3Cs model were significantly different among groups (p < 0.01). HCWs' willingness to IV recommendation was influenced by their ability to answer related questions (r = 0.187, p < 0.001) after controlling for their IV willingness and perceived risk. HCWs' attitudes towards IV affect their vaccination and recommendation. The BeSD framework revealed the drivers during the decision-making process. Further study should classify the causes in detail to refine HCWs' education.

A multicentre study on the incidence of respiratory viruses in children with community-acquired pneumonia requiring hospitalization in the setting of the zero-COVID policy in China.

BACKGROUND: Stringent nonpharmaceutical interventions (NPIs) have been implemented worldwide to combat the COVID-19 pandemic, and the circulation and seasonality of common respiratory viruses have subsequently changed. There have been few multicentre studies or comparisons of the prevalence of respiratory viruses accounting for community-acquired pneumonia (CAP) in hospitalized children between the pre-COVID period and the period after community and school reopening in the setting of the zero-COVID policy. METHODS: We included 1543 children with CAP who required hospitalization from November 1, 2020 to April 30, 2021 (period 1), and 629 children with the same conditions from November 1, 2018, to April 30, 2019 (period 2), in our study. All respiratory samples from these patients were screened for six respiratory viruses (respiratory syncytial virus [RSV], adenovirus [ADV], influenza A virus [Flu A], influenza B virus [Flu B], parainfluenza virus type 1 [PIV1], and parainfluenza virus type 3 [PIV3]) using a multiplex real-time PCR assay. RESULTS AND CONCLUSIONS: The median ages of the enrolled patients at the time of diagnosis were 1.5 years and 1.0 years for period 1 and period 2, respectively. In period 1, viral pathogens were detected in 50.3% (776/1543) of the enrolled patients. The most frequently identified viral pathogen was RSV (35.9%, 554/1543), followed by PIV3 (9.6%, 148/1543), PIV1 (3.6%, 56/1543), ADV (3.4%, 52/1543), Flu A (1.0%, 16/1543), and Flu B (0.8%, 13/1543). The total detection rates of these six viruses in the peak season of CAP were at the pre-COVID level. The prevalence of Flu A decreased dramatically, and circulation activity was low compared to pre-COVID levels, while the incidence of PIV3 increased significantly. There were no significant differences in the detection rates of RSV, ADV, Flu B, and PIV1 between the two periods. Our results showed that respiratory viruses accounted for CAP in hospitalized children at pre-COVID levels as communities and schools reopened within the zero-COVID policy, although the prevalence aetiology spectrum varied.

Severe Anemia Observed in a Chinese Patient with COVID-19 and Plasmodium Falciparum Malaria Co-Infection.

BACKGROUND: COVID-19 and malaria share some similar symptoms such as fever, difficulty in breathing, fatigue, and headaches of acute onset. With overlapping symptoms and travel history significant for COVID-19 and malaria, healthcare systems and professionals will face a great challenge in the case of COVID-19 and malaria co-infection. METHODS: Here we presented a patient with COVID-19 infection and refractory anemia of unknown reason. A diagnostic test for malaria was later performed. RESULTS: The patient was ultimately diagnosed with COVID-19 and plasmodium falciparum malaria co-infection. He recovered gradually after receiving anti-malaria treatment. CONCLUSIONS: The present case highlights the danger of focusing only on a diagnosis of COVID-19, reminding clinicians to be vigilant about the possibility of co-infections.

[Features of unintentional injury in children under the impact of coronavirus disease 2019]. / æ–°åž‹å† çŠ¶ç— æ¯’è‚ºç‚Žç–«æƒ ä¸‹å„¿ç«¥æ„å¤–ä¼¤å®³çš„ç‰¹å¾.

OBJECTIVES: To study the features of unintentional injury in children under the impact of coronavirus disease 2019 (COVID-19). METHODS: A retrospective analysis was performed on the medical data of 2 526 children with unintentional injury in Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from July 2019 to June 2022. The study period was divided into 5 stages: before the epidemic (July to December, 2019), the Wuhan epidemic period (January to April, 2020), the epidemic remission period in China (May 2020 to February 2022), the Shanghai epidemic period (March to May, 2022), and the epidemic remission period in Shanghai (June 2022). The incidences of unintentional injury in children at different time stages and different ages were compared. A questionnaire survey was conducted on 107 children of the 2 526 children to explore the features of unintentional injury. RESULTS: There were significant differences in gender composition, age, age distribution and proportion of many types of unintentional injuries among the five time stages (P<0.05). There was a reduction in the number of children who attended the emergency department due to unintentional injury during the Wuhan epidemic and the Shanghai epidemic. The proportion of children with trauma-related unintentional injuries in each stage reached more than 50%, and the proportion of children with trauma-related unintentional injuries reached 63.9% and 82.0%, respectively during the Wuhan epidemic and the Shanghai epidemic. Most children suffering from unintentional injury were mainly school-aged and preschool children (1 823 children, 72.17%). Compared with the same period of Shanghai epidemic in 2021, the age of children with unintentional injury was younger (median 7 years vs 11 years), and the proportion of children with trauma-related unintentional injuries increased (97% vs 69%) during the Shanghai epidemic (P<0.05). CONCLUSIONS: Under the COVID-19 epidemic, there is a reduction in the number of children with unintentional injury, while there is an increase in the proportion of children with trauma-related unintentional injuries. Unintentional injury is more common among school-aged and preschool children.

3’UTR of SARS-CoV-2 spike gene hijack host miR-296 or miR-520h to disturb cell proliferation and cytokine signaling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has becoming globally public health threat. Recently studies were focus on SARS-CoV-2 RNA to design vaccine and drugs. It was demonstrated that virus RNA could play as sponge to host noncoding RNAs to regulate cellular processes. Bioinformatic research predicted a series of motif on SARS-CoV-2 genome where are targets of human miRNAs. In this study, we used dual-luciferase reporter assays to validate the interaction between 3’UTR of SARS-CoV-2 S (S-3’UTR) gene and bioinformatic predicted targeting miRNAs. The growth of 293T cells and HUVECs with overexpressed S-3’UTR was determined, while miRNAs and IL6, TNF-α levels were checked in this condition. Then, miR-296 and miR-602 mimic were introduced into 293T cells and HUVECs with overexpressed S-3’UTR, respectively, to reveal the underlying regulation mechanism. In results, we screened 19 miRNAs targeting the S-3’UTR, including miR-296 and miR-602. In 293T cell, S-3’UTR could inhibit 293T cell growth through down-regulation of miR-296. By reducing miR-602, S-3’UTR could induce HUVECs cell proliferation, alter the cell cycle, reduce apoptosis, and enhanced IL6 and TNF-αlevel. In conclusion, SARS-CoV-2 RNA could play as sponge of host miRNA to disturb cell growth and cytokine signaling. It suggests an important clue for designing COVID-19 drug and vaccine.

Association Between Wages and Nursing Staff Turnover in Iowa Nursing Homes.

Background and Objectives: Nursing staff turnover is a substantial concern for nursing homes that care for millions of older individuals, especially during the coronavirus disease 2019 pandemic. Low pay is considered as one of the key reasons for high turnover. However, we do not know whether increasing wages can lead to lower turnover. In this study, we fill this gap in our understanding by analyzing the relationship between wages and nursing staff turnover. Research Design and Methods: We obtained data on hourly wages (Medicare Cost Reports), turnover (Iowa Department of Human Services), and nursing home and resident characteristics (Nursing Home Compare and LTCFocus) from 2013 to 2017. We summarized the characteristics of nursing homes as well as turnover trends over time. Next, we used pooled ordinary least squares (OLS) and facility fixed effects regressions to examine the relationship between wages and turnover adjusting for nursing home and resident characteristics. Results: Among the 396 nursing homes in Iowa, average hourly wage was $27.0 for registered nurses (RNs), $21.6 for licensed practical nurses (LPNs), and $14.1 for certified nurse aides (CNAs) during 2013-2017. Average turnover rates were increasing over time for all staff types and in 2017, turnover rates were 46.0% for RNs, 44.4% for LPNs, and 64.7% for CNAs. In both pooled OLS and facility fixed effects regressions, higher wages were associated with lower turnover of CNAs but not LPNs or RNs. The magnitude of the effect of wages on turnover for CNAs was lower in facility fixed effects regressions. Discussion and Implications: We found a significant relationship between hourly wages and turnover for CNAs but not for LPNs or RNs. Focusing on higher wages alone may not lead to lower turnover of all types of nursing staff in nursing homes. We should also focus on nonwage factors related to turnover.

The forecast of COVID-19 spread risk at the county level.

The early detection of the coronavirus disease 2019 (COVID-19) outbreak is important to save people's lives and restart the economy quickly and safely. People's social behavior, reflected in their mobility data, plays a major role in spreading the disease. Therefore, we used the daily mobility data aggregated at the county level beside COVID-19 statistics and demographic information for short-term forecasting of COVID-19 outbreaks in the United States. The daily data are fed to a deep learning model based on Long Short-Term Memory (LSTM) to predict the accumulated number of COVID-19 cases in the next two weeks. A significant average correlation was achieved (r=0.83 (p = 0.005)) between the model predicted and actual accumulated cases in the interval from August 1, 2020 until January 22, 2021. The model predictions had r > 0.7 for 87% of the counties across the United States. A lower correlation was reported for the counties with total cases of <1000 during the test interval. The average mean absolute error (MAE) was 605.4 and decreased with a decrease in the total number of cases during the testing interval. The model was able to capture the effect of government responses on COVID-19 cases. Also, it was able to capture the effect of age demographics on the COVID-19 spread. It showed that the average daily cases decreased with a decrease in the retiree percentage and increased with an increase in the young percentage. Lessons learned from this study not only can help with managing the COVID-19 pandemic but also can help with early and effective management of possible future pandemics. The code used for this study was made publicly available on https://github.com/Murtadha44/covid-19-spread-risk. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40537-021-00491-1.

Low molecular weight heparin reduces arterial blood lactic acid content and increases estimated glomerular filtration rate in patients with moderate Covid-19 pneumonia.

BACKGROUND: Coronavirus disease 2019 (Covid-19) remains a serious health threat worldwide. We aimed to investigate whether low molecular weight heparin (LMWH) can promote organ function recovery in moderate Covid-19 pneumonia patients. METHODS: We initiated an LMWH protocol in Covid-19 patients with increased D-dimer, body mass index >30 kg/m2 or a history of diabetes from January 18, 2020 at Shanghai Public Health Clinical Center. In this retrospective study, we assigned moderate Covid- 19 pneumonia patients admitted between January 18th and April 18, 2020 receiving the LMWH protocol to the LMWH group. Moderate patients who met the inclusion criteria but did not receive LMWH protocol were included in the control group by 1:2 propensity score matching. General clinical information, indicators for renal function, arterial blood gas analyses, arterial blood lactic acid content (mmol/L), and coagulation indexes at 0 day, 3 days, 7 days, and 11 days after admission were recorded and compared between the two groups. RESULTS: There were 41 patients in the LMWH group and 82 patients in the control group. General information in both groups were similar. Compared to the control group, the arterial blood lactic acid content (mmol/L) at day 11 (1.3 [1.1, 1.7] vs. 1.2 [0.9, 1.3], P = 0.016) was reduced in the LMWH group. The estimated glomerular filtration rate (eGFR) in the LMWH group was higher than that in the control group at day 7 (108.54 [89.11, 128.17] vs. 116.85 [103.39, 133.47], P = 0.039) and day 11 (113.74 [94.49, 126.34] vs. 128.31 [112.75, 144, 12], P  = 0.003). The serum creatinine levels (Scr) in the LMWH group were lower than that in the control group at day 7 (62.13 [51.47, 77.64] vs. 55.49 [49.50, 65.75], P = 0.038) and day 11 (63.35 [50.17, 75.73] vs. 51.62 [44.62, 61.24], P = 0.005). CONCLUSIONS: LMWH treatment can reduce arterial blood lactic acid levels and improve eGFR in moderate Covid-19 pneumonia patients. Randomized controlled trials are warranted to further investigate this issue. TRIAL REGISTRATION: ChiCTR.org.cn, ChiCTR2000034796.

Profit Status and Employee Turnover in Iowa Nursing Homes

Employee turnover is a huge concern for nursing homes that care for millions of older individuals whose physical and cognitive impairments make them vulnerable, especially in the middle of a pandemic like COVID-19. Existing research has shown that high turnover of employees can lead to poorer quality of care. Low pay is often cited as one of the key reasons for high turnover of employees in nursing homes. For-profit nursing homes may try to maximize profits by limiting wages paid to their employees. In this study, we examine whether profit-status of a facility is associated with high turnover of its employees. We obtain data on 415 nursing homes operating in Iowa between 2013-2017. We descriptively examine the turnover trends in nurse employees and all employees over time by profit status. We evaluate whether profit status is associated with high turnover using pooled linear regressions controlling for nursing home and resident characteristics. Descriptive results show that for-profit facilities had higher turnover of nurse employees (61.1% vs. 49.6%) and all employees (56.6% vs. 45.4%). Results from multivariate regressions show that, compared to non-profit facilities, for-profit facilities had 6.93 percentage points higher (p<0.01) turnover of all employees, and 7.76 percentage points higher (p<0.01) turnover of nurse employees after controlling for facility and resident characteristics. Given existing evidence on the adverse impact of high employee turnover on nursing home quality, we need policies aimed at lowering employee turnover, targeting for-profit nursing homes.

First Year of Skilled Nursing Facility Value-based Purchasing Program Penalizes Facilities With Poorer Financial Performance.

BACKGROUND: The Skilled Nursing Facility Value-based Purchasing Program (SNF-VBP) incentivizes facilities to coordinate care, improve quality, and lower hospital readmissions. However, SNF-VBP may unintentionally punish facilities with lower profit margins struggling to invest resources to lower readmissions. OBJECTIVE: The objective of this study was to estimate the SNF-VBP penalty amounts by skilled nursing facility (SNF) profit margin quintiles and examine whether facilities with lower profit margins are more likely to be penalized by SNF-VBP. RESEARCH DESIGN: We combined the first round of SNF-VBP performance data with SNF profit margins and characteristics data. Our outcome variables included estimated penalty amount and a binary measure for whether facilities were penalized by the SNF-VBP. We categorized SNFs into 5 profit margin quintiles and examined the relationship between profit margins and SNF-VBP performance using descriptive and regression analysis. RESULTS: The average profit margins for SNFs in the lowest profit margin quintile was -14.4% compared with the average profit margin of 11.1% for SNFs in the highest profit margin quintile. In adjusted regressions, SNFs in the lowest profit margin quintile had 17% higher odds of being penalized under SNF-VBP compared with facilities in the highest profit margin quintile. The average penalty for SNFs in the lowest profit margin quintile was $22,312. CONCLUSIONS: SNFs in the lowest profit margins are more likely to be penalized by the SNF-VBP, and these losses can exacerbate quality problems in SNFs with lower quality. Alternative approaches to measuring and rewarding SNFs under SNF-VBP or programs to assist struggling SNFs is warranted, particularly considering the coronavirus disease 2019 pandemic, which requires resources for prevention and management.

The NLRP3 inflammasome and COVID-19: Activation, pathogenesis and therapeutic strategies.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical presentations, ranging from asymptomatic cases to severe pneumonia or even death. In severe COVID-19 cases, an increased level of proinflammatory cytokines has been observed in the bloodstream, forming the so-called "cytokine storm". Generally, nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 (NLRP3) inflammasome activation intensely induces cytokine production as an inflammatory response to viral infection. Therefore, the NLRP3 inflammasome can be a potential target for the treatment of COVID-19. Hence, this review first introduces the canonical NLRP3 inflammasome activation pathway. Second, we review the cellular/molecular mechanisms of NLRP3 inflammasome activation by SARS-CoV-2 infection (e.g., viroporins, ion flux and the complement cascade). Furthermore, we describe the involvement of the NLRP3 inflammasome in the pathogenesis of COVID-19 (e.g., cytokine storm, respiratory manifestations, cardiovascular comorbidity and neurological symptoms). Finally, we also propose several promising inhibitors targeting the NLRP3 inflammasome, cytokine products and neutrophils to provide novel therapeutic strategies for COVID-19.

High Dose Intravenous Vitamin C for Preventing The Disease Aggravation of Moderate COVID-19 Pneumonia. A Retrospective Propensity Matched Before-After Study.

Background: Coronavirus disease 2019 (COVID-19) pandemic is continuing to impact multiple countries worldwide and effective treatment options are still being developed. In this study, we investigate the potential of high-dose intravenous vitamin C (HDIVC) in the prevention of moderate COVID-19 disease aggravation. Methods: In this retrospective before-after case-matched clinical study, we compare the outcome and clinical courses of patients with moderate COVID-19 patients who were treated with an HDIVC protocol (intravenous injection of vitamin C, 100 mg/kg/day, 1 g/h, for 7 days from admission) during a one-month period (between March 18 and april 18, 2020, HDIVC group) with a control group treated without the HDIVC protocol during the preceding two months (January 18 to March 18, 2020). Patients in the two groups were matched in a 1:1 ratio according to age and gender. Results: The HDIVC and control groups each comprised 55 patients. For the primary outcomes, there was a significant difference in the number of patients that evolved from moderate to severe type between the two groups (HDIVC: 4/55 vs. control: 12/55, relative risk [RR] = 0.28 [0.08, 0.93], P = 0.03). Compared to the control group, there was a shorter duration of systemic inflammatory response syndrome (SIRS) (P = 0.0004) during the first week and lower SIRS occurrence (2/21 vs 10/22, P = 0.0086) on Day 7 (6-7 days after admission). In addition, HDIVC group had lower C-reactive protein levels (P = 0.005) and higher number of CD4+ T cells from Day 0 (on admission) to Day 7 (P = 0.04)." The levels of coagulation indicators, including activated partial thromboplastin time and D-dimer were also improved in the HDIVC compared to the control group on Day 7. Conclusion: HDIVC may be beneficial in limiting disease aggravation in the early stage of COVID-19 pneumonia, which may be related to its improvements on the inflammatory response, immune function and coagulation function. Further randomized controlled trials are required to augment these findings.

Nursing Home Profit Margins and Citations for Infection Prevention and Control.

OBJECTIVES: Recent rampant spread of COVID-19 cases in nursing homes has highlighted the concerns around nursing homes' ability to contain the spread of infections. The ability of nursing homes to invest in quality improvement initiatives may depend on resource availability. In this study, we sought to examine whether lower profit margins, as a proxy for lack of resources, are associated with persistent infection control citations. DESIGN: We conducted a retrospective study. SETTING AND PARTICIPANTS: Medicare-certified nursing homes in the US with financial and facility characteristics data (n = 12,194). METHODS: We combined facility-level data on nursing home profit margins from Medicare Cost Reports with deficiency citation data from Nursing Home Compare (2017-2019) and facility characteristics data from LTCFocus.org. We descriptively analyzed infection control citations by profit margins quintiles. We used logistic regressions to examine the relationship between profit margin quintiles and citations for infection prevention and control, adjusting for facility and market characteristics. RESULTS: About three-fourths of all facilities received deficiency citations for infection prevention and control during 1 or more years from 2017 to 2019 with about 10% of facilities cited in all 3 years. Facilities in the highest profit margin quintile had 7.6% of facilities with citations for infection prevention and control in each of the 3 years compared with 8.1%, 10.0%, 10.7%, and 13.7% for facilities in the fourth, third, second, and first quintiles of profit margins, respectively. Multivariable regressions showed that facilities with the lowest profit margins (first quintile) had 54.3% higher odds of being cited in at least 1 year and 87.6% higher odds of being cited in each of the 3 years compared with facilities with the highest profit margins (fifth quintile). CONCLUSIONS AND IMPLICATIONS: Our findings indicate that nursing homes may need more resources to prevent citations for infection prevention and control.

Modeling and tracking Covid-19 cases using Big Data analytics on HPCC system platformm.

This project is funded by the US National Science Foundation (NSF) through their NSF RAPID program under the title "Modeling Corona Spread Using Big Data Analytics." The project is a joint effort between the Department of Computer & Electrical Engineering and Computer Science at FAU and a research group from LexisNexis Risk Solutions. The novel coronavirus Covid-19 originated in China in early December 2019 and has rapidly spread to many countries around the globe, with the number of confirmed cases increasing every day. Covid-19 is officially a pandemic. It is a novel infection with serious clinical manifestations, including death, and it has reached at least 124 countries and territories. Although the ultimate course and impact of Covid-19 are uncertain, it is not merely possible but likely that the disease will produce enough severe illness to overwhelm the worldwide health care infrastructure. Emerging viral pandemics can place extraordinary and sustained demands on public health and health systems and on providers of essential community services. Modeling the Covid-19 pandemic spread is challenging. But there are data that can be used to project resource demands. Estimates of the reproductive number (R) of SARS-CoV-2 show that at the beginning of the epidemic, each infected person spreads the virus to at least two others, on average (Emanuel et al. in N Engl J Med. 2020, Livingston and Bucher in JAMA 323(14):1335, 2020). A conservatively low estimate is that 5 % of the population could become infected within 3 months. Preliminary data from China and Italy regarding the distribution of case severity and fatality vary widely (Wu and McGoogan in JAMA 323(13):1239-42, 2020). A recent large-scale analysis from China suggests that 80 % of those infected either are asymptomatic or have mild symptoms; a finding that implies that demand for advanced medical services might apply to only 20 % of the total infected. Of patients infected with Covid-19, about 15 % have severe illness and 5 % have critical illness (Emanuel et al. in N Engl J Med. 2020). Overall, mortality ranges from 0.25 % to as high as 3.0 % (Emanuel et al. in N Engl J Med. 2020, Wilson et al. in Emerg Infect Dis 26(6):1339, 2020). Case fatality rates are much higher for vulnerable populations, such as persons over the age of 80 years (> 14 %) and those with coexisting conditions (10 % for those with cardiovascular disease and 7 % for those with diabetes) (Emanuel et al. in N Engl J Med. 2020). Overall, Covid-19 is substantially deadlier than seasonal influenza, which has a mortality of roughly 0.1 %. Public health efforts depend heavily on predicting how diseases such as those caused by Covid-19 spread across the globe. During the early days of a new outbreak, when reliable data are still scarce, researchers turn to mathematical models that can predict where people who could be infected are going and how likely they are to bring the disease with them. These computational methods use known statistical equations that calculate the probability of individuals transmitting the illness. Modern computational power allows these models to quickly incorporate multiple inputs, such as a given disease's ability to pass from person to person and the movement patterns of potentially infected people traveling by air and land. This process sometimes involves making assumptions about unknown factors, such as an individual's exact travel pattern. By plugging in different possible versions of each input, however, researchers can update the models as new information becomes available and compare their results to observed patterns for the illness. In this paper we describe the development a model of Corona spread by using innovative big data analytics techniques and tools. We leveraged our experience from research in modeling Ebola spread (Shaw et al. Modeling Ebola Spread and Using HPCC/KEL System. In: Big Data Technologies and Applications 2016 (pp. 347-385). Springer, Cham) to successfully model Corona spread, we will obtain new results, and help in reducing the number of Corona patients. We closely collaborated with LexisNexis, which is a leading US data analytics company and a member of our NSF I/UCRC for Advanced Knowledge Enablement. The lack of a comprehensive view and informative analysis of the status of the pandemic can also cause panic and instability within society. Our work proposes the HPCC Systems Covid-19 tracker, which provides a multi-level view of the pandemic with the informative virus spreading indicators in a timely manner. The system embeds a classical epidemiological model known as SIR and spreading indicators based on causal model. The data solution of the tracker is built on top of the Big Data processing platform HPCC Systems, from ingesting and tracking of various data sources to fast delivery of the data to the public. The HPCC Systems Covid-19 tracker presents the Covid-19 data on a daily, weekly, and cumulative basis up to global-level and down to the county-level. It also provides statistical analysis for each level such as new cases per 100,000 population. The primary analysis such as Contagion Risk and Infection State is based on causal model with a seven-day sliding window. Our work has been released as a publicly available website to the world and attracted a great volume of traffic. The project is open-sourced and available on GitHub. The system was developed on the LexisNexis HPCC Systems, which is briefly described in the paper.

Cardiovascular manifestations in severe and critical patients with COVID-19.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could cause virulent infection leading to Corona Virus Disease 2019 (COVID-19)-related pneumonia as well as multiple organ injuries. HYPOTHESIS: COVID-19 infection may result in cardiovascular manifestations leading to worse clinical outcome. METHODS: Fifty four severe and critical patients with confirmed COVID-19 were enrolled. Risk factors predicting the severity of COVID-19 were analyzed. RESULTS: Of the 54 patients (56.1 ± 13.5 years old, 66.7% male) with COVID-19, 39 were diagnosed as severe and 15 as critical cases. The occurrence of diabetes, the level of D-dimer, inflammatory and cardiac markers in critical cases were significantly higher. Troponin I (TnI) elevation occurred in 42.6% of all the severe and critical patients. Three patients experienced hypotension at admission and were all diagnosed as critical cases consequently. Hypotension was found in one severe case and seven critical cases during hospitalization. Sinus tachycardia is the most common type of arrythmia and was observed in 23 severe patients and all the critical patients. Atrioventricular block and ventricular tachycardia were observed in critical patients at end stage while bradycardia and atrial fibrillation were less common. Mild pericardial effusion was observed in one severe case and five critical cases. Three critical cases suffered new onset of heart failure. Hypotension during treatment, severe myocardial injury and pericardial effusion were independent risk factors predicting the critical status of COVID-19 infection. CONCLUSION: This study has systemically observed the impact of COVID-19 on cardiovascular system, including myocardial injury, blood pressure, arrythmia and cardiac function in severe and critical cases. Monitoring of vital signs and cardiac function of COVID-19 patients and applying potential interventions especially for those with hypotension during treatment, severe myocardial injury or pericardial effusion, is of vital importance.

A Universal Design of Betacoronavirus Vaccines against COVID-19, MERS, and SARS.

Vaccines are urgently needed to control the ongoing pandemic COVID-19 and previously emerging MERS/SARS caused by coronavirus (CoV) infections. The CoV spike receptor-binding domain (RBD) is an attractive vaccine target but is undermined by limited immunogenicity. We describe a dimeric form of MERS-CoV RBD that overcomes this limitation. The RBD-dimer significantly increased neutralizing antibody (NAb) titers compared to conventional monomeric form and protected mice against MERS-CoV infection. Crystal structure showed RBD-dimer fully exposed dual receptor-binding motifs, the major target for NAbs. Structure-guided design further yielded a stable version of RBD-dimer as a tandem repeat single-chain (RBD-sc-dimer) which retained the vaccine potency. We generalized this strategy to design vaccines against COVID-19 and SARS, achieving 10- to 100-fold enhancement of NAb titers. RBD-sc-dimers in pilot scale production yielded high yields, supporting their scalability for further clinical development. The framework of immunogen design can be universally applied to other beta-CoV vaccines to counter emerging threats.