Use telehealth as needed: telehealth substitutes in-person primary care and associates with the changes in unplanned events and follow-up visits.

BACKGROUND: Telehealth rapidly expanded since the outbreak of the COVID-19 pandemic. This study aims to understand how telehealth can substitute in-person services by 1) estimating the changes in non-COVID emergency department (ED) visits, hospitalizations, and care costs among US Medicare beneficiaries by visit modality (telehealth vs. in-person) during the COVID-19 pandemic relative to the previous year; 2) comparing the follow-up time and patterns between telehealth and in-person care. METHODS: A retrospective and longitudinal study design using US Medicare patients 65 years or older from an Accountable Care Organization (ACO). The study period was April-December 2020, and the baseline period was March 2019 - February 2020. The sample included 16,222 patients, 338,872 patient-month records and 134,375 outpatient encounters. Patients were categorized as non-users, telehealth only, in-person care only and users of both types. Outcomes included the number of unplanned events and costs per month at the patient level; number of days until the next visit and whether the next visit happened within 3-, 7-, 14- and 30-days at the encounter level. All analyses were adjusted for patient characteristics and seasonal trends. RESULTS: Beneficiaries who used only telehealth or in-person care had comparable baseline health conditions but were healthier than those who used both types of services. During the study period, the telehealth only group had significantly fewer ED visits/hospitalizations and lower Medicare payments than the baseline (ED 13.2, 95% CI [11.6, 14.7] vs. 24.6 per 1,000 patients per month and hospitalization 8.1 [6.7, 9.4] vs. 12.7); the in-person only group had significantly fewer ED visits (21.9 [20.3, 23.5] vs. 26.1) and lower Medicare payments, but not hospitalizations; the both-types group had significantly more hospitalizations (23.0 [21.4, 24.6] vs. 17.8). Telehealth was not significantly different from in-person encounters in number of days until the next visit (33.4 vs. 31.2 days) or the probabilities of 3- and 7-day follow-up visits (9.2 vs. 9.3% and 21.8 vs.23.5%). CONCLUSIONS: Patients and providers treated telehealth and in-person visits as substitutes and used either depending on medical needs and availability. Telehealth did not lead to sooner or more follow-up visits than in-person services.

Post-Acute Care in Inpatient Rehabilitation Facilities between Traditional Medicare and Medicare Advantage Plans Before and During the COVID-19 Pandemic

Objectives Compare post-acute care (PAC) utilization and outcomes in inpatient rehabilitation facilities (IRF) between beneficiaries covered by Traditional Medicare (TM) and Medicare Advantage (MA) plans during the COVID-19 pandemic relative to the previous year. Design This multiyear cross-sectional study used Inpatient Rehabilitation Facility – Patient Assessment Instrument (IRF-PAI) data to assess PAC delivery from January 2019 to December 2020. Setting and Participants Inpatient rehabilitation for stroke, hip fracture, joint replacement, cardiac and pulmonary conditions among Medicare beneficiaries 65 years or older. Methods Patient-level multivariate regression models with difference-in-differences approach were used to compare TM and MA plans in length of stay (LOS), payment per episode, functional improvements, and discharge locations. Results A total of 271,188 patients were analyzed (Women [57.1%], mean [SD] age 77.8 [0.06] years), among whom 138,277 were admitted for stroke, 68,488 hip fracture, 19,020 joint replacement, 35,334 cardiac and 10,069 pulmonary conditions. Before the pandemic, MA beneficiaries had longer LOS (+0.22 days 95% CI [0.15, 0.29]), lower payment per episode (-$361.05 [-573.38, -148.72]), more discharges to home with HHA (48.9% vs. 46.6%), and less to SNF (15.7% vs. 20.2%) than TM beneficiaries. During the pandemic, both plan types had shorter LOS (-0.68 days [0.54, 0.84]), higher payment (+$798 [558, 1036]), increased discharges to home with HHA (52.8% vs. 46.6%) and decreased discharges to SNF (14.5% vs. 20.2%) than before. Differences between TM and MA beneficiaries in these outcomes became smaller and less significant. All results were adjusted for beneficiary and facility characteristics. Conclusions and Implications Though the COVID-19 pandemic affected PAC delivery in IRF in the same directions for both TM and MA plans, the timing, time duration and magnitude of the impacts were different across measures and admission conditions. Differences between the two plan types shrunk and performance across all dimensions became more comparable over time.

The Relative Importance of Hospital Discharge and Patient Composition in Changing Post-Acute Care Utilization and Outcomes Among Medicare Beneficiaries.

Background: The COVID-19 pandemic changed care delivery. But the mechanisms of changes were less understood. Objectives: Examine the extent to which the volume and pattern of hospital discharge and patient composition contributed to the changes in post-acute care (PAC) utilization and outcomes during the pandemic. Research design: Retrospective cohort study. Medicare claims data on hospital discharges in a large healthcare system from March 2018 to December 2020. Subjects: Medicare fee-for-service beneficiaries, 65 years or older, hospitalized for non-COVID diagnoses. Measures: Hospital discharges to Home Health Agencies (HHA), Skilled Nursing Facilities (SNF), and Inpatient Rehabilitation Facilities (IRF) versus home. Thirty- and ninety-day mortality and readmission rates. Outcomes were compared before and during the pandemic with and without adjustment for patient characteristics and/or interactions with the pandemic onset. Results: During the pandemic, hospital discharges declined by 27%. Patients were more likely to be discharged to HHA (+4.6%, 95% CI [3.2%, 6.0%]) and less likely to be discharged to either SNF (-3.9%, CI [-5.2%, -2.7%]) or to home (-2.8% CI [-4.4%, -1.3%]). Thirty- and ninety-day mortality rates were significantly higher by 2% to 3% points post-pandemic. Readmission were not significantly different. Up to 15% of the changes in discharge patterns and 5% in mortality rates were attributable to patient characteristics. Conclusions: Shift in discharge locations were the main driver of changes in PAC utilization during the pandemic. Changes in patient characteristics explained only a small portion of changes in discharge patterns and were mainly channeled through general impacts rather than differentiated responses to the pandemic.

Alcohol Consumption and Mental Health during the COVID-19 Pandemic.

AIMS: To examine the association between alcohol consumption and mental health during the COVID-19 pandemic. METHODS: An anonymous online survey was distributed among US adults during May-August 2020 through social networks and ResearchMatch. We collected information on demographic, lifestyles and mental health symptoms including anxiety, depression, stress and post-traumatic stress disorder. Logistic regression models were used to examine the cross-sectional association between alcohol consumption and mental health symptoms. We also examined effect modification by race, age, gender, social support, financial insecurity and quarantine status. RESULTS: The analytical sample consists of 3623 adults. Stable drinking habits and regular drinking behaviors were found to co-exist with better mental health status. Participants who increased their alcohol use had higher odds of developing mental health disorders than those who maintained their pre-pandemic drinking habits. Additionally, participants who engaged in binge drinking during the pandemic had higher odds of depression and stress than those who did not. The associations regarding increased drinking and binge drinking in relation to adverse mental health outcomes were stronger among females, racial minorities, and individuals with financial concerns, poor social support and restricted quarantine status than their counterparts. CONCLUSIONS: During the early stage of the COVID-19 pandemic, increased alcohol use and binge drinking are cross-sectionally associated with higher odds of mental health disorders, which highlighted the need for targeted intervention to address the mental health needs of individuals who have engaged in these behaviors, especially among females, minorities, those with insecurities or with restricted quarantine status.

Mental health conditions of Chinese international students and associated predictors amidst the pandemic.

The current study aims to examine the mental health conditions and the associated predictors among Chinese international students. A sample of 256 Chinese international students aged 16 or above living primarily in Canada were asked to complete an online survey. Mental health conditions were assessed with the Depression, Anxiety, and Stress Scale-21 and the Physical and Mental Health Summary Scales. 15.3%, 20.4%, and 10.5% of respondents reported severe to extremely severe depression, anxiety, and stress levels, respectively. Univariate analysis of variance models and multiple linear regression models identified education and financial status as significant sociodemographic predictors while controlling for the effect of physical health status. Higher financial status and lower level of education were associated with better mental health conditions. These findings shed light on our understanding of mental health conditions and the risk factors among Chinese international students during the COVID-19 pandemic.

Application of deep learning-based diagnostic systems in screening asymptomatic COVID-19 patients among oversea returnees.

INTRODUCTION: Our study aimed to investigate the performance of deep learning (DL)-based diagnostic systems in alerting against COVID-19, especially among asymptomatic individuals coming from overseas, and to analyze the features of identified asymptomatic patients in detail. METHODOLOGY: DL diagnostic systems were deployed to assist in the screening of COVID-19, including the pneumonia system and pulmonary nodules system. 1,917 overseas returnees who underwent CT examination and rRT-PCR tests were enrolled. DL pneumonia system promptly alerted clinicians to suspected COVID-19 after CT examinations while the performance was evaluated with rRT-PCR results as the reference. The radiological features of asymptomatic COVID-19 cases were described according to the Nomenclature of the Fleischner Society. RESULTS: Fifty-three cases were confirmed as COVID-19 patients by rRT-PCR tests, including 5 asymptomatic cases. DL pneumonia system correctly alerted 50 cases as suspected COVID-19 with a sensitivity of 0.9434 and specificity of 0.9592 (within 2 minutes per case); while the pulmonary nodules system alerted 2 of the 3 missed asymptomatic cases. Additionally, five asymptomatic patients presented different characteristics such as elevated creatine kinase level and prolonged prothrombin time, as well as atypical radiological features. CONCLUSIONS: DL diagnostic systems are promising complementary approaches for prompt screening of imported COVID-19 patients, even the imported asymptomatic cases. Unique clinical and radiological characteristics of asymptomatic cases might be of great value in screening as well. ADVANCES IN KNOWLEDGE: DL-based systems are practical, efficient, and reliable to assist radiologists in screening COVID-19 patients. Differential features of asymptomatic patients might be useful to clinicians in the frontline to differentiate asymptomatic cases.

COVID-19 metabolism: Mechanisms and therapeutic targets.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS-CoV-2-induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID-19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS-CoV-2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID-19 metabolism. SARS-CoV-2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS-CoV-2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID-19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS-CoV-2-induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID-19 pandemic.

Healthy Community-Life Circle Planning Combining Objective Measurement and Subjective Evaluation: Theoretical and Empirical Research

Background: The world faces vast health challenges, and urban residents living in high-density areas have even greater demand for healthy lifestyles. Methods: Based on the data of points of interest, a field survey, and an interview, we explored the healthy community-life circle in the downtown area of Chengdu, China from two perspectives: objective measurement and subjective perception of residents. We evaluated the coverage rate and convenience in accessing eight types of health service facilities within a 15-min walk using linear and logistics regression models to explore the degree of resident satisfaction with facilities and influencing factors. Results: Results showed significant differences in coverage rates between different districts. The overall convenience in accessing health service facilities decreased gradually from the city center to the outskirts. The social environment, the layout of health service facilities, and residents’ travel habits were related to health service facility satisfaction. Results also showed significant differences in various facilities’ accessibility satisfaction between objective measurement and residents’ perception measurement. Compared with subjective measurement, the objective measurements of accessibility for sports venues (objectively measured average minus perceived average: −1.310), sports zones (−0.740), and specialized hospitals (−1.081) were lower;those for community hospitals (0.095), clinics (1.025), and pharmacies (0.765) were higher;and facility accessibility measured by subjective perception had a more significant impact on health facility satisfaction. Pharmacies (OR: 1.932) and community hospitals (OR: 1.751) had the largest impact among the eight types of facilities. Conclusion: This study proposed to construct a healthy community-life circle with a category and hierarchy system.

Understanding Consumer Online Impulse Buying in Live Streaming E-Commerce: A Stimulus-Organism-Response Framework.

With the proliferation of live streaming, there is evidence that online impulse buying is becoming an emerging phenomenon. Although many studies have investigated impulse buying in the context of offline shopping and business-to-consumer e-commerce, online impulse buying in live streaming has attracted little attention. In this study, we aim to explore the effect of social presence in live streaming on customer impulse buying based on the stimulus-organism-response framework. The research model presented here identifies pleasure and arousal as the mediation of impulse buying in live streaming. We use the AMOST and IBM SPSS PROCESS software to estimate our model based on data at the minute level from 189 customers, who watched live streaming in the past three months. The results suggest that the social presence of the broadcaster and the social presence of the live streamer positively affect impulse buying directly and indirectly via pleasure and arousal, promoting consumer online impulse buying in live streaming, but the social presence of the viewers has no significant effect on pleasure and arousal. For practice, our results can help policymakers and operators of the live streaming platform alleviate impulse buying in the digital world.

Evaluation of Clinical and Immune Responses in Recovered Children with Mild COVID-19.

The coronavirus disease 2019 (COVID-19) has spread globally and variants continue to emerge, with children are accounting for a growing share of COVID-19 cases. However, the establishment of immune memory and the long-term health consequences in asymptomatic or mildly symptomatic children after severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We collected clinical data and whole blood samples from discharged children for 6-8 months after symptom onset among 0-to-14-year-old children. Representative inflammation signs returned to normal in all age ranges. The infants and young children (0-4 years old) had lung lesions that persisted for 6-8 months and were less responsive for antigen-specific IgG secretion. In the 5-to-14-year-old group, lung imaging abnormalities gradually recovered, and the IgG-specific antibody response was strongest. In addition, we found a robust IgM+ memory B cell response in all age. Memory T cells specific for the spike or nucleocapsid protein were generated, with no significant difference in IFN-γ response among all ages. Our study highlights that although lung lesions caused by COVID-19 can last for at least 6-8 months in infants and young children, most children have detectable residual neutralizing antibodies and specific cellular immune responses at this stage.

Disparities in the Use of In-Person and Telehealth Primary Care Among High- and Low-Risk Medicare Beneficiaries During COVID-19.

We conducted a retrospective cohort study using a difference-in-differences design to estimate differences in primary care outpatient clinic visit utilization among high- and low-risk Medicare aging beneficiaries from an Accountable Care Organization during the COVID-19 pandemic compared to a control cohort from the previous year. High-risk was defined as having a Hierarchical Condition Category score of 2 or higher. A total of 582 101 patient-month records were analyzed. After adjusting for patient characteristics, those in the high-risk group had 339 (95% CI [333, 345]) monthly outpatient encounters (in-person and telehealth) per 1000 patients compared to 186 (95% CI [182, 190]) in the low-risk group. This represented a 22.8% and 26.5% decline from the previous year in each group, respectively. Within each group, there was lower utilization among those who were older, male, or dually eligible for Medicaid in the high-risk group and among those who were younger, male, or non-white in the low-risk group. Telehealth use was less common among patients who were older, dually eligible for Medicaid or living in rural/suburban areas compared to urban areas. All results were significant at the 95% level. We found significant disparities based on age, gender, insurance status, and non-white race in primary care utilization during the pandemic among Medicare beneficiaries. With the exception of gender, these disparities differed between high- and low-risk groups. Interventions targeting these vulnerable groups may improve health equity in the setting of public health emergencies.

AcademyHealth Annual Research Meeting (ARM): A Selection of Abstracts Accepted for Oral Presentation, 2021.

RESEARCH OBJECTIVE: To investigate the extent to which telehealth visits mitigated COVID-19 pandemic-related impacts on in-person outpatient visits among Medicare beneficiaries, including those who are high-cost high-need. High-cost high-need patients were defined as those 65 years or older and with 2 or higher Hierarchical Condition Categories (HCC) scores. STUDY DESIGN: A difference-in-difference design was used to estimate the change in outpatient in-person and telehealth utilization for the COVID-19 pandemic cohort compared to the control cohort in the prior year. POPULATION STUDIED: Medicare patients from an Accountable Care Organization (ACO) were used as the study sample. The pandemic cohort was defined as those enrolled in the ACO in 2019-2020 (N = 21,361). The control cohort was defined as those enrolled in the ACO in 2018-2019 (N = 20,028). The study period was defined as April-September 2020 for the pandemic cohort and the same months in 2019 for the control cohort, with the preceding 12 months used as the baseline periods, respectively. Over 740,000 patient-month records were analyzed using logistic and negative binomial regressions. The models were adjusted for patient-level characteristics, including HCC scores, which reflect the complexity of patient health conditions and risk for future healthcare costs. PRINCIPAL FINDINGS: The total number of outpatient encounters (in-person and telehealth) in both primary and specialty care decreased by 41.5% in April 2020 compared to the pre-pandemic period. Telehealth comprised 78% of all outpatient encounters in April 2020 but declined to 22% by the end of September 2020. Only about 40% of all patients had at least one telehealth encounter between April-September 2020. Compared to the control cohort, the pandemic cohort experienced a monthly average of 113 fewer primary care encounters per 1000 patients (OR: 0.75, 95% CI: [0.73, 0.77]) and 49 fewer specialty care encounters (OR: 0.82, 95% CI: [0.80, 0.85]) over the six-month study period. This represented a decline of 25.6% and 17.3% in primary care and specialty encounters, respectively, among high-cost high-need patients. High-cost high-need patients or those with disabilities were more likely to use telehealth and experienced a lesser reduction in outpatient care utilization than other Medicare beneficiaries (OR: 1.20 and 1.06). Medicare beneficiaries with dual Medicaid coverage, those of non-white race/ethnic groups, and those living in rural/suburban areas were less likely to use telehealth and experienced a greater reduction in total outpatient care (OR: 0.86, 0.96 and 0.90). CONCLUSIONS: While there was a substantial significant increase in telehealth use in April 2020, utilization declined significantly during the six-month study period, and did not fully mitigate the decline in in-person outpatient visits resulting from the COVID-19 pandemic. While high-cost high-need Medicare patients and those with disabilities were more likely to use telehealth, disparities in telehealth usage and reductions in outpatient care remain among low-income, non-white, and rural Medicare beneficiaries. IMPLICATIONS FOR POLICY OR PRACTICE: Older patients insured by Medicare, including those with high-cost high-need or disabilities were able to make use of telehealth services for outpatient visits during the COVID-19 pandemic. Health policies and interventions should target improving telehealth access and delivery for advancing sustainability and equity among Medicare beneficiaries. PRIMARY FUNDING SOURCE: Patient-Centered Outcomes Research Institute.

The SARS-CoV-2 Nucleocapsid Protein and Its Role in Viral Structure, Biological Functions, and a Potential Target for Drug or Vaccine Mitigation.

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the world is still expanding. Thus, there is an urgent need to better understand this novel virus and find a way to control its spread. Like other coronaviruses, the nucleocapsid (N) protein is one of the most crucial structural components of SARS-CoV-2. This protein shares 90% homology with the severe acute respiratory syndrome coronavirus N protein, implying functional significance. Based on the evolutionary conservation of the N protein in coronavirus, we reviewed the currently available knowledge regarding the SARS-CoV-2 N protein in terms of structure, biological functions, and clinical application as a drug target or vaccine candidate.

COVID-19 Related Symptoms of Anxiety, Depression, and PTSD among US Adults.

During the COVID-19 pandemic, social distancing measures often result in individual isolation, which can lead to adverse mental outcomes. We collected online questionnaires from 3,952 US adults to examine the impact of "shelter-in-place" guidelines on mental health, and to explore potential disparities and modifiable factors. Self-reported anxiety, depression, and PTSD symptoms were associated with more restrictive quarantine. Younger adults, women, those with lower income, more insecurity, more media exposure, reduced physical activity, or worsened family relationships were particularly affected. Targeted prevention on susceptible subpopulations, including young adults and lower SES groups, might help mitigate disparities in COVID-19-related mental health problems.

Transmission dynamics of COVID-19 among index case family clusters in Beijing, China.

The outbreak of coronavirus disease-2019 (COVID-19) impacts public health dramatically around the world. The demographic characteristics, exposure history, dates of illness onset and dates of confirmed diagnosis were collected from the data of 24 family clusters from Beijing. The characteristics of the cases and the estimated key epidemiologic time-to-event distributions were described. The basic reproductive number (R0) was calculated. Among 89 confirmed COVID-19 patients from 24 family clusters, the median age was 38.0 years and 43.8% were male. The median of incubation period was 5.08 days (95% confidence interval (CI) 4.17-6.21). The median of serial interval was 6.00 days (95% CI 5.00-7.00). The basic reproductive number (R0) was 2.06 (95% CI 2.02-2.08). The median of onset-to-care-seeking days and the median of onset-to-hospital admission days were significantly reduced after 23 January 2020, which implied the enhanced public health awareness among families. With epidemic containment measures in place, the results can inform health authorities about possible extent of epidemic transmission within families. Furthermore, following initiation of interventions, public health measures are not only important for curbing the epidemic spread at the community level but also improve health seeking behaviour at the individual level.

Sex differences in clinical characteristics and risk factors for disease severity of hospitalized patients with COVID-19.

Recent studies reported sex differences in patients with coronavirus disease-2019 (COVID-19). We aim to analyze sex differences in clinical characteristics and risk factors for disease severity of hospitalized patients with COVID-19 in Beijing. All adults (185 cases) diagnosed with COVID-19 and admitted to Beijing Ditan Hospital, Capital Medical University were included in samples. The median age of all patients was 41 years. The mean body mass index (BMI) of males was relatively higher compared to females (p < 0.001). The proportion of male patients with coronary heart disease (CHD), nonalcoholic fatty liver disease (NAFLD), history of smoking and drinking was higher than females. Male patients developed more clinical symptoms, obtained more abnormal laboratory test results, while they were less aware of care-seeking than female patients. There were no significant differences in clinical complications and outcomes between two groups. Age (odds ratio [OR]: 1.082; 95% confidence interval [CI]: 1.034-1.132; p = 0.001) and BMI (OR: 1.237; 95% CI: 1.041-1.47; p = 0.016) were considered risk factors for refractory pneumonia in multivariate regression analysis. The findings of the current study showed that SARS-CoV-2 was more likely to affect older males with comorbidities. Further researches into factors underlying obesity and disease severity may provide mechanistic insight into COVID-19 development.

Infection and disease spectrum in individuals with household exposure to SARS-CoV-2: A family cluster cohort study.

We primarily quantified exposure patterns, transmission characteristics, and the clinical spectrum of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among household contacts of individuals with severe coronavirus disease-2019 (COVID-19). We conducted a retrospective cohort study of 20 index patients hospitalized with severe COVID-19 and 79 of their household contacts. We determined the transmission frequency, range of manifestations of SARS-CoV-2 infection, and factors associated with infection in household settings. Of the 79 household contacts, 53 (67%) developed SARS-CoV-2 infection (49 [62%] symptomatic, 4 [5%] asymptomatic). Eight patients (10%) developed severe COVID-19, and one died of COVID-19 pneumonia (case-fatality rate: 1.9%). The probability of SARS-CoV-2 infection was similar in children and adults (55% vs. 72%, p = .14), with children being less likely to develop the symptomatic disease (46% vs. 68%, p = .06). Handwashing ≥ 5 times/day was associated with reduced infection risk (52.8% vs. 76.9%, p = .04). SARS-CoV-2 has a high frequency of transmission among household contacts. Nonhospitalized individuals with SARS-CoV-2 infection should be quarantined in patient care facilities rather than at home to minimize spread, if possible, and frequent handwashing should be practiced to prevent transmission.

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

Background: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics. Methods: We trained a U-Net-based model on unenhanced chest CT scans obtained from 2447 patients admitted to Tongji Hospital (Wuhan, China) between Feb 1, 2020, and March 3, 2020 (1647 patients with RT-PCR-confirmed COVID-19 and 800 patients without COVID-19) to segment lung opacities and alert cases with COVID-19 imaging manifestations. The ability of artificial intelligence (AI) to triage patients suspected to have COVID-19 was assessed in a large external validation set, which included 2120 retrospectively collected consecutive cases from three fever clinics inside and outside the epidemic centre of Wuhan (Tianyou Hospital [Wuhan, China; area of high COVID-19 prevalence], Xianning Central Hospital [Xianning, China; area of medium COVID-19 prevalence], and The Second Xiangya Hospital [Changsha, China; area of low COVID-19 prevalence]) between Jan 22, 2020, and Feb 14, 2020. To validate the sensitivity of the algorithm in a larger sample of patients with COVID-19, we also included 761 chest CT scans from 722 patients with RT-PCR-confirmed COVID-19 treated in a makeshift hospital (Guanggu Fangcang Hospital, Wuhan, China) between Feb 21, 2020, and March 6, 2020. Additionally, the accuracy of AI was compared with a radiologist panel for the identification of lesion burden increase on pairs of CT scans obtained from 100 patients with COVID-19. Findings: In the external validation set, using radiological reports as the reference standard, AI-aided triage achieved an area under the curve of 0·953 (95% CI 0·949-0·959), with a sensitivity of 0·923 (95% CI 0·914-0·932), specificity of 0·851 (0·842-0·860), a positive predictive value of 0·790 (0·777-0·803), and a negative predictive value of 0·948 (0·941-0·954). AI took a median of 0·55 min (IQR: 0·43-0·63) to flag a positive case, whereas radiologists took a median of 16·21 min (11·67-25·71) to draft a report and 23·06 min (15·67-39·20) to release a report. With regard to the identification of increases in lesion burden, AI achieved a sensitivity of 0·962 (95% CI 0·947-1·000) and a specificity of 0·875 (95 %CI 0·833-0·923). The agreement between AI and the radiologist panel was high (Cohen's kappa coefficient 0·839, 95% CI 0·718-0·940). Interpretation: A deep learning algorithm for triaging patients with suspected COVID-19 at fever clinics was developed and externally validated. Given its high accuracy across populations with varied COVID-19 prevalence, integration of this system into the standard clinical workflow could expedite identification of chest CT scans with imaging indications of COVID-19. Funding: Special Project for Emergency of the Science and Technology Department of Hubei Province, China.

Analysis of ACE2 Gene-Encoded Proteins Across Mammalian Species.

Human beings are currently experiencing a serious public health event. Novel coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), has infected about 3 million people worldwide and killed more than 200,000, most being the elderly or people with potential chronic diseases or in immunosuppressive states. According to big data analysis, there are many proteins homologous to or interacting with the angiotensin-converting enzyme 2 (ACE2), which, therefore, may not be the only receptor for the novel coronavirus; other receptors may also exist in host cells of different species. These potential receptors may also play an important role in the infection process of the novel coronavirus. The current study aimed to discover such key proteins or receptors and analyze the susceptibility of different animals to the novel coronavirus, in order to reveal the transmission process of the virus in cross-species infection. We analyzed the proteins coded by the ACE2 gene in different mammalian species and predicted their correlation and homology with the human ACE2 receptor. The major finding of our predictive analysis suggested ACE2 gene-encoded proteins to be highly homologous across mammals. Based on their high homology, their possibility of binding the spike-protein of SARS-CoV-2 is quite high and species such as Felis catus, Bos taurus, Rattus norvegicus etc. may be potential susceptible hosts; special monitoring is particularly required for livestock that are in close contact with humans. Our results might provide ideas for the prevention and control of the novel coronavirus pneumonia.

Pattern of liver injury in adult patients with COVID-19: a retrospective analysis of 105 patients.

BACKGROUND: Recent studies reported that patients with coronavirus disease-2019 (COVID-19) might have liver injury. However, few data on the combined analysis and change patterns of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and total bilirubin (TBil) have been shown. METHODS: This is a single-center retrospective study. A total of 105 adult patients hospitalized for confirmed COVID-19 in Beijing Ditan Hospital between January 12, and March 17, 2020 were included, and divided into mild group (n = 79) and severe group(n = 26). We compared liver functional test results between the two groups. Category of ALT change during the disease course was also examined. RESULTS: 56.2% (59/105) of the patients had unnormal ALT, AST, or total TBil throughout the course of the disease, but in 91.4% (96/105) cases the level of ALT, AST or TBil ≤3 fold of the upper limit of normal reference range (ULN). The overall distribution of ALT, AST, and TBil were all significantly difference between mild and severe group (P <  0.05). The percentage of the patients with elevated both ALT and AST was 12.7% (10/79) in mild cases vs. 46.2% (12/26) in severe cases (P = 0.001). 34.6% (9/26) severe group patients started to have abnormal ALT after admission, and 73.3% (77/105) of all patients had normal ALT before discharge. CONCLUSIONS: Elevated liver function index is very common in patients with COVID-19 infection, and the level were less than 3 × ULN, but most are reversible. The abnormality of 2 or more indexes is low in the patients with COVID-19, but it is more likely to occur in the severe group.