Miracle-dz/UniFAR-FTUs huggingface dataset:
Early prediction of mortality risk among severe COVID-19 patients using machine learning

Abstract Background Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been spreading globally. The number of deaths has increased with the increase in the number of infected patients. We aimed to develop a clinical model to predict the outcome of severe COVID-19 patients early. Methods Epidemiological, clinical, and first laboratory findings after admission of 183 severe COVID-19 patients (115 survivors and 68 nonsurvivors) from the Sino-French New City Branch of Tongji Hospital were used to develop the predictive models. Five machine learning approaches (logistic regression, partial least squares regression, elastic net, random forest, and bagged flexible discriminant analysis) were used to select the features and predict the patients' outcomes. The area under the receiver operating characteristic curve (AUROC) was applied to compare the models' performance. Sixty-four severe COVID-19 patients from the Optical Valley Branch of Tongji Hospital were used to externally validate the final predictive model. Results The baseline characteristics and laboratory tests were significantly different between the survivors and nonsurvivors. Four variables (age, high-sensitivity C-reactive protein level, lymphocyte count, and d-dimer level) were selected by all five models. Given the similar performance among the models, the logistic regression model was selected as the final predictive model because of its simplicity and interpretability. The AUROCs of the derivation and external validation sets were 0.895 and 0.881, respectively. The sensitivity and specificity were 0.892 and 0.687 for the derivation set and 0.839 and 0.794 for the validation set, respectively, when using a probability of death of 50% as the cutoff. The individual risk score based on the four selected variables and the corresponding probability of death can serve as indexes to assess the mortality risk of COVID-19 patients. The predictive model is freely available at https://phenomics.fudan. edu.cn/risk_scores/. Conclusions Age, high-sensitivity C-reactive protein level, lymphocyte count, and d-dimer level of COVID-19 patients at admission are informative for the patients' outcomes.
Nosocomial infections among patients with COVID-19, SARS and MERS: a rapid review and meta-analysis

Background: COVID-19, a disease caused by SARS-CoV-2 coronavirus, has now spread to most countries and regions of the world. As patients potentially infected by SARS-CoV-2 need to visit hospitals, the incidence of nosocomial infection can be expected to be high. Therefore, a comprehensive and objective understanding of nosocomial infection is needed to guide the prevention and control of the epidemic. Methods: We searched major international and Chinese databases Medicine, Web of science, Embase, Cochrane, CBM(China Biology Medicine disc), CNKI (China National Knowledge Infrastructure) and Wanfang database)) for case series or case reports on nosocomial infections of COVID-19, SARS(Severe Acute Respiratory Syndromes) and MERS(Middle East Respiratory Syndrome) from their inception to March 31st, 2020. We conducted a meta-analysis of the proportion of nosocomial infection patients in the diagnosed patients, occupational distribution of nosocomial infection medical staff and other indicators. Results: We included 40 studies. Among the confirmed patients, the proportions of nosocomial infections were 44.0%, 36.0% and 56.0% for COVID-19, SARS and MERS, respectively. Of the confirmed patients, the medical staff and other hospital-acquired infections accounted for 33.0% and 2.0% of COVID-19 cases, 37.0% and 24.0% of SARS cases, and 19.0% and 36.0% of MERS cases, respectively. Nurses and doctors were the most affected among the infected medical staff. The mean numbers of secondary cases caused by one index patient were 29.3 and 6.3 for SARS and MERS, respectively. Conclusions: The proportion of nosocomial infection in patients with COVID-19 was 44%. Patients attending hospitals should take personal protection. Medical staff should be awareness of the disease to protect themselves and the patients. Keywords: COVID-19; meta-analysis; nosocomial infection; rapid review.
Outcomes of the 2019 novel coronavirus in patients with or without a history of cancer: a multi-centre North London experience

Background Four months after the first known case of the 2019 novel coronavirus disease (COVID-19), on the 11th March 2020, the WHO declared the outbreak a pandemic and acknowledged the potential to overwhelm national healthcare systems. The high prevalence and associated healthcare, social and economic challenges of COVID-19 suggest this pandemic is likely to have a major impact on cancer management, and has been shown to potentially have worse outcomes in this cohort of vulnerable patients (1). This study aims to compare the outcomes of reverse transcriptase polymerase chain reaction (RT-PCR) confirmed COVID-19 positive disease in patients with or without a history of cancer. Method: We retrospectively collected clinical, pathological and radiological characteristics and outcomes of COVID-19 RT-PCR positive cancer patients treated consecutively in four different North London hospitals (cohort A). Outcomes recorded included morbidity, mortality and length of hospital stay. All clinically relevant outcomes were then compared to consecutively admitted COVID-19 positive patients, without a history of cancer (cohort B), treated at the primary centre during the same time period (12th March- 7th April 2020). Results: A total of 52 electronic patient records during the study time period were reviewed. Cohort A (median age 76 years, 56% males) and cohort B (median age 58 years, 62% male) comprised of 26 patients each. With the exclusion of cancer, both had a median of 2 comorbidities. Within cohort A, the most frequent underlying cancer was colorectal (5/26) and prostate cancer (5/26), and 77% of patients in Cohort A had received previous anti-cancer therapy. The most common presenting symptoms were cough and pyrexia in both cohorts. Frequent laboratory findings included lymphopenia, anaemia and elevated CRP in both cohorts, whilst hypokalaemia, hypoalbuminaemia and hypoproteinaemia was predominantly seen amongst patients with cancer. Median duration of admission was 7 days in both cohorts. The mortality rate was the same in both cohorts (23%), with median age of mortality of 80 years. Of cancer patients who died, all were advanced stage, had been treated with palliative intent and had received anti-cancer therapy within 13 days of admission. Conclusion: Old age, late stage of cancer diagnosis and multiple co-morbidities adversely influence the outcome of patients with COVID-19 positive patients. Whilst extra caution is warranted in the administration of anti-cancer therapies pertaining to the risk of immune-suppression, this data does not demonstrate a higher risk to cancer patients compared to their non-cancer counterparts.
Do Weather Temperature and Median-age affect COVID-19 Transmission?

It was observed that the coldest countries and the eldest in terms of median-age were most distressed by COVID-19 pandemic, while the warmest countries and that have younger-aged population were the least affected. Therefore, this study utilized the non-linear least squares method to estimate the impact of weather temperatures and median age on COVID-19 cases per million in thirty-nine countries divided into two groups. The first group composed of twenty-four countries that announced the first COVID-19 case in January 2020, while the second group contains fifteen countries that witnessed the pandemic for the first time in February of the same year. The study revealed some major findings, which are: COVID-19 cases per million were not significantly affected by weather temperature or the median age in “January-group” countries (after 72.67 days on average), while COVID-19 cases per million increased significantly by decreasing temperatures, and increasing the median age in case of “February-group” countries (after an average of 44.80 days). This means that weather temperature and median age may influence the transmission rates of COVID-19 in its early stages, while weather temperature or median age no longer have effects in the advanced stages of the pandemic.
Clinical characteristics of children with COVID-19: a rapid review and meta-analysis

Abstract Background: Most guidelines on COVID-19 published so far include recommendations for patients regardless of age. Clinicians need a more accurate understanding of the clinical characteristics of children with COVID-19. Methods: We searched studies reporting clinical characteristics in children with COVID-19 published until March 31, 2020. We screened the literature, extracted the data and evaluated the risk of bias and quality of evidence of the included studies. We combined some of the outcomes (symptoms) in a single-arm meta-analysis using a random-effects model. Results: Our search retrieved 49 studies, including 25 case reports, 23 case series and one cohort study, with a total of 1667 patients. Our meta-analysis showed that most children with COVID-19 have mild symptoms. Eighty-three percent of the children were within family clusters of cases, and 19% had no symptoms. At least 7% with digestive symptoms. The main symptoms of children were fever (48%, 95% confidence interval [CI]: 39%, 56%) and cough (39%, 95% CI: 30%, 48%). The lymphocyte count was below normal level in only 15% [95% CI: 8%, 22%] of children which is different from adult patients. 66% [95% CI: 55%, 77%] of children had abnormal findings in CT imaging. Conclusions: Most children with COVID-19 have only mild symptoms, and many children are asymptomatic. Fever and cough are the most common symptoms in children. Vomiting and diarrhea were not common in children. The lymphocyte count is usually within the normal range in children.
Potential effectiveness and safety of antiviral agents in children with coronavirus disease 2019: a rapid review and meta-analysis

Background: The COVID-19 outbreak presents a new, life-threatening disease. Our aim was to assess the potential effectiveness and safety of antiviral agents for COVID-19 in children. Methods: Electronic databases from their inception to March, 31 2020 were searched for randomized controlled trials, clinical controlled trials and cohort studies of interventions with antiviral agents for children (less than 18 years of age) with COVID-19. Results: A total of 23 studies of indirect evidence with 6008 patients were included. The risks of bias in all studies were moderate to high in general. The effectiveness and safety of antiviral agents for children with COVID-19 is uncertain: For adults with COVID-19, lopinavir/ritonavir had no effect on mortality (risk ratio [RR]= 0.77, 95% confidence interval [CI] 0.45 to 1.30) and probability of negative PCR test (RR=0.98, 95 CI% 0.82 to 1.18). Arbidol had no benefit on probability of negative PCR test (RR=1.27, 95% CI 0.93 to 1.73). Hydroxychloroquine was not associated with increasing the probability of negative PCR result (RR=0.93, 95% CI 0.73 to 1.18). For adults with SARS, interferon was associated with reduced corticosteroid dose (weighted mean difference [WMD]=-0.14 g, 95% CI -0.21 to -0.07) but had no effect on mortality (RR=0.72, 95% CI 0.28 to 1.88); ribavirin did not reduce mortality (RR=0.68, 95% CI % 0.43 to 1.06) and was associated with high risk of severe adverse reactions; and oseltamivir had no effect on mortality (RR=0.87, 95% CI 0.55 to 1.38). Ribavirin combined with interferon was also not effective in adults with MERS and associated with adverse reactions. Conclusions: There is no evidence showing the effectiveness of antiviral agents for children with COVID-19, and the clinical efficacy of existing antiviral agents is still uncertain. We do not suggest clinical routine use of antivirals for COVID-19 in children, with the exception of clinical trials. Keywords: Antiviral agents; children; COVID-19; meta-analysis; rapid review.
A systematic review of antibody mediated immunity to coronaviruses: antibody kinetics, correlates of protection, and association of antibody responses with severity of disease

The duration and nature of immunity generated in response to SARS-CoV-2 infection is unknown. Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARS-CoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The timescale of protection is a critical determinant of the future impact of the pathogen. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. The dynamics of immunity and nature of protection are relevant to discussions surrounding therapeutic use of convalescent sera as well as efforts to identify individuals with protective immunity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV-1, MERS-CoV and human endemic coronaviruses (HCoVs). We reviewed 1281 abstracts and identified 322 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While studies of SARS-CoV-2 are necessary to determine immune responses to it, evidence from other coronaviruses can provide clues and guide future research.
Estimating the fraction of unreported infections in epidemics with a known epicenter: An application to COVID-19

We develop an analytically tractable method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the U.S. during the first half of March 2020. Our method utilizes the covariation in initial reported infections across U.S. regions and the number of travelers to these regions from the epicenter, along with the results of an early randomized testing study in Iceland. Using our estimates of the number of unreported infections, which are substantially larger than the number of reported infections, we also provide estimates for the infection fatality rate using data on reported COVID-19 fatalities from U.S. counties.
Breastfeeding of infants born to mothers with COVID-19: a rapid review

Abstract Background: Existing recommendations on whether mothers with COVID-19 should continue breastfeeding are still conflicting. We aimed to conduct a rapid review of mother-to-child transmission of COVID-19 during breastfeeding. Methods: We systematically searched Medline, Embase, Web of Science, Cochrane library, China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang, and preprint articles up to March 2020. We included studies relevant to transmission through milk and respiratory droplets during breastfeeding of mothers with COVID-19, SARS, MERS and influenza. Two reviewers independently screened studies for eligibility, extracted data, assessed risk of bias and used GRADE to assess certainty of evidence. Results: A total of 4481 records were identified in our literature search. Six studies (five case reports and one case series) involving 58 mothers (16 mothers with COVID-19, 42 mothers with influenza) and their infants proved eligible. Five case reports showed that the viral nucleic acid tests for all thirteen collected samples of breast milk from mothers with COVID-19 were negative. A case series of 42 influenza infected postpartum mothers taking precautions (hand hygiene and wearing masks) before breastfeeding showed that no neonates were infected with influenza during one-month of follow-up. Conclusions: The current evidence indicates that SARS-CoV-2 viral nucleic acid has not been detected in breast milk. The benefits of breastfeeding may outweigh the risk of SARS-CoV-2 infection in infants. Mothers with COVID-19 should take appropriate precautions to reduce the risk of transmission via droplets and close contact during breastfeeding. Keywords: Breastfeeding; COVID-19; infant; mother-to-child transmission; rapid Review.
Improving Coronavirus (COVID-19) Diagnosis using Deep Transfer Learning

Background: Coronavirus disease (COVID-19) is an infectious disease caused by a new virus. Exponential growth is not only threatening lives, but also impacting businesses and disrupting travel around the world. Aim: The aim of this work is to develop an efficient diagnosis of COVID-19 disease by differentiating it from viral pneumonia, bacterial pneumonia and healthy cases using deep learning techniques. Method: In this work, we have used pre-trained knowledge to improve the diagnostic performance using transfer learning techniques and compared the performance different CNN architectures. Results: Evaluation results using K-fold (10) showed that we have achieved state of the art performance with overall accuracy of 98.75% on the perspective of CT and X-ray cases as a whole. Conclusion: Quantitative evaluation showed high accuracy for automatic diagnosis of COVID-19. Pre-trained deep learning models develop in this study could be used early screening of coronavirus, however it calls for extensive need to CT or X-rays dataset to develop a reliable application.
Public preferences for free-ranging domestic cat (Felis catus) management options

Debate has occurred in recent years regarding the control of cat (Felis catus) populations. We investigated attitudes of Texas AM attitudes about nuisance behaviors associated with cats, euthanasia, and cat overpopulation; preferred control method for cat populations in 6 locations; and expected outcomes of each control method. Preference of control method for cats on campus was influenced by respondents' sex, perception of nuisance, and expected outcome of each control method. While respon- dents in this study recognized the predatory impact of cats on wildlife species in natural areas and on campus, they did not believe the cat's exotic status or its predation on wildlife was a legitimate reason for controlling population numbers.
Respiratory Physiology & Neurobiology

In the present study we analyze the epidemiological data of COVID-19 of Tibet and high-altitude regions of Bolivia and Ecuador, and compare to lowland data, to test the hypothesis that high-altitude inhabitants (+2,500 m above sea-level) are less susceptible to develop severe adverse e ﬀ ects in acute SARS-CoV-2 virus infection. Analysis of available epidemiological data suggest that physiological acclimatization/adaptation that counter-balance the hypoxic environment in high-altitude may protect from severe impact of acute SARS-CoV-2 virus infection. Potential underlying mechanisms such as: (i) a compromised half-live of the virus caused by the high-altitude environment, and (ii) a hypoxia mediated down regulation of angiotensin-converting enzyme 2 (ACE2), which is the main binding target of SARS-CoV-2 virus in the pulmonary epithelium are discussed.
Apolipoprotein E and Carotid Artery Atherosclerosis

Background and Purpose —Carotid artery atherosclerosis is a strong predictor for future stroke. It is yet unclear whether the apolipoprotein E polymorphism ( APOE) is related to atherosclerosis in the carotid arteries. The aim of the present study was to investigate the role of APOE in carotid artery atherosclerosis. Methods—A population-based cross-sectional study was performed on 5401 subjects. Atherosclerosis was noninvasively assessed by the common carotid artery intima-media wall thickness and the presence of plaques in the carotid arteries. The relationship of the 6APOE genotypes with these 2 indicators was studied with linear and logistic regression analysis, respectively, with adjustments for age and sex. Results—Carriers of theE2E3genotype had a thinner intima-media wall thickness (mean difference, 20.02 mm; 95% CI, 20.03 to20.01 mm) and fewer plaques (odds ratio for .3 plaques at 6 sites, 0.6; 95% CI, 0.4 to 0.8) than the most common group,E3E3. The E4E4 group had slightly more atherosclerosis, but this was not statistically significant. Adjusting for the level of the apolipoprotein E protein (apoE) in serum or total or HDL cholesterol did not essentially change these findings. Conclusions—Our results suggest that APOE*4 is not an important risk factor for carotid artery atherosclerosis. The inverse relationship of E2E3with carotid artery atherosclerosis seems to be independent of serum apoE and total and HDL cholesterol levels. However, the low frequency, together with the small effects, implies that any protective effect of E2E3on carotid artery atherosclerosis is limited. (Stroke. 2001;32:1947-1952.)
Factors that influence the decision regarding hormone replacement therapy in postmenopausal women

Cardiovascular disease is the leading cause of death in women in the United States today. Prior to menopause women have lower rates of heart disease than men; however, after menopause a woman's risk for heart disease rises dramatically. This is thought to be due the ovaries' decreased production of estradiol, but the mechanisms for this effect have not been fully elucidated. The need exists to investigate the impact of healthy lifestyles on attenuating the risk of cardiovascular disease in women as they age. The majority of research on hormone replacement therapy (HRT) has focused on the biomedical model suggesting that menopause reflects an estrogen "deficiency" and is treatable by pharmaceutical intervention. Little information is available that views menopause from a broader perspective which includes psychological and social factors. This research tested the hypothesis that postmenopausal women who practice positive lifestyle interventions, such as health supporting diets and regular exercise, will demonstrate positive biological, social and psychological outcomes independent of HRT. Seventy healthy postmenopausal women, aged 48-66, who had experienced a surgical or natural menopause were categorized into one of three groups: (1) no hormone replacement therapy (n = 36); (2) estrogen only (n = 11); and (3) estrogen and progestin (n = 23). Subjects donated a fasting blood sample and completed a comprehensive lifestyle and medical questionnaire that gathered information regarding health, menopause, decision making, self-esteem, and mood states. Subjects also completed a food frequency and three-day food diary. Anthropometric measurements were performed to determine body mass index and waist hip ratios. Biological assays of collected blood samples included estradiol and progesterone concentrations, lipid profiles, serum beta-carotene and vitamin E in total serum and in LDL, total antioxidants and the resistance of LDL to oxidation. Results indicated that lifestyle factors including quality of dietary intake, duration and intensity of exercise, and body weight may be better predictors of disease risk than use of HRT in postmenopausal women. Results suggest that, regardless of hormone use, positive lifestyle interventions will provide improved quality of life in women as they age.