bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coincidence of COVID-19 Infection and Smell—Taste Perception Disorders
Authors: Cetinkaya Erdem Atalay 
Published: May 2020

Abstract
Many reports by physicians and patients during the 2019 to 2020 pandemic indicate that COVID-19 is associated with elevated levels of odor and taste perception disorders (anosmia, hyposmia, ageusia, and/or dysgeusia). Recent increase in olfactory dysfunction in patients referred to ear nose and throat clinics and COVID-19 infection at the same time encouraged us to examine anosmic/hyposmic patients to establish any association between these signs. It has been shown that the COVID-19 virus exploits the uses angiotensin-converting enzyme 2 receptor to obtain cell entry. This result increases the interest to examine the expression of angiotensin-converting enzyme 2 in neurological tissue, and to assess the possible contribution of damage. This mini review provides fundamental knowledge on coincidence of COVID-19 infection and smell—taste perception disorders from an objective perspective.
Preliminary Experience With Inertial Movement Technology to Characterize Endotracheal Intubation Kinematics
Authors: Carlson Jestin N. , Cho Sohyung , Ohu Ikechukwu P. N. , Griffin Russell E. , Ko Hoo Sang , Lim Chiho , Wang Henry E. 
Published: May 2020

Background
Endotracheal intubation (ETI) is an important emergency intervention. Only limited data describe ETI skill acquisition and often use bulky technology, not easily transitioned to the clinical setting. In this study, we used small, portable inertial detection technology to characterize intubation kinematic differences between experienced and novice intubators.

Methods
We performed a prospective study including novice (<10 prior clinical ETI) and experienced (>100 clinical ETI) emergency providers. We tracked upper extremity motion with roll, pitch, and yaw using inertial measurement units (IMU) placed on the bilateral hands and wrists of the intubator. Subject performed 6 simulated emergency intubations on a mannequin. Using machine learning algorithms, we determined the motions that best discriminated experienced and novice providers.

Results
We included data on 12 novice and 5 experienced providers. Four machine learning algorithms (artificial neural network, support vector machine, decision tree, and K-nearest neighbor search) were applied. Artificial neural network had the greatest accuracy (95% confidence interval) for discriminating between novice and experienced providers (91.17%, 90.8%–91.5%) and was the most parsimonious of the tested algorithms. Using artificial neural network, information from 5 movement features (right hand, roll amplitude; right hand, pitch amplitude; right hand, yaw standard deviation; left hand, yaw standard deviation; left hand, pitch frequency of peak amplitude) was able discriminated experienced from novice providers.

Conclusions
Novice and experienced providers have different ETI movement patterns and can be distinguished by 5 specific movements. Inertial detection technology can be used to characterize the kinematics of emergency airway management.
Lasting Symptoms After Esophageal Resection (LASER)
Authors: Markar Sheraz R. , Zaninotto Giovanni , Castoro Carlo , Johar Asif , Lagergren Pernilla , Elliott Jessie A. , Gisbertz Suzanne S. , Mariette Christophe , Alfieri Rita , Huddy Jeremy , Sounderajah Viknesh , Pinto Eleonora , Scarpa Marco , Klevebro Fredrik , Sunde Berit , Murphy Conor F. , Greene Christine , Ravi Narayanasamy , Piessen Guillaume , Brenkman Hylke , Ruurda Jelle P. , Van Hillegersberg Richard , Lagarde Sjoerd , Wijnhoven Bas , Pera Manuel , Roig José , Castro Sandra , Matthijsen Robert , Findlay John , Antonowicz Stefan , Maynard Nick , McCormack Orla , Ariyarathenam Arun , Sanders Grant , Cheong Edward , Jaunoo Shameen , Allum William , Van Lanschot Jan , Nilsson Magnus , Reynolds John V. , van Berge Henegouwen Mark I. , Hanna George B. 
Published: May 2020

Objective:
To identify the most prevalent symptoms and those with greatest impact upon health-related quality of life (HRQOL) among esophageal cancer survivors.

Background:
Long-term symptom burden after esophagectomy, and associations with HRQOL, are poorly understood.

Patients and Methods:
Between 2010 and 2016, patients from 20 European Centers who underwent esophageal cancer surgery, and were disease-free at least 1 year postoperatively were asked to complete LASER, EORTC-QLQ-C30, and QLQ-OG25 questionnaires. Specific symptom questionnaire items that were associated with poor HRQOL as identified by EORTC QLQ-C30 and QLQ-OG25 were identified by multivariable regression analysis and combined to form a tool.

Results:
A total of 876 of 1081 invited patients responded to the questionnaire, giving a response rate of 81%. Of these, 66.9% stated in the last 6 months they had symptoms associated with their esophagectomy. Ongoing weight loss was reported by 10.4% of patients, and only 13.8% returned to work with the same activities.
Three LASER symptoms were correlated with poor HRQOL on multivariable analysis; pain on scars on chest (odds ratio (OR) 1.27; 95% CI 0.97–1.65), low mood (OR 1.42; 95% CI 1.15–1.77) and reduced energy or activity tolerance (OR 1.37; 95% CI 1.18–1.59). The areas under the curves for the development and validation datasets were 0.81 ± 0.02 and 0.82 ± 0.09 respectively.

Conclusion:
Two-thirds of patients experience significant symptoms more than 1 year after surgery. The 3 key symptoms associated with poor HRQOL identified in this study should be further validated, and could be used in clinical practice to identify patients who require increased support.
World vaping update
Authors: Striley Catherine W. , Nutley Sara K. 
Published: May 2020

Purpose of review
Although death and injury related to e-cigarette use and vaping products has decreased since the peak in 2019, concern over the popularity of electronic nicotine delivery systems (ENDS – a term which includes vape pens, electronic or e-cigarettes, and products that produce vapor for inhaling rather than combusting to produce smoke) continues. ENDS are used as an aid to quit smoking and for harm reduction.

Recent findings
This review covers peer-reviewed literature from January 2019 through February 2020 on vaping (the process of using ENDS). Prevalence, risk factors for use, and health risks and benefits from use predominated. Policy articles, commentaries and editorials were excluded from review. E-cigarette or vaping product use-associated lung injury (EVALI)-related injury and death were in the news and literature this year. Because most EVALI-related injury and death occurred among young people who had vaped tetrahydrocannabinol (THC), data from the Healthy Minds (United States) study are reviewed to consider variation in risk factors for vaping THC compared with nicotine.

Summary
Findings provide up-to-date information on vaping as a way to consume a drug, whether THC or nicotine. Harm reduction benefits were shown in a year-long follow-up of smoking cessation; harms continue to accumulate, including from passive consumption.
A radiomics approach to artificial intelligence in echocardiography: Predicting post-operative right ventricular failure
Authors: Shad Rohan , Quach Nicolas , Fong Robyn , Langlotz Curt P. , Kong Sandra , Kasinpila Patpilai , Amsallem Myriam , Haddad Francois , Shudo Yasuhiro , Woo Y. Joseph , Teuteberg Jeffrey , Hiesinger William 
Published: May 2020

AbstractIn this study, we describe a novel ‘radiomics’ approach to an echocardiography artificial intelligence system that enables the extraction of hundreds of thousands of motion parameters per echocardiography video. We apply this AI system to the clinical problem of predicting post-operative right ventricular failure (RV failure) in heart failure patients receiving implantable circulatory life support systems. Post-operative RV failure is the single largest contributor to short-term mortality in patients with left ventricular assist devices (LVAD); yet predicting which patient is at risk of developing this complication in the pre-operative setting, has remained beyond the abilities of experts in the field. We report results on testing datasets using a standard 10-fold cross validation. The AUC for the AI system trained using the Stanford LVAD dataset was 0.860 (95% CI 0.815-0.905; n = 290 patients) using pre-operative echocardiograms alone. We further show that our system outperforms board certified clinicians equipped with both contemporary risk scores (AUC 0.502 - 0.584) and independently measured echocardiographic metrics (0.519 – 0.598).
Psychological Distress Among People Losing Work During the COVID-19 Pandemic in Australia
Authors: Collie Alex , Sheehan Luke , Vreden Caryn van , Grant Genevieve , Whiteford Peter , Petrie Dennis , Sim Malcolm R 
Published: May 2020

AbstractIntroductionThis study estimated the extent of psychological distress among people losing work during the coronavirus disease of 2019 (COVID-19) pandemic in Australia, and examined associations between distress, nature of work loss and degree of social interaction.MethodsData were from a baseline online survey of an inception cohort recruited in the weeks following the introduction of physical distancing and movement restrictions to contain the spread of COVID-19 in Australia. These restrictions resulted in widespread unemployment and working hour reduction. Psychological distress was measured using the Kessler-6 scale. Data on nature of work loss, social interactions, demographic, job and occupational characteristics were also collected. Regression modelling was conducted to determine the relationship between work loss, social interactions and psychological distress, accounting for confounders.ResultsAmong the 551 study participants 31% reported severe psychological distress, 35% in those with job loss and 28% in those still employed but working less. Those who had significantly greater odds of high psychological distress were younger, female, had lost their job and had lower social interactions. The relationship between job loss and distress became non-significant when financial stress, and occupation were included in the regression model, but the protective effect of higher social interactions remained significant.DiscussionThere was a high prevalence of psychological distress in people losing work during the coronavirus pandemic. Age, gender, job loss and social interactions were strongly associated with distress. Interventions that promote social interaction may help to reduce distress during among people losing work during the COVID-19 pandemic.
Predicted success of prophylactic antiviral therapy to block or delay SARS-CoV-2 infection depends on the drug’s mechanism of action
Authors: Czuppon Peter , Débarre Florence , Gonçalves Antonio , Tenaillon Olivier , Perelson Alan S. , Guedj Jérémie , Blanquart François 
Published: May 2020

AbstractRepurposed drugs that are immediately available and safe to use constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we find that a critical efficacy above 87% is needed to block viral establishment. This can be improved by combination therapy. Below the critical efficacy, establishment of infection can sometimes be prevented, most effectively with drugs blocking viral entry into cells or enhancing viral clearance. Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. This delay flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.
Systematic Review and Meta-analysis of the Effectiveness and Safety of Hydroxychloroquine in COVID-19
Authors: Yang Tzu-Han , Chou Chian-Yin , Yang Yi-Fan , Yang Yi-Ping , Chien Chian-Shiu , Yarmishyn Aliaksandr A. , Yang Tzu-Ying , Chiou Shih-Hwa , Chang Yuh-Lih 
Published: May 2020

AbstractBackgroundsSince COVID-19 outbreak, various agents have been tested but no proven effective therapies have been identified. This has led to a lot of controversies among associated researches. Hence, in order to address the issue of using hydroxychloroquine in treating COVID-19 patients, we conducted a systematic review and meta-analysis.MethodsA thorough search was carried out to find relevant studies in MEDLINE, medRxiv, PubMed, Cochrane Database, China Academic Journals Full-text Database and Web of Science. Two investigators independently reviewed 274 abstracts and 23 articles. The trials which evaluated hydroxychloroquine for treatment of COVID-19 were included for this systematic review. Two investigators assessed quality of the studies and data extraction was done by one reviewer and cross checked by the other.ResultsFive trials involving 677 patients were included while conducting the meta-analysis. Compared with the control group, hydroxychloroquine with or without azithromycin showed benefits in positive-to-negative conversion of SARS-CoV-2 (odds ratio [OR], 1.95 [95% CI,0.19 to 19.73] and a reduction in progression rate (OR, 0.89 [95% CI, 0.58 to 1.37]), but without demonstrating any statistical significance. This systematic review has also suggested a possible synergistic effect of the combination therapy which included hydroxychloroquine and azithromycin. However, the use of hydroxychloroquine alone was associated with increased mortality in COVID-19 patients.ConclusionThe use of hydroxychloroquine with or without azithromycin for treatment of COVID-19 patients, seems to be effective. The combination of hydroxychloroquine and azithromycin has shown synergic effects. However, mortality rate was increased when the treatment was conducted with hydroxychloroquine.
Remdesivir in treatment of COVID-19: A systematic benefit-risk assessment
Authors: Davies Miranda , Osborne Vicki , Lane Samantha , Roy Debabrata , Dhanda Sandeep , Evans Alison , Shakir Saad 
Published: May 2020

AbstractBackgroundThere is a need to identify effective, safe treatments for COVID-19 (coronavirus disease) rapidly, given the current, ongoing pandemic. A systematic benefit-risk assessment was designed and conducted to strengthen the ongoing understanding of the benefit-risk balance for remdesivir in COVID-19 treatment by using a structured method which uses all available data.MethodsThe Benefit-Risk Action Team (BRAT) framework was used to assess the overall benefit-risk of the use of remdesivir as a treatment for COVID-19 compared to standard of care, placebo or other treatments. We searched PubMed,Google Scholar and government agency websites to identify literature reporting clinical outcomes in patients taking remdesivir for COVID-19. A value tree was constructed and key benefits and risks were ranked by two clinicians in order of considered importance.ResultsSeveral key benefits and risks for use of remdesivir in COVID-19 compared to placebo have been identified. In one trial, the benefit of time to clinical improvement was not statistically significant (21 vs 23 days, HR=1.23, 95% CI: 0.87, 1.75), although the study was underpowered. In another trial, a shorter time to recovery in patients treated with remdesivir was observed (11 vs 15 days), with non-significant reduced mortality risk (8% vs 12%). Risk data were only available from one trial. This trial reported fewer serious adverse events in patients taking remdesivir (18%) comparted to the placebo group (26%), however more patients in the remdesivir group discontinued treatment as a result of an adverse event compared to those patients receiving placebo (12% vs 5%).ConclusionsPreliminary clinical trial results suggest a favourable benefit-risk profile for remdesivir compared to placebo, however there is limited safety data available at the current time. The current framework summarises the key anticipated benefits and risks for which further data are needed. Ongoing clinical trial data can be incorporated into the framework when available to provide an updated benefit-risk assessment.
Systematic benefit-risk assessment for the use of chloroquine or hydroxychloroquine as a treatment for COVID-19: Establishing a dynamic framework for rapid decision-making
Authors: Osborne Vicki , Davies Miranda , Dhanda Sandeep , Roy Debabrata , Lane Samantha , Evans Alison , Shakir Saad 
Published: May 2020

AbstractObjectivesGiven the current pandemic, there is an urgent need to identify effective, safe treatments for COVID-19 (coronavirus disease). A systematic benefit-risk assessment was designed and conducted to strengthen the ongoing monitoring of the benefit-risk balance for chloroquine (CQ) and hydroxychloroquine (HCQ) in COVID-19 treatment.MethodsThe overall benefit-risk of the use of chloroquine or hydroxychloroquine as a treatment for COVID-19 compared to standard of care, placebo or other treatments was assessed using the Benefit-Risk Action Team (BRAT) framework. We searched PubMed and Google Scholar to identify literature reporting clinical outcomes in patients taking chloroquine or hydroxychloroquine for COVID-19. A value tree was constructed and key benefits and risks were ranked by two clinicians in order of considered importance.ResultsSeveral potential key benefits and risks were identified for use of hydroxychloroquine or chloroquine in COVID-19 treatment. Currently available results did not show an improvement in mortality risk; Cox proportional hazard ratio (HR) for death between patients who received HCQ alone vs. neither hydroxychloroquine or azithromycin was 1.08 (95% CI 0.63-1.85). A further study compared the incidence of intubation or death (composite outcome) in a time to event analysis between patients who received HCQ vs. those patients who did not (adjusted Cox proportional HR 1.00 (95% CI 0.76-1.32)). Risk of cardiac arrest, abnormal electrocardiogram (ECG) and QT prolongation was greater among patients taking HCQ (with or without azithromycin) compared to standard of care in the same study.ConclusionsOverall, based on the available data there does not appear to be a favourable benefit-risk profile for chloroquine or hydroxychloroquine compared to standard of care in treatment of severe COVID-19. As further data from clinical trials and real world use on these benefits and risks becomes available, this can be incorporated into the framework for an ongoing benefit-risk assessment.
Automated recognition of ultrasound cardiac views based on deep learning with graph constraint
Authors: Gao Yanhua , Zhu Yuan , Liu Bo , Hu Yue , Guo Youmin 
Published: May 2020

ObjectiveIn Transthoracic echocardiographic (TTE) examination, it is essential to identify the cardiac views accurately. Computer-aided recognition is expected to improve the accuracy of the TTE examination.MethodsThis paper proposes a new method for automatic recognition of cardiac views based on deep learning, including three strategies. First, A spatial transform network is performed to learn cardiac shape changes during the cardiac cycle, which reduces intra-class variability. Second, a channel attention mechanism is introduced to adaptively recalibrates channel-wise feature responses. Finally, unlike conventional deep learning methods, which learned each input images individually, the structured signals are applied by a graph of similarities among images. These signals are transformed into the graph-based image embedding, which act as unsupervised regularization constraints to improve the generalization accuracy.ResultsThe proposed method was trained and tested in 171792 cardiac images from 584 subjects. Compared with the known result of the state of the art, the overall accuracy of the proposed method on cardiac image classification is 99.10% vs. 91.7%, and the mean AUC is 99.36%. Moreover, the overall accuracy is 98.15%, and the mean AUC is 98.96% on an independent test set with 34211 images from 100 subjects.ConclusionThe method of this paper achieved the results of the state of the art, which is expected to be an automated recognition tool for cardiac views recognition. The work confirms the potential of deep learning on ultrasound medicine.
Calcification of abdominal aorta is an underappreciated cardiovascular disease risk factor
Authors: Sethi Anurag , Taylor Leland , Ruby J Graham , Venkataraman Jagadish , Cule Madeleine , Melamud Eugene 
Published: May 2020

AbstractBackgroundCalcification of the abdominal artery is an important contributor to cardiovascular disease in diabetic and chronic kidney disease (CKD) populations. However, prevalence of the pathology, risk factors, and long term disease outcomes in a general population have not been systematically analyzed.MethodWe developed machine learning models to quantify levels of abdominal aortic calcification (AAC) in 29,957 whole body dual-energy X-ray absorptiometry (DEXA) scans from the UK Biobank cohort. Using regression techniques we associated severity of calcification across a wide range of physiological parameters, clinical biomarkers, and environmental risk factors (406 in total). We performed a common variant genetic association study spanning 9,572,557 single-nucleotide polymorphisms to identify genetic loci relevant to AAC. We evaluated the prognostic value of AAC across 151 disease classes using Cox proportional hazard models. We further examined an epidemiological model of calcification on cardiovascular morbidity with and without LDL interactions.FindingsWe find evidence for AAC in >10.4% of the cohort despite low prevalence of diabetes (2.5%) and CKD (0.5%). Increased level of AAC is a strong prognostic indicator of cardiovascular outcomes for stenosis of precerebral arteries (HR~1.5), Myocardial Infarction (HR~1.5), & Ischemic Heart Disease (HR~1.33). We find that AAC is genetically correlated with cardiovascular-related traits and that the genetic signals are enriched in vascular and adipose tissue. We report three loci associated with AAC, with the strongest association occuring at theTWIST1/HDAC9locus (beta=0.078, p-value=1.4e-11) in a region also associated with coronary artery disease. Surprisingly, we find that elevated but still within clinically normal levels of serum phosphate and glycated hemoglobin are linked to increased vascular calcification. Furthermore, we show AAC arises in the absence of hypercholesterolemia. By our estimate, AAC is an LDL-independent risk factor for cardiovascular outcomes, with risk similar to elevated LDL.DataThis research has been conducted using the UK Biobank Resource.
Quantitative COVID-19 infectiousness estimate correlating with viral shedding and culturability suggests 68% pre-symptomatic transmissions
Authors: Prakash Meher K. 
Published: May 2020

AbstractA person clinically diagnosed with COVID 19 can infect others for several days before and after the onset of symptoms. At the epidemiological level, this information on how infectious someone is lies embedded implicitly in the serial interval data. Other clinical indicators of infectiousness based on the temporal kinetics of the viral shedding from the nasopharyngeal swabs and sputum show the former decaying weeks sooner than the latter. In this work, we attempt to provide a better quantitative estimate for the temporal infectiousness profile using serial interval data from a combined 1251 individuals reported in the literature. We show that the infectiousness profile which we calculate correlates well with the viral shedding kinetics from nasopharyngeal swabs (ρ=0.97, p=0.00) and culturability (ρ=0.83, p=0.01). The profile suggests that a 68.4% (95% CI: 67.0-69.7%) of the infections are caused by infections before the symptoms appear, which is a much stronger pre-symptomatic influence than what was predicted in the literature 44% (95% CI: 25-69%) using serial data from 77 individuals.