bluuebunny/crossref_metadata_2025 huggingface dataset:
Essential Workers’ COVID-19 Vaccine Hesitancy, Misinformation and Informational Needs in the Republic of North Macedonia
Authors: Fucaloro S. , Yacoubian V. , Piltch-Loeb R. , Harriman N. , Burmaz T. , Hadji-Janev M. , Savoia E.
Published: December 2021

Introduction

The COVID-19 pandemic is a global health crisis that as of December 2021 has resulted in the death of over 5.2 million people. Despite the unprecedented development and distribution of vaccines, hesitancy to take the vaccine remains a wide-spread public health challenge, especially in Eastern European countries. In this study we focus on a sample of essential workers living in the Republic of North Macedonia to: 1) Describe rates of vaccine acceptance, risk perception and sources of COVID-19 information, 2) Explore predictors of vaccine hesitancy, and 3) Describe informational needs of hesitant and non-hesitant workers.

Methods

Descriptive statistics were used to present frequencies of vaccine acceptance. Logistic regression was used to explore predictors of vaccine hesitancy based on sociodemographic characteristics, hesitancy to take other vaccines in the past, previous diagnosis of COVID-19, and individual risk perception of getting COVID-19. Chi square analysis was used to compare differences in informational needs between hesitant and non-hesitant individuals across socio-demographic groups.

Results

From a sample of 1003 individuals, 439 (44%) reported that they were very likely to get the vaccine, and the rest (66%) reported some level of hesitancy. Older age, Albanian ethnicity, post-secondary school education, previous diagnosis of COVID-19, previous vaccine acceptance of other vaccines, and increased risk perception of COVID-19 infection were all found to be negatively associated with vaccine hesitancy. In particular hesitant individuals, compared to the non-hesitant, wanted to have more information and reassurance that all main international agencies (i.e. FDA, WHO, EMA) were all in accordance in recommending the vaccine and that they would be free to choose if getting the vaccine or not without consequences (p<0.01).
Saliva swabs are the preferred sample for Omicron detection
Authors: Marais Gert , Hsiao Nei-yuan , Iranzadeh Arash , Doolabh Deelan , Enoch Annabel , Chu Chun-yat , Williamson Carolyn , Brink Adrian , Hardie Diana
Published: December 2021

The Omicron variant is characterised by more than 50 distinct mutations, the majority of which are located in the spike protein. The implications of these mutations for disease transmission, tissue tropism and diagnostic testing are still to be determined. We evaluated the relative performance of saliva and mid-turbinate swabs as RT-PCR samples for the Delta and Omicron variants. The positive percent agreement (PPA) of saliva swabs and mid-turbinate swabs to a composite standard was 71% (95% CI: 53-84%) and 100% (95% CI: 89-100%), respectively, for the Delta variant. However, for the Omicron variant saliva and mid-turbinate swabs had a 100% (95% CI: 90-100%) and 86% (95% CI: 71-94%) PPA, respectively. This finding supports ex-vivo data of altered tissue tropism from other labs for the Omicron variant. Reassessment of the diagnostic testing standard-of-care may be required as the Omicron variant become the dominant variant worldwide.
Virtual Exam for Parkinson’s Disease Enables Frequent and Reliable Remote Measurements of Motor Function
Authors: Burq Maximilien , Rainaldi Erin , Ho King Chung , Chen Chen , Bloem Bastiaan R. , Evers Luc J.W. , Helmich Rick C. , Myers Lance , Marks William , Kapur Ritu
Published: December 2021

Sensor-based remote monitoring could help us better track Parkinson’s disease (PD) progression, and measure patients’ response to putative disease-modifying therapeutic interventions. To be useful, the remotely-collected measurements should be valid, reliable and sensitive to change, and people with PD must engage with the technology.

We developed a smartwatch-based active assessment that enables unsupervised measurement of motor signs of PD. 388 study participants with early-stage PD (Personalized Parkinson Project, 64% men, average age 63 years) wore a smartwatch for a median of 390 days, allowing for continuous passive monitoring. Participants performed unsupervised motor tasks both in the clinic (once) and remotely (twice weekly for one year). Dropout rate was 2% at the end of follow-up. Median wear-time was 21.1 hours/day, and 59% of per-protocol remote assessments were completed.

In-clinic performance of the virtual exam verified that most participants correctly followed watch-based instructions. Analytical validation was established for in-clinic measurements, which showed moderate-to-strong correlations with consensus MDS-UPDRS Part III ratings for rest tremor (ρ=0.70), bradykinesia (ρ=-0.62), and gait (ρ=-0.46). Test-retest reliability of remote measurements, aggregated monthly, was good-to-excellent (ICC: 0.75 - 0.96). Remote measurements were sensitive to the known effects of dopaminergic medication (on vs off Cohen’s d: 0.19 - 0.54). Of note, in-clinic assessments often did not reflect the patients’ typical status at home.

This demonstrates the feasibility of using smartwatch-based unsupervised active tests, and establishes the analytical validity of associated digital measurements. Weekly measurements can create a more complete picture of patient functioning by providing a real-life distribution of disease severity, as it fluctuates over time. Sensitivity to medication-induced change, together with the improvement in test-retest reliability from temporal aggregation implies that these methods could help reduce sample sizes needed to demonstrate a response to therapeutic intervention or disease progression.
Infrared spectroscopy enables rapid, robust, portable COVID-19 saliva screening based on pathophysiological response to SARS-CoV-2
Authors: Kazmer Seth T. , Hartel Gunter , Robinson Harley , Richards Renee S. , Yan Kexin , Van Hal Sebastiaan J. , Chan Raymond , Hind Andrew , Bradley David , Zieschang Fabian , Rawle Daniel J. , Le Thuy T. , Reid David W. , Suhrbier Andreas , Hill Michelle M
Published: December 2021

Fourier-transform infrared (FTIR) spectroscopy provides a (bio)chemical snapshot of the sample, and was recently proposed for COVID-19 saliva screening in proof-of-concept cohort studies. As a step towards translation of this technology, we conducted controlled validation experiments in multiple biological systems. SARS-CoV-2 or UV-inactivated SARS-CoV-2 were used to infect Vero E6 cells in vitro, and K18-hACE2 mice in vivo. Potentially infectious culture supernatant or mouse oral lavage samples were treated with ethanol or Trizol to 75% (v/v) for attenuated total reflectance (ATR)-FTIR spectroscopy, or RT-PCR, respectively. The control condition, UV-inactivated SARS-CoV-2 elicited strong biochemical changes in culture supernatant/oral lavage despite lack of replication determined by RT-PCR or cell culture infectious dose 50%. Crucially, we show that active SARS-CoV-2 infection induced additional FTIR signals over the UV-inactivated SARS-CoV-2 infection, which correspond to innate immune response, aggregated proteins, and RNA. For human patient cohort prediction, we achieved high sensitivity of 93.48% on leave-on-out cross validation (n=104 participants) for predicting COVID-19 positivity using a partial least squares discriminant analysis model, in agreement with recent studies. However, COVID-19 patients negative on follow-up (RT-PCR on day of saliva sampling) were poorly predicted in this model. Importantly, COVID-19 vaccination did not lead to mis-classification of COVID-19 negatives. Meta-analysis revealed SARS-CoV-2 induced increase in Amide II band in all arms of this study and recent studies, indicative of altered β-sheet structures in secreted proteins. In conclusion, ATR-FTIR is a robust, simple, portable method for COVID-19 saliva screening based on detection of pathophysiological responses to SARS-CoV-2.
Diversity in antibody titer at an average of 87 days after the second dose of BNT162b2 mRNA coronavirus disease 2019 vaccine: data from a predominantly elderly population in a practice in Tokyo
Authors: Fuse-Nagase Yasuko , Nagase Mitsuo
Published: December 2021

It is very important for the elderly, who tend to have serious COVID-19 infection and high mortality rates, to maintain sufficient immunity. We reviewed the medical charts of predominantly elderly population to obtain the data on serum anti-SARS-CoV-2S antibody titer after complete vaccination with the BNT162b2 mRNA vaccine (two doses) and evaluated the background factors associated with the titer. We enrolled 230 participants (101 men and 129 women). Their average age was 71.9 (SD 12.5) years, and median was 72 years. The anti-SARS-CoV-2S antibody titer varied from 0.55 U/mL to 4920 U/mL. We found that the value of the titer varied widely. The value of the titer was negatively associated with age, alcohol consumption, time elapsed from second vaccine dose, and use of immunosuppressive medication. The result that the titer was negatively associated with aging suggests that the timing of additional shot should be carefully determined especially among elderly population.
Rapid and Durable Protection Against Marburg Virus with a Single-Shot ChAd3-MARV GP Vaccine
Authors: Hunegnaw Ruth , Honko Anna , Wang Lingshu , Carr Derick , Murray Tamar , Shi Wei , Dulan Caitlyn N. M. , Foulds Kathryn E. , Agans Krystle N. , Cross Robert W. , Geisbert Joan B. , Geisbert Thomas W. , Cheng Cheng , Ploquin Aurélie , Stanley Daphne A. , Nabel Gary J. , Sullivan Nancy J.
Published: December 2021

Marburg virus (MARV) causes a severe hemorrhagic fever disease in primates with mortality rates in humans up to 90%. Since 2018, MARV has been identified as a priority pathogen by the WHO, needing urgent research and development of countermeasures due to the high public health risk it poses. Recently, the first case of MARV in West Africa underscored the significant outbreak potential of this virus. The potential for cross border spread as had occurred during the Ebola 2014-2016 outbreak illustrates the critical need for Marburg vaccines. To support regulatory approval of the ChAd3-Marburg vaccine that has completed Phase I trials, we show that a non-replicating chimpanzee-derived adenovirus vector with a demonstrated safety profile in humans (ChAd3) protected against a uniformly lethal challenge with Marburg-Angola. Protective immunity was achieved within 7 days of vaccination and was maintained through one year post vaccination, antigen-specific antibodies were a significant immune correlate of protection in the acute challenge model (p=0.0003), and predictive for protection with an AUC = 0.88. These results demonstrate that a single-shot ChAd3 MARV vaccine generated a protective immune response that was both rapid and durable with a significant immune correlate of protection that will support advanced clinical development.

One Sentence Summary

A single-shot of non-replicating ChAd3-MARV vaccine demonstrated both rapid (within 1 week) and durable (12 months) protection against lethal Marburg virus infection in macaques.
A Pattern Recognition Diagnostic Model to Restore and Emulate Knee Mobility
Authors: Hollinger David S. , Gulfam Muhammad , Packer Sadaira , Sukmanto Bayu
Published: December 2021

Electromyography (EMG) is an electrical voltage potential linked to muscle contraction, resulting in human joint motion, such as knee flexion. Knee injuries, such as knee osteoarthritis (KOA), disrupt functional mobility of the knee joint and subsequently atrophy the muscles controlling knee movement during activities of daily living (ADL). Consequently, weakened muscles exhibiting deteriorated EMG signal fidelity are hypothesized to have discernible signal patterns from a healthy individual’s EMG signals. Pattern recognition algorithms are useful for mapping a set of complex inputs (EMG signals and knee angles) to classify knee health status (injured vs. healthy). A secondary outcome is to predict future knee angles from previous input signals to inform a robotic knee exoskeleton to apply real-time torque assistance to a patient during ADL. A Decision Tree Classifier, Random Forest, Naive Bayes, and a Feed Forward Neural Network (Fully Connected) were used for binary classification (healthy vs. injured). Partial Least Squares Regression, Decision Tree Regressor, and XGBoost were used to predict future joint angles for the regression task (knee angle prediction). Overall, the Random Forest Classifier had the best overall classification performance. XGBoost and Decision Tree Regression performed the best among regression algorithms for predicting real-time angles during walking while Partial Least Squares Regression performed the best during the standing tasks. In summary, our Machine Learning methods are useful for assisting clinicians and patients during physical rehabilitation by providing quantitative insight into the patient’s neuromuscular control of the knee.
Effectiveness of BNT162b2 and mRNA-1273 Second Doses and Boosters for SARS-CoV-2 infection and SARS-CoV-2 Related Hospitalizations: A Statewide Report from the Minnesota Electronic Health Record Consortium
Authors: Drawz Paul E , DeSilva Malini , Bodurtha Peter , Benitez Gabriela Vazquez , Murray Anne , Chamberlain Alanna M , Dudley R Adams , Waring Stephen , Kharbanda Anupam B , Murphy Daniel , Muscoplat Miriam Halstead , Melendez Victor , Margolis Karen L , McFarling Lynn , Lupu Roxana , Winkelman Tyler N.A. , Johnson Steve
Published: December 2021

Using vaccine data combined with electronic health records, we report that mRNA boosters provide greater protection than a two-dose regimen against SARS-CoV-2 infection and related hospitalizations. The benefit of a booster was more evident in the elderly and those with comorbidities. These results support the case for COVID-19 boosters.
Echinacea as a Potential Force against Coronavirus Infections? A Mini-Review of Randomized Controlled Trials in Adults and Children
Authors: Simon Nicolussi , Karin Ardjomand-Woelkart , Rainer Stange , Giuseppe Gancitano , Peter Klein , Mercedes Ogal
Published: December 2021

Echinacea purpurea was shown to broadly inhibit coronaviruses and SARS-CoV-2 in vitro. This review discusses the available clinical evidence from randomized, blinded and controlled human studies. Two RCTs with results on enveloped viruses, respectively coronavirus infections during prevention treatment were detected. Incidence and/or viral loads were measured by RT-PCR and symptom severity was recorded. Jawad et al. (2012) collected nasopharyngeal swabs from adults (N=755) over 4 months of continuous prevention. Overall, 24 and 47 enveloped virus infections occurred, including 21 and 33 coronavirus detections [229E; HKU1; OC43] with Echinaforce® extract [2’400mg daily] and placebo, respectively (p=0.0114). Ogal et al. (2021) administered the same extract [1’200mg] or control for 4 months to children (4 – 12 years) (N=203). Echinacea reduced the incidence of enveloped virus infections from 47 to 29 (p=0.0038) whereas 11 and 13 coronavirus detections [229E, OC43, NL63] were counted (p>0.05). Respiratory symptoms during coronavirus infections were significantly lower with area-under-curve AUC=75.8 (+/-50.24) versus 27.1 (+/-21.27) score points (p=0.0036). Importantly, viral loads in nasal secretions were significantly reduced by 98.5%, with Ct-values 31.1 [95% CI 26.3; 35.9] versus 25.0 [95% CI 20.5; 29.5] (p = 0.0479). Results from clinical studies confirm the antiviral activity found for Echinacea in vitro, embracing enveloped respiratory pathogens and therefore coronaviruses as well. Substantiating results from a new completed study seems to extrapolate these effects to the prevention of SARS-CoV-2 infection. As hypothesized, the testified broad antiviral activity of Echinacea extract appears to be inclusive for SARS-CoV-2.
An aging focused unobtrusive and Privacy-Preserving Digital Behaviorome
Authors: Schütz Narayan , Knobel Samuel E.J. , Botros Angela , Single Michael , Pais Bruno , Santschi Valérie , Gatica-Perez Daniel , Buluschek Philipp , Urwyler Prabitha , Gerber Stephan M. , Müri Réne M. , Mosimann Urs , Saner Hugo , Nef Tobias
Published: December 2021

Abstract

Digital measures are increasingly used as objective health measures in remote-monitoring settings. In addition to their use in purely clinical research, such as in clinical trials, one promising application area for sensor-derived digital measures is in technology-assisted ageing and ageing-related research. In this context, digital measures may be used to measure the risk of certain adverse events such as falls, and also to provide novel research insights into ageing and ageing-related conditions, like cognitive impairment. While major emphasis has been placed on deriving one or more digital measures from wearable devices, a more holistic approach inspired by systems biology that leverages large, non-exhaustive sets of digital measures may prove highly beneficial. Such an approach would be useful if combined with modern big data approaches like machine learning. As such, extensive sets of digital measures, which may be referred to as digital behavioromes, could help characterise new phenotypes in deep phenotyping efforts. These measures could also assist in the discovery of novel digital biomarkers or in the creation of digital clinical outcome assessments. While clinical research into digital measures focuses primarily on measures derived from wearable devices, proven technology used for long-term remote monitoring of older adults is generally contactless, unobtrusive, and privacy-preserving. In this context, we introduce and describe a digital behaviorome: a large, non-exhaustive set of digital measures based entirely on contactless, unobtrusive, and privacy-preserving sensor technologies. We also demonstrate how such a behaviorome can be used to build digital clinical outcome assessments that are relevant to ageing and derived from machine learning. These outcomes included fall risk, frailty, mild cognitive impairment, and late-life depression. With the exception of late-life depression, all digital outcome assessments demonstrated a promising ability (ROC AUC≥0.7) to discriminate between positive and negative health outcomes, often in the range of comparable work with wearable devices. Finally, we highlight the possibility of using these digital behaviorome-based outcome assessments to discover novel potential digital biomarkers for each outcome. Here, we found reasonable contributors but also some potentially interesting new candidates regarding fall risk and mild cognitive impairment.
Population immunity to pre-Omicron and Omicron SARS-CoV-2 variants in US states and counties through December 1, 2021
Authors: Klaassen Fayette , Chitwood Melanie H. , Cohen Ted , Pitzer Virginia E. , Russi Marcus , Swartwood Nicole A. , Salomon Joshua A. , Menzies Nicolas A.
Published: December 2021

Prior infection and vaccination both contribute to population-level SARS-CoV-2 immunity. We used a Bayesian model to synthesize evidence and estimate population immunity to prevalent SARS-CoV-2 variants in the United States over the course of the epidemic until December 1, 2021, and how this changed with the introduction of the Omicron variant. We used daily SARS-CoV-2 infection estimates and vaccination coverage data for each US state and county. We estimated relative rates of vaccination conditional on previous infection status using the Census Bureau’s Household Pulse Survey. We used published evidence on natural and vaccine-induced immunity, including waning and immune escape. The estimated percentage of the US population with a history of SARS-CoV-2 infection or vaccination as of December 1, 2021, was 88.2% (95%CrI: 83.6%-93.5%), compared to 24.9% (95%CrI: 18.5%-34.1%) on January 1, 2021. State-level estimates for December 1, 2021, ranged between 76.9% (95%CrI: 67.6%-87.6%, West Virginia) and 94.4% (95%CrI: 91.2%-97.3%, New Mexico). Accounting for waning and immune escape, the effective protection against the Omicron variant on December 1, 2021, was 21.8% (95%CrI: 20.7%-23.4%) nationally and ranged between 14.4% (95%CrI: 13.2%-15.8%, West Virginia), to 26.4% (95%CrI: 25.3%-27.8%, Colorado). Effective protection against severe disease from Omicron was 61.2% (95%CrI: 59.1%-64.0%) nationally and ranged between 53.0% (95%CrI: 47.3%-60.0%, Vermont) and 65.8% (95%CrI: 64.9%-66.7%, Colorado). While over three-quarters of the US population had prior immunological exposure to SARS-CoV-2 via vaccination or infection on December 1, 2021, only a fifth of the population was estimated to have effective protection to infection with the immune-evading Omicron variant.

Significance

Both SARS-CoV-2 infection and COVID-19 vaccination contribute to population-level immunity against SARS-CoV-2. This study estimates the immunity and effective protection against future SARS-CoV-2 infection in each US state and county over 2020-2021. The estimated percentage of the US population with a history of SARS-CoV-2 infection or vaccination as of December 1, 2021, was 88.2% (95%CrI: 83.6%-93.5%). Accounting for waning and immune escape, protection against the Omicron variant was 21.8% (95%CrI: 20.7%-23.4%). Protection against infection with the Omicron variant ranged between 14.4% (95%CrI: 13.2%-15.8%%, West Virginia) and 26.4% (95%CrI: 25.3%-27.8%, Colorado) across US states. The introduction of the immune-evading Omicron variant resulted in an effective absolute increase of approximately 30 percentage points in the fraction of the population susceptible to infection.
Risk of myocarditis following sequential COVID-19 vaccinations by age and sex
Authors: Patone Martina , Mei Xue W , Handunnetthi Lahiru , Dixon Sharon , Zaccardi Francesco , Shankar-Hari Manu , Watkinson Peter , Khunti Kamlesh , Harnden Anthony , Coupland Carol AC , Channon Keith M. , Mills Nicholas L , Sheikh Aziz , Hippisley-Cox Julia
Published: December 2021

In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.

Funding

Health Data Research UK.
Sharp Increases in Drug Overdose Deaths Among High-School-Age Adolescents During the US COVID-19 Epidemic and Illicit Fentanyl Crisis
Authors: Friedman Joseph , Godvin Morgan , Shover Chelsea , Gone Joseph P. , Hansen Helena , Schriger David
Published: December 2021

Although overdose deaths in the US have increased exponentially for the past four decades, these shifts have historically affected adults, while pediatric overdose rates remained stable. However, this may be changing, given that the illicit drug supply has become increasingly hazardous in recent years, as illicitly-manufactured-fentanyls (IMFs) and other synthetic opioid and benzodiazepine analogues are increasingly sold as heroin and counterfeit prescription pills. We calculated drug overdose deaths per 100,000 population by 5-year age groups for the 2010-2021 period. For high-school-aged adolescents (age 14-18), we stratified rates by race/ethnicity, census region, associated substance, and ICD-10 cause-of-death intent categories. Adolescent overdose mortality saw a sharp increase between 2019 and 2020, from 2.35 per 100,000 to 4.58 per 100,000, representing a 94.3% increase, the largest percent increase of any 5-year age group. American Indian or Alaska Native (AIAN) adolescents, Latinx adolescents, and adolescents in the West census region were disproportionately affected, overdose death rates 2.15, 1.31, and 1.68 times the national average in 2021, respectively. Trends were driven by fatalities involving IMFs, which nearly tripled from 2019 to 2020, and represented 76.6% of adolescent overdose deaths in 2021. Sharp increases in adolescent drug overdose deaths, despite flat or declining drug use rates, and no increase in deaths from alcohol or most drugs, reinforce that rising fatalities are likely driven by an increasingly toxic, IMF-contaminated drug supply. Rising racial disparities in overdose require a prevention approach that ameliorates deep-seated social and economic inequalities as well as poor access to mental and physical healthcare and social services for AIAN and Latinx adolescents. Our results should also be understood in the context of rising rates of adolescent mental illness during the COVID-19 pandemic. These findings highlight the urgent need for accurate, harm-reduction-oriented education for early adolescents about the risks of an evolving drug supply, as well as greater access to naloxone and services that check drugs for the presence of IMFs.
Overlooked Trustworthiness of Explainability in Medical AI
Authors: Zhang Jiajin , Chao Hanqing , Kalra Mannudeep K. , Wang Ge , Yan Pingkun
Published: December 2021

While various methods have been proposed to explain AI models, the trustworthiness of the generated explanation received little examination. This paper reveals that such explanations could be vulnerable to subtle perturbations on the input and generate misleading results. On the public CheXpert dataset, we demonstrate that specially designed adversarial perturbations can easily tamper saliency maps towards the desired explanations while preserving the original model predictions. AI researchers, practitioners, and authoritative agencies in the medical domain should use caution when explaining AI models because such an explanation could be irrelevant, misleading, and even adversarially manipulated without changing the model output. AI researchers, practitioners, and authoritative agencies in the medical domain should use caution when explaining AI models because such an explanation could be irrelevant, misleading, and even adversarially manipulated without changing the model output.
Endoscopic findings in patients with persistent dyspepsia in a tertiary care hospital of south Punjab
Authors: Din Chaudhary Farooq Mohyud , Gul Muhammad Asif , Hameed Rizwan , Zaidi Yasir Abbas , Kanju Shehryar , Ilyas Muhammad , Zubair Muhammad , Umar Qasim , Altaf Syeda Manal , Tameez-ud-din Ahsan
Published: December 2021

Background

One of the most common clinical problem encountered by physicians in clinical practice is dyspepsia. This symptom has great impact on quality of life of patients. There are numerous causes of dyspepsia, organic as well as functional. Endoscopy is the diagnostic test of choice in these patients.

Aim

The aim of our study was to see the endoscopic findings in patients with persistent dyspepsia.

Methods

Retrospective analysis of data of patients who underwent Esophagogastroduodenoscopy (EGD) for persistent dyspepsia was collected and evaluated.

Results

There were 495 patients in our study, 244 females and 251 males, with a mean age of 41 years. Almost half of the patients belonged to 21-40 years age group. The most common endoscopic finding in patients with persistent dyspepsia was gastritis (n=219, 44.2%), followed by normal endoscopy (n= 94, 19%), incompetent lower esophageal sphincter (n=67, 13.5%), gastric malignancy (n=48, 9.7%). Ulcer disease was found in just 15 patients (3%).

Conclusion

Most common endoscopic finding in patients with persistent dyspepsia was gastritis followed by normal endoscopy.
The HUNT Study: a population-based cohort for genetic research
Authors: Brumpton Ben M. , Graham Sarah , Surakka Ida , Skogholt Anne Heidi , Løset Mari , Fritsche Lars G. , Wolford Brooke , Zhou Wei , Nielsen Jonas Bille , Holmen Oddgeir L. , Gabrielsen Maiken E. , Thomas Laurent , Bhatta Laxmi , Rasheed Humaira , Zhang He , Kang Hyun Min , Hornsby Whitney , Moksnes Marta R. , Coward Eivind , Melbye Mads , Giskeødegård Guro F. , Fenstad Jørn , Krokstad Steinar , Næss Marit , Langhammer Arnulf , Boehnke Michael , Abecasis Gonçalo R. , Åsvold Bjørn Olav , Hveem Kristian , Willer Cristen J.
Published: December 2021

The Trøndelag Health Study (HUNT) is a population-based cohort of ∼229,000 individuals recruited in four waves beginning in 1984 in Trøndelag County, Norway. ∼88,000 of these individuals have available genetic data from array genotyping. HUNT participants were recruited during 4 community-based recruitment waves and provided information on health-related behaviors, self-reported diagnoses, family history of disease, and underwent physical examinations. Linkage via the Norwegian personal identification number integrates digitized health care information from doctor visits and national health registries including death, cancer and prescription registries. Genome-wide association studies of HUNT participants have provided insights into the mechanism of cardiovascular, metabolic, osteoporotic and liver-related diseases, among others. Unique features of this cohort that facilitate research include nearly 40 years of longitudinal follow-up in a motivated and well-educated population, family data, comprehensive phenotyping, and broad availability of DNA, RNA, urine, fecal, plasma, and serum samples.
Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern
Authors: Murugadoss Karthik , Niesen Michiel J.M. , Raghunathan Bharathwaj , Lenehan Patrick J. , Ghosh Pritha , Feener Tyler , Anand Praveen , Simsek Safak , Suratekar Rohit , Hughes Travis K. , Soundararajan Venky
Published: December 2021

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged and outcompeted previously circulating strains, resulting in repeated COVID-19 surges, reinfections, and breakthrough infections in vaccinated individuals. With over 5 million SARS-CoV-2 genomes sequenced globally over the last 2 years, there is unprecedented data to decipher how competitive viral evolution results in the emergence of fitter SARS-CoV-2 variants. Much attention has been directed to studying how specific mutations in the Spike protein impact its binding to the ACE2 receptor or viral neutralization by antibodies, but there is limited knowledge of a genomic signature that is shared primarily by the sequential dominant variants. Here we introduce a methodology to quantify the genome-wide distinctiveness of polynucleotide fragments of various lengths (3-to 240-mers) that constitute SARS-CoV-2 sequences (freely available at https://academia.nferx.com/GENI). Compared to standard phylogenetic distance metrics and overall mutational load, the quantification of distinctive 9-mer polynucleotides provides a higher resolution of separation between VOCs (Reference = 89, IQR: 65-108; Alpha = 166, IQR: 150-182; Beta 130, IQR: 113-147; Gamma = 165, IQR: 152-180; Delta = 234, IQR: 216-253; and Omicron = 294, IQR: 287-315). Omicron’s exceptionally high genomic distinctiveness may confer a competitive advantage over both prior VOCs (including Delta) and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Expanding on this analysis, evaluation of genomic distinctiveness weighted by intra-lineage 9-mer conservation for 1,363 lineages annotated in GISAID highlights that genomic distinctiveness has increased over time (R2=0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed till date. This study demonstrates the value of characterizing new SARS-CoV-2 variants by their genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known functionally or antigenically salient sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that real-time monitoring of genomic distinctiveness would aid in more rapid assessment of viral fitness.
Influenza A H1N1–mediated pre-existing immunity to SARS-CoV-2 predicts COVID-19 outbreak dynamics
Authors: Almazán Nerea Martín , Rahbar Afsar , Carlsson Marcus , Hoffman Tove , Kolstad Linda , Rönnberg Bengt , Pantalone Mattia Russel , Fuchs Ilona Lewensohn , Nauclér Anna , Ohlin Mats , Sacharczuk Mariusz , Religa Piotr , Amér Stefan , Molnár Christian , Lundkvist Åke , Susrud Andres , Sörensen Birger , Söderberg-Nauclér Cecilia
Published: December 2021

Background

Susceptibility to SARS-CoV-2 infections is highly variable, ranging from asymptomatic and mild infections in most, to deadly outcome in few. This individual difference in susceptibility and outcome could be mediated by a cross protective pre-immunity, but the nature of this pre-immunity has remained elusive.

Methods

Antibody epitope sequence similarities and cross-reactive T cell peptides were searched for between SARS-CoV-2 and other pathogens. We established an ELISA test, a Luminex Multiplex bead array assay and a T cell assay to test for presence of identified peptide specific immunity in blood from SARS-CoV-2 positive and negative individuals. Mathematical modelling tested if SARS-CoV-2 outbreak dynamics could be predicted.

Findings

We found that peptide specific antibodies induced by influenza A H1N1 (flu) strains cross react with the most critical receptor binding motif of the SARS-CoV-2 spike protein that interacts with the ACE2 receptor. About 55–73% of COVID-19 negative blood donors in Stockholm had detectable antibodies to this peptide, NGVEGF, in the early pre-vaccination phase of the pandemic, and seasonal flu vaccination trended to enhance SARS-CoV-2 antibody and T cell immunity to this peptide. Twelve identified flu/SARS-CoV-2 cross-reactive T cell peptides could mediate protection against SARS-CoV-2 in 40–71% of individuals, depending on their HLA type. Mathematical modelling taking pre-immunity into account could fully predict pre-omicron SARS-CoV-2 outbreaks.

Interpretation

The presence of a specific cross-immunity between Influenza A H1N1 strains and SARS-CoV-2 provides mechanistic explanations to the epidemiological observations that influenza vaccination protects people against SARS-CoV-2 infection.
Mitigating isolation: The use of rapid antigen testing to reduce the impact of self-isolation periods
Authors: Bays Declan , Whiteley Timothy , Pindar Matt , Taylor Johnathon , Walker Brodie , Williams Hannah , Finnie Thomas J. R. , Gent Nick
Published: December 2021

Isolating, either enforced or self-guided, is a well-recognised and used technique in the limitation and reduction of disease spread. This usually balances the societal harm of disease transmission against the individual harm of being isolated and is typically limited to a very small number of individuals. With the widespread transmission of SARS-CoV-2 and requirements to self-isolate when symptomatic or having tested positive, the number of people affected has grown very large causing noticeable individual cost, and disruption to the provision of essential services. With widespread access to reliable rapid antigen tests (also known as LFD or LFTs), in this paper we examine strategies to utilise this testing technology to limit the individual harm whist maintaining the protective effect of isolation. We extend this work to examine how isolation may be improved and mitigate the release of infective individuals into the population caused by fixed time-periods.
Extending upon: What effect might border screening have on preventing importation of COVID-19 compared with other infections? – Considering the additional effect of post-arrival isolation
Authors: Bays Declan , Bennett Emma , Finnie Thomas
Published: December 2021

We recently described a simple model through which we assessed what effect subjecting travellers to a single on-arrival test might have on reducing risk of importing disease cases during simulated outbreaks of COVID-19, Influenza, SARS, and Ebola. We build upon this work to allow for the additional requirement that inbound travellers also undergo a period of self-isolation upon arrival, where upon completion the traveller is again tested for signs of infection prior to admission across the border. Prior results indicated that a single on-arrival test has the potential to detect 9% of travellers infected with COVID-19, compared to 35%, 10% and 3% for travellers infected with influenza, SARS, and Ebola respectively. Our extended model shows that testing administered after a 2-day isolation period may be able to detect up to 41%, 97%, 44% and 15% of COVID-19, Influenza, SARS, and Ebola infected travellers respectively. Longer self-isolation periods increase detection rates further, with an 8-day self-isolation period suggesting detection rates of up to 94%, 100%, 98% and 62% for travellers infected with COVID-19, Influenza, SARS, and Ebola respectively. These results therefore suggest that testing arrivals after an enforced period of self-isolation may present a reasonable method of protecting against case importation during international outbreaks.
Unsuspected clonal spread of Methicillin-resistant Staphylococcus aureus causing bloodstream infections in hospitalized adults detected using whole genome sequencing
Authors: Talbot Brooke M. , Jacko Natasia F. , Petit Robert A. , Pegues David A. , Shumaker Margot J. , Read Timothy D. , David Michael Z.
Published: December 2021

Background

Though detection of transmission clusters of methicillin-resistant Staphylococcus aureus (MRSA) infections is a priority for infection control personnel in hospitals, the transmission dynamics of MRSA among hospitalized patients with bloodstream infections (BSIs) has not been thoroughly studied. Whole genome sequencing (WGS) of MRSA isolates for surveillance is valuable for detecting outbreaks in hospitals, but the bioinformatic approaches used are diverse and difficult to compare.

Methods

We combined short-read WGS with genotypic, phenotypic, and epidemiological characteristics of 106 MRSA BSI isolates collected for routine microbiological diagnosis from inpatients in two hospitals over 12 months. Clinical data and hospitalization history were abstracted from electronic medical records. We compared three genome sequence alignment strategies to assess similarity in cluster ascertainment. We conducted logistic regression to measure the probability of predicting prior hospital overlap between clustered patient isolates by the genetic distance of their isolates.

Results

While the three alignment approaches detected similar results, they showed some variation. A pangenome-based alignment method was most consistent across MRSA clonal complexes. We identified nine unique clusters of closely-related BSI isolates. Most BSI were healthcare-associated and community-onset. Our logistic model showed that with 13 single nucleotide polymorphisms the likelihood that any two patients in a cluster overlapped in a hospital was 50 percent.

Conclusions

Multiple clusters of closely related MRSA isolates can be identified using WGS among strains cultured from BSI in two hospitals. Genomic clustering of these infections suggest that transmission resulted from a mix of community spread and healthcare exposures long before BSI diagnosis.

Multiple clusters of closely related MRSA bloodstream infections were identified using WGS in two hospitals using three bioinformatic workflows. Genomic epidemiology suggests that transmission resulted from a mix of community spread and healthcare exposures long before symptom onset.
Personalized Feeding Infusion Rate of Nutrition to Improve Glycemic Variability Control in Critical Care Patients
Authors: Abohtyra Rammah
Published: December 2021

Control-based algorithms in the intensive care unit (ICU) patients have been developed to deliver a sufficient amount of insulin, but optimizing the rate of feeding of nutrition in ICU patients to improve glycemic variability control has not been done yet. Continuous feeding is commonly used for nutrition in critically ill patients who cannot be fed orally to maintain a normal blood sugar concentration, but optimizing its rate, for these individuals, is needed to avoid the adverse outcomes caused by medications such as insulin. This paper develops a control-based algorithm combines a predictive control algorithm with a revised nonlinear compartmental model used in the ICU to design personalized feeding function rates to improve patient glycemic variability. Our control algorithm is robust and acts very quickly to avoid medical intervention effects.
Identifying Mitral Valve Prolapse at Risk for Ventricular Arrhythmias and Myocardial Fibrosis from 12-lead Electrocardiograms using Deep Learning
Authors: Tison Geoffrey H. , Abreau Sean , Lim Lisa , Crudo Valentina , Barrios Joshua , Nguyen Thuy , Hu Gene , Dixit Shalini , Nah Gregory , Lee Yoojin , Delling Francesca N.
Published: December 2021

Background

Mitral valve prolapse (MVP) is a common valvulopathy, with a subset of MVP patients developing sudden cardiac death or cardiac arrest. Complex ventricular ectopy (ComVE) represents a marker of arrhythmic risk that is associated with myocardial fibrosis and increased mortality in MVP. We hypothesize that an ECG-based machine-learning model can identify MVP with ComVE and/or myocardial fibrosis on cardiac magnetic resonance (CMR) imaging.

Methods

A deep convolutional neural network (CNN) was trained to detect ComVE using 6,916 12-lead ECGs from 569 MVP patients evaluated at the University of California San Francisco (UCSF) between 2012 and 2020. A separate CNN was also trained to detect late gadolinium enhancement (LGE) using 87 ECGs from MVP patients with contrast CMR.Results: The prevalence of ComVE was 160/569 or 28% (20 patients or 3% had cardiac arrest or sudden cardiac death). The area under the curve (AUC) of the CNN to detect ComVE was 0.81 (95% CI, 0.78-0.84). AUC remained high even after excluding patients with moderate-severe mitral regurgitation (MR) [0.80 (95% CI, 0.77-0.83)], or with bileaflet MVP [0.81 (95% CI, 0.76-0.85)]. The top ECG segments able to discriminate ComVE vs no ComVE were related to ventricular depolarization and repolarization (early-mid ST and QRS fromV1, V3, and III). LGE in the papillary muscles or basal inferolateral wall was present in 21 (24%) of 87 patients with available CMR. The AUC for detection of LGE was 0.75 (95% CI, 0.68-0.82).

Conclusions

Standard 12-lead ECGs analyzed with machine learning can detect MVP at risk for ventricular arrhythmias and fibrosis and can identify novel ECG correlates of arrhythmic risk regardless of leaflet involvement or mitral regurgitation severity. ECG-based CNNs may help select those MVP patients requiring closer follow-up and/or a CMR.
Early Treatment with Fluvoxamine Among Patients with COVID-19: A Cost-Consequence Model
Authors: Mills Fergal P. , Reis Gilmar , Thorlund Kristian , Forrest Jamie I. , Guo Christina M. , Boulware David R , Mills Edward J. ,   for the TOGETHER Investigators
Published: December 2021

Background

Three randomized trials have been conducted indicating a clinical benefit of early treatment with fluvoxamine versus placebo for adults with symptomatic COVID-19. We assessed the cost-consequences associated with the use of this early treatment in outpatient populations.

Methods

Using results from the three completed trials of fluvoxamine vs. placebo for the treatment of COVID-19, we performed a meta-analysis. We conducted a cost-consequence analysis using a decision-model to assess the health system benefits of the avoidance of progression to severe COVID-19. Outcomes of relevance to resource planning decisions in the US and elsewhere, including costs and days of hospitalization avoided, were reported. We constructed a decision-analytic model in the form of a decision tree to evaluate two treatment strategies for high-risk patients with confirmed, symptomatic COVID-19, from the perspective of a third-party payer:(1) treatment with a 10-day course of fluvoxamine (100mg twice daily); (2) current standard-of-care; (3) molnupiravir 5-day course. We used a time horizon of 28 days.

Results

Administration of fluvoxamine to symptomatic outpatients with COVID-19 at high-risk of developing progression to severe COVID-19 complications is substantially cost-saving in the US, in the amount of $232 per eligible patient, and saves an average of 0.15 hospital days per patient treated is likely to be similarly beneficial in other settings. Fluvoxamine is cost saving in locations where total hospital costs are >$738. Molnupiravir had an additional cost to the healthcare system of $404 per patient treated.

Conclusions

Fluvoxamine is cost-saving for COVID-19 outpatient therapy.

Funding

FastGrants and Rainwater Charitable Foundation
In vitro evolution predicts emerging CoV-2 mutations with high affinity for ACE2 and cross-species binding
Authors: Bate Neil , Savva Christos G , Moody Peter CE , Brown Edward A , Ball Jonathan K , Schwabe John WR , Sale Julian E , Brindle Nicholas PJ
Published: December 2021

Emerging SARS CoV-2 variants are creating major challenges in the ongoing Covid-19 pandemic. Predicting CoV-2 mutations that increase transmissibility or immune evasion would be extremely valuable in development of broad-acting therapeutics and vaccines and prioritising viral monitoring and containment. Using in vitro evolution, we identify a double mutation in CoV-2 receptor binding domain (RBD) that increases affinity for ACE2 almost 20-fold. We determine the mutant:ACE2 structure to reveal the binding mechanism and show the main affinity driver, Q498H, boosts binding of other RBD variants. We find this mutation incompatible with the common N501Y mutation, but N501Y variants can acquire Q498R to access a similar bonding network and affinity gain. We show Q498H, and Q498R plus N501Y, enable variants to bind rat ACE2 with high affinity. These mutations are now emerging in CoV-2 variants, such as the Omicron variant, where they would be expected to drive increased human-to-human and cross-species transmission.