bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is the quality of hospital EHR data sufficient to evidence its ICHOM outcomes performance in heart failure? A pilot evaluation
Authors: Aerts Hannelore , Kalra Dipak , Saez Carlos , Ramírez-Anguita Juan Manuel , Mayer Miguel-Angel , Garcia-Gomez Juan M. , Durá Hernández Marta , Thienpont Geert , Coorevits Pascal 
Published: February 2021

AbstractThere is increasing recognition that healthcare providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error prone. However, there is uncertainty about whether routinely collected clinical data within EHR systems includes the data most relevant to measuring and comparing outcomes, and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality.In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multi-stakeholder consultation. Adopting this approach, we perform a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure. To this end, all available registries compatible with the diagnosis of heart failure within the IMASIS-2 data repository connected to the Hospital del Mar network (142,345 visits of 12,503 patients) were extracted and mapped to the ICHOM format. We focus our pilot assessment on five commonly used data quality dimensions: completeness, correctness, consistency, uniqueness and temporal stability.Overall, this pilot study reveals high scores on the consistency, completeness and uniqueness dimensions. Temporal stability analyses show some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, investigation of data correctness suggests several issues concerning the proper characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail which is not explicitly available in the coded data of an EHR.To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM heart failure standard set, across multiple hospitals.
Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness
Authors: Chen Jiangzhuo , Hoops Stefan , Marathe Achla , Mortveit Henning , Lewis Bryan , Venkatramanan Srinivasan , Haddadan Arash , Bhattacharya Parantapa , Adiga Abhijin , Vullikanti Anil , Srinivasan Aravind , Wilson Mandy L , Ehrlich Gal , Fenster Maier , Eubank Stephen , Barrett Christopher , Marathe Madhav 
Published: February 2021

AbstractWe study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our strategy marks a departure from such largely aggregate vaccine allocation strategies. We propose a novel agent-based modeling approach motivated by recent advances in (i) science of real-world networks that point to efficacy of certain vaccination strategies and (ii) digital technologies that improve our ability to estimate some of these structural properties. Using a realistic representation of a social contact network for the Commonwealth of Virginia, combined with accurate surveillance data on spatio-temporal cases and currently accepted models of within- and between-host disease dynamics, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals’ degree (number of social contacts) and total social proximity time issignificantly more effectivethan the currently used age-based allocation strategy in terms of number of infections, hospitalizations and deaths. Our results suggest that in just two months, by March 31, 2021, compared to age-based allocation, the proposed degree-based strategy can result inreducing an additional 56–110k infections, 3.2–5.4k hospitalizations, and 700–900 deaths just in the Commonwealth of Virginia. Extrapolating these results for the entire US, this strategy can lead to 3–6 million fewer infections, 181–306k fewer hospitalizations, and 51–62k fewer deaths compared to age-based allocation.The overall strategy is robust even: (i) if the social contacts are not estimated correctly; (ii) if the vaccine efficacy is lower than expected or only a single dose is given; (iii) if there is a delay in vaccine production and deployment; and (iv) whether or not non-pharmaceutical interventions continue as vaccines are deployed. For reasons of implementability, we have used degree, which is a simple structural measure and can be easily estimated using several methods, including the digital technology available today. These results are significant, especially for resource-poor countries, where vaccines are less available, have lower efficacy, and are more slowly distributed.
Outdoor air pollution and the risk of asthma exacerbations in single lag0 and lag1 exposure patterns: A systematic review and meta-analysis
Authors: Huang Junjun , Yang Xiaoyu , Fan Fangfang , Hu Yan , Wang Xi , Zhu Sainan , Ren Guanhua , Wang Guangfa 
Published: February 2021

ABSTRACTBackgroundAsthma exacerbations accelerate the disease progression, as well as increases the incidence of hospitalizations and deaths. There have been studies on the effects of outdoor air pollution and asthma exacerbations; however, evidence regarding single lag0 and lag1 exposure patterns is inconclusive.ObjectiveTo synthesize evidence regarding the relationship between outdoor air pollution and the asthma exacerbation risk in single lag0 and lag1 exposure patterns.MethodsWe performed a systematic literature search using PubMed, Embase, Cochrane Library, Web of Science, ClinicalTrials, China National Knowledge Internet, Chinese BioMedical, and Wanfang databases until August 1st, 2020. Additionally, we reviewed the reference lists of the relevant articles. Two authors independently evaluated the eligible articles and performed structured extraction of relevant information. Pooled relative risks (RRs) and 95% confidence intervals (CIs) of lag0 and lag1 exposure patterns were estimated using the random-effect models.ResultsEighty-four studies met the eligibility criteria and provided sufficient information for meta-analysis. Outdoor air pollutants were associated with significantly increased risks of asthma exacerbations in both single lag0 and lag1 exposure patterns [lag0: RR (95%CI) (pollutants), 1.057(1.011, 1.103) (air quality index; AQI), 1.007(1.005, 1.010) (PM2.5), 1.009(1.005, 1.012) (PM10), 1.010(1.006, 1.014) (NO2), 1.030(1.011, 1.048) (CO), 1.005(1.002, 1.009) (O3); lag1: RR (95%CI) (pollutants), 1.064(1.022, 1.106) (AQI), 1.005(1.002, 1.008) (PM2.5), 1.007(1.004, 1.011) (PM10), 1.008(1.004, 1.012) (NO2), 1.025(1.007, 1.042) (CO), 1.010(1.006, 1.013) (O3)], except SO2 [lag0: RR (95%CI), 1.004(1.000, 1.007); lag1: RR (95%CI), 1.003(0.999, 1.006)]. Subgroup analyses revealed stronger effects in children and asthma exacerbations associated with other events (including symptoms, lung function changes, and medication use as required).ConclusionThese findings demonstrate that outdoor air pollution significantly increases the asthma exacerbation risk in single lag0 and lag1 exposure patterns.PROSPERO registration numberCRD42020204097 (https://www.crd.york.ac.uk/PROSPERO).Strengths and limitations of this studyWe performed a systematic literature search of six databases (with no specified start date or language limitation).Secondary references were included.Publication bias was assessed by applying Begg’s and Egger’s tests.This study focused on the association between outdoor air pollution and the asthma exacerbation risk in single lag0 and lag1 exposure patterns.There were few available studies regarding the AQI, other events, and death analyses.
Demographic and clinical characteristics of patients with functional motor disorders: the prospective Salpêtrière cohort
Authors: Garcin Béatrice , Villain Nicolas , Mesrati Francine , Naccache Lionel , Roze Emmanuel , Degos Bertrand 
Published: February 2021

AbstractFunctional motor disorders (FMD) are common and disabling. They are known to affect predominantly women and to start at young or middle age but to date, large case series are lacking, and demographic and clinical characteristics of patients with FMD rely on data from small cohorts. The current study aimed at describing the demographic and clinical characteristics of a large cohort of FMD patients.MethodsWe prospectively collected data from FMD patients who were referred to the Neurophysiology Department of the Pitié-Salpêtrière University Hospital between 2008 and 2016 for treatment with repeated transcranial magnetic stimulation.Results482 patients were included. There was a majority of women (73.7%) with a median age of 40 years old at TMS treatment. Median age at symptoms onset was 35.5 years old and symptoms were mostly characterized by an acute (47.3%) or subacute (46%) onset. Only 23% of patients were active workers while 58.3% were unemployed for medical reasons. Half of the patients suffered from functional motor weakness (n= 241) and the other half suffered from movement disorders (n=241), mainly represented by tremor (21.15%) and dystonia (20.5%). 33.6% had no psychiatric comorbidity and 17.4% reported no history of trauma. No significant differences were found in age or gender according to clinical phenotypes.ConclusionWe present the largest cohort of patients with FMD to date. This cohort will contribute to a better understanding of FMDs and their risk factors.
Vaccine Efficacy at a Point in Time
Authors: Follmann Dean , Fay Michael 
Published: February 2021

AbstractVaccine trials are generally designed to assess efficacy on clinical disease. The vaccine effect on infection, while important both as a proxy for transmission and to describe a vaccine’s total effects, requires frequent longitudinal sampling to capture all infections. Such sampling may not always be feasible. A logistically easy approach is to collect a sample to test for infection at a regularly scheduled visit. Such point or cross-sectional sampling does not permit estimation of classic vaccine effiacy on infection, as long duration infections are sampled with higher probability. Building on work by Rinta-Kokko and others (2009) we evaluate proxies of the vaccine effect on transmission at a point in time; the vaccine efficacy on prevalent infection and on prevalent viral load, VEPI and VEPV L, respectively. Longer infections with higher viral loads should have more transmission potential and prevalent vaccine efficacy naturally captures this aspect. We apply a proportional hazards model for infection risk and show how these metrics can be estimated using longitudinal or cross-sectional sampling. We also introduce regression models for designs with multiple cross-sectional sampling. The methods are evaluated by simulation and a phase III vaccine trial with PCR cross-sectional sampling for subclinical infection is analyzed.
Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning
Authors: Jamshidi Elham , Asgary Amirhossein , Tavakoli Nader , Zali Alireza , Dastan Farzaneh , Daaee Amir , Badakhshan Mohammadtaghi , Esmaily Hadi , Jamaldini Seyed Hamid , Safari Saeid , Bastanhagh Ehsan , Maher Ali , Babajani Amirhesam , Mehrazi Maryam , Kashi Mohammad Ali Sendani , Jamshidi Masoud , Sendani Mohammad Hassan , Rahi Sahand Jamal , Mansouri Nahal 
Published: February 2021

ABSTRACTBackgroundEarly prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation strategies, and thus reduce the prevalence of the disease. Such publicly accessible prediction models are lacking, however.MethodsBased on a comprehensive evaluation of existing machine learning (ML) methods, we created two models based solely on the age, gender, and medical histories of 23,749 hospital-confirmed COVID-19 patients from February to September 2020: a symptom prediction model (SPM) and a mortality prediction model (MPM). The SPM predicts 12 symptom groups for each patient: respiratory distress, consciousness disorders, chest pain, paresis or paralysis, cough, fever or chill, gastrointestinal symptoms, sore throat, headache, vertigo, loss of smell or taste, and muscular pain or fatigue. The MPM predicts the death of COVID-19-positive individuals.ResultsThe SPM yielded ROC-AUCs of 0.53-0.78 for symptoms. The most accurate prediction was for consciousness disorders at a sensitivity of 74% and a specificity of 70%. 2440 deaths were observed in the study population. MPM had a ROC-AUC of 0.79 and could predict mortality with a sensitivity of 75% and a specificity of 70%. About 90% of deaths occurred in the top 21 percentile of risk groups. To allow patients and clinicians to use these models easily, we created a freely accessible online interface at www.aicovid.org.ConclusionsThe ML models predict COVID-19-related symptoms and mortality using information that is readily available to patients as well as clinicians. Thus, both can rapidly estimate the severity of the disease, allowing shared and better healthcare decisions with regard to hospitalization, self-isolation strategy, and COVID-19 vaccine prioritization in the coming months.Abstract Figure
Five hours total sleep deprivation does not affect CA1 dendritic length or spine density
Authors: Brodin Alvin T.S. , Gabulya Sarolta , Wellfelt Katrin , Karlsson Tobias E. 
Published: February 2021

AbstractSleep is essential for long term memory function. However the neuroanatomical consequences of sleep loss are disputed. Sleep deprivation has been reported to cause both decreases and increases of dendritic spine density. Here we use Thy1-GFP expressing transgenic mice to investigate the effects of acute sleep deprivation on the dendritic architecture of hippocampal CA1 pyramidal neurons. We found that five hours of sleep deprivation had no effect on either dendritic length or dendritic spine density. Our work suggests that no major neuroanatomical changes result from one episode of sleep deprivation.
ASigNTF: Agnostic Signature using NTF – a universal agnostic strategy to estimate cell-types abundance from transcriptomic datasets
Authors: Fogel Paul , Boldina Galina , Rocher Corinne , Bettembourg Charles , Luta George , Augé Franck 
Published: February 2021

AbstractBackgroundMolecular signatures for deconvolution of immune cell types have been proposed, based on a methodology that relies on the biological classification of the cell types being studied. When working with less known biological material, a data-driven approach is needed to uncover the underlying classes and construct ad hoc signatures.ResultsWe introduce a new approach, ASigNTF: Agnostic Signature using Non-negative Tensor Factorization, to perform the deconvolution of cell types from transcriptomics data (RNAseq and microarray). ASigNTF, which is based on two complementary statistical/mathematical tools: non-negative tensor factorization (for dimensionality reduction) and the Herfindahl-Hirschman index (for signature selection), can be applied to any type of tissue as long as transcriptomic data on isolated cells is available. As a direct result of the new method, we propose two new signatures for the deconvolution of immune cell types, one consisting of a relatively small set of 415 genes, which is more compatible with microarray platforms, and a larger set of 915 genes. Using external datasets, our two signatures outperform the CIBERSORT LM22 signature in deconvolution of RNA-seq data. Our signature with 415 genes allows to recognize a larger number of cell types compared to the ABIS microarray signature.ConclusionsThe paper proposes a new method, ASigNTF; applies the method, and also provides a software implementation that allows to identify molecular signatures for deconvolution of complex tissues and specifically up to 16 immune cell types from micro-array or RNA-seq data.HighlightsSeveral signatures of immune cell types have been proposed, which follow a methodology deeply rooted in the known biological classification of the investigated cell types.When working with less known biological material, a more agnostic, data-driven approach is required to uncover the underlying classes and construct ad hoc signatures.We present ASigNTF, a new agnostic approach to cell type classification and signature selection supported by an application software.We discuss the results of benchmarking our proposed signatures, ABIS-seq and CIBERSORT on external datasets.
The epoxyeicosatrienoic pathway is intact in endothelial and smooth muscle cells exposed to aldosterone excess
Authors: Brunnenkant Laura , Meng Yao , Sun Jing , Marques Jair Gonzalez , Koletzko Berthold , Schnitzler Michael Mederos Y , Gudermann Thomas , Williams Tracy Ann , Beuschlein Felix , Heinrich Daniel A , Adolf Christian , Reincke Martin , Schneider Holger 
Published: February 2021

AbstractObjectivesEndothelial dysfunction (ED) is considered to be a major driver of the increased incidence of cardiovascular disease in primary aldosteronism (PA). Whether the epoxyeicosatrienoic acid (EET) pathway, involving the release of beneficial endothelium-derived lipid mediators, contributes to ED in PA is unknown. Preclinical evidence suggests this pathway to be relevant in the pathogenesis in various models of experimental hypertension. In addition, an orally available soluble epoxide hydrolase inhibitor, which halts the breakdown of EETs, has already passed a phase 1 clinical trial.We, therefore, exposed primary human coronary artery endothelial cells to 1 nM aldosterone.MethodsWe used qPCR to investigate changes in the expression levels of essential genes for the synthesis and degradation of EETs as well as mass spectrometry to determine endothelial synthetic capacity to release EETs upon stimulation. We also assessed primary human coronary artery smooth muscle cells for expression of putative EET receptor ion channels or downstream mediators as well as for the calcium response to EETs using calcium imaging.ResultsNo major aldosterone-related expression changes were detected on the endothelial as well as the smooth muscle side. Stimulated release of endothelial EETs was unaffected. Likewise, the smooth muscle calcium response was unchanged after aldosterone excess.ConclusionsThe EET pathway is not negatively affected by increased aldosterone concentrations as seen in PA. Modulating the EET pathway with therapeutic intent in patients with PA might therefore be assessed in future preclinical and clinical trials to address ED.
Pharmacokinetics of Orally Administered GS-441524 in Dogs
Authors: Yan Victoria C. , Pham Cong-Dat , Yan Matthew J. , Yan Alexander J. , Khadka Sunada , Arthur Kenisha , Ackroyd Jeffrey J. , Georgiou Dimitra K. , Roon Laura E. , Bushman Lane R. , Anderson Peter L. , Li Chun , Muller Florian L. 
Published: February 2021

AbstractDespite being FDA-approved for COVID-19, the clinical efficacy of remdesivir (Veklury®) remains contentious. We previously pointed out pharmacokinetic, pharmacodynamic and toxicology reasons for why its parent nucleoside GS-441524, is better suited for COVID-19 treatment. Here, we assess the oral bioavailability of GS-441524 in beagle dogs and show that plasma concentrations ∼24-fold higher than the EC50against SARS-CoV-2 are easily and safely sustained. These data support translation of GS-441524 as an oral agent for COVID-19.
Ovine CD14- an immune response gene has a role against gastrointesinal nematodeHaemonchus contortus-a novel report
Authors: Rawat Kavita , Pal Aruna , Banerjee Samiddha , Pal Abantika , Mandal Subhas Chandra , Batabyal Subhashis 
Published: February 2021

AbstractCD14 (also known as monocyte differentiation antigen) is an important immune response gene known to be primarily responsible for innate immunity against bacterial pathogen and as pattern recognition receptor (PRR) binds with LPS (endotoxin), lipoproteins, lipotechoic acid of bacteria.So far very limited work has been conducted in parasitic immunology. In the current study, we reported the role of CD14 in parasitic immunology in livestock species (sheep) for the first time. Ovine CD14 is characterized as a horse-shoe shaped as a bent solenoid with a hydrophobic amino-terminal pocket for CD14 along with domains. High mutation frequency was observed, out of total 41 mutations identified, 23 mutations were observed to be thermodynamically unstable and 11 mutations were deleterious in nature, causing major functional alteration of important domains of CD14, an indicative for variations in individual susceptibility for sheeps againstHaemonchus contortusinfestations.In silicostudies with molecular docking reveals a role of immune response againstHaemonchus contortusin sheep, which is later confirmed with experimental evidence through differential mRNA expression analysis for sheep, which revealed better expression of CD14 inHaemonchus contortusinfected sheep compared to that of healthy sheep. We confirmed the above findings with supportive evidences with haematological and biochemical analyses. Phylogenetic analysis was conducted to assess the evolutionary relationship with respect to human and observed that sheep may well be used as model organism due better genetic closeness compared to that of mouse.