bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Implementation Science Approach to Promote Optimal Implementation, Adoption, Use, and Spread of Continuous Clinical Monitoring System Technology
Authors: Dykes Patricia C. , Lowenthal Graham , Faris Ann , Leonard Michelle Waters , Hack Robin , Harding Deborah , Huffman WHNP Carolyn , Hurley Ann , An Perry 
Published: December 2020

Objectives
This study aimed to apply implementation science tenets to guide the deployment and use of in-hospital Clinical Monitoring System Technology (CMST) and to develop a toolkit to promote optimal implementation, adoption, use, and spread of CMST.

Methods
Six steps were carried out to (1) establish leadership support; (2) identify, educate, and sustain champions; (3) enlist clinical staff users to learn barriers and facilitators; (4) examine initial qualitative data from 11 clinician group interviews; (5) validate barriers/facilitators to CMST use and toolkit content; and (6) propose a toolkit to promote utilization. Clinical Monitoring System Technology output before and after implementation were compared.

Results
The top 3 barriers to effective CMST use were as follows: (1) inadequate education/training/support, (2) clinical workflow challenges, and (3) lack of communication. Facilitators to CMST implementation and adoption included the following: (1) providing comprehensive and consistent CMST education, (2) presenting evidence early and often, (3) tailoring device and usage expectations to individual environments, and (4) providing regular feedback about progress. Empirical data drove the development of a CMST implementation toolkit covering 6 areas: (1) why, (2) readiness, (3) readiness and implementation, (4) patient/family introduction, (5) champions, (6) care team saves, and (7) troubleshooting. Clinical Monitoring System Technology positively impacted failure to rescue events. Monthly median cardiac alert responses decreased from 30 to 3.64 minutes (87.9%), and respiratory alert responses decreased from 26 to 4.85 minutes (81.4%).

Conclusions
Using implementation science tenets to concurrently guide deployment and study performance of 2 CMST devices and impact on workload was effective for both learning CMST efficacy at 2 hospital systems and developing a toolkit to promote optimal implementation, adoption, use, and spread.
Accelerated Isotropic Multiparametric Imaging by High Spatial Resolution 3D-QALAS With Compressed Sensing
Authors: Fujita Shohei , Hagiwara Akifumi , Takei Naoyuki , Hwang Ken-Pin , Fukunaga Issei , Kato Shimpei , Andica Christina , Kamagata Koji , Yokoyama Kazumasa , Hattori Nobutaka , Abe Osamu , Aoki Shigeki 
Published: December 2020

Objectives
The aims of this study were to develop an accelerated multiparametric magnetic resonance imaging method based on 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) combined with compressed sensing (CS) and to evaluate the effect of CS on the quantitative mapping, tissue segmentation, and quality of synthetic images.

Materials and Methods
A magnetic resonance imaging system phantom, containing multiple compartments with standardized T1, T2, and proton density (PD) values; 10 healthy volunteers; and 12 patients with multiple sclerosis were scanned using the 3D-QALAS sequence with and without CS and conventional contrast-weighted imaging. The scan times of 3D-QALAS with and without CS were 5:56 and 11:11, respectively. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. For patients with multiple sclerosis, the mean T1, T2, PD, and the amount of myelin in plaques and contralateral normal-appearing white matter (NAWM) were measured. Simple linear regression analysis and Bland-Altman analysis were performed for each metric obtained from the datasets with and without CS. To compare overall image quality and structural delineations on synthetic and conventional contrast-weighted images, case-control randomized reading sessions were performed by 2 neuroradiologists in a blinded manner.

Results
The linearity of both phantom and volunteer measurements in T1, T2, and PD values obtained with and without CS was very strong (R
2 = 0.9901–1.000). The tissue segmentation obtained with and without CS also had high linearity (R
2 = 0.987–0.999). The quantitative tissue values of the plaques and NAWM obtained with CS showed high linearity with those without CS (R
2 = 0.967–1.000). There were no significant differences in overall image quality between synthetic contrast-weighted images obtained with and without CS (P = 0.17–0.99).

Conclusions
Multiparametric imaging of the whole brain based on 3D-QALAS can be accelerated using CS while preserving tissue quantitative values, tissue segmentation, and quality of synthetic images.
Is Technology Enhanced Learning Cost-effective to Improve Skills?
Authors: Lim Angelina S. , Lee Shaun Wen Huey 
Published: December 2020

Introduction
Objective Structured Clinical Examinations (OSCEs) are an accepted technique for evaluation of clinical competence in healthcare. However, the economic imperative requires faculty to control cost, using innovative educational strategies such as virtual simulation. The objective of this study was to evaluate the cost implications of implementing an online interactive learning module [Monash OSCE Virtual Experience (MOVE)].

Methods
All fourth-year pharmacy students enrolled in Monash University in 2017 were provided access to MOVE. Cost-minimization analyses were performed to evaluate the cost of introducing MOVE in the pharmacy course using the smallest cohort size (Malaysia campus) of 40 students as the base case. We also determined under what circumstances MOVE would be more cost-effective, considering the different operational situations such as when student numbers increased or when the number of simulation modules created were increased.

Results
The overall cost of setup and implementation of MOVE in the first year of implementation among 40 students was US $94.38 per student. In comparison, the face-to-face workshop cost was US $64.14 per student. On the second year of implementation, the ongoing cost of operation of MOVE was US $32.86 per student compared with US $58.97 per student using face-to-face workshop. A net benefit using MOVE was observed after the third year of implementation. Larger savings were noted when the cohort size extends larger than 100 students.

Conclusions
Monash OSCE Virtual Experience was a flexible and cost-effective approach to aid students in preparation for an OSCE and enhanced students' learning experience. The wider applicability of these findings will need to be explored in other settings.
External Validity of the Multicenter Randomized PREOPANC Trial on Neoadjuvant Chemoradiotherapy in Pancreatic Cancer
Authors: Versteijne Eva , Suker Mustafa , Groen Jesse V. , Besselink Marc G. , Bonsing Bert A. , Bosscha Koop , Busch Olivier R. , de Hingh Ignace H. J. T. , de Jong Koert P. , Molenaar I. Quintus , van Santvoort Hjalmar C. , Verkooijen Helena M. , Van Eijck Casper H. , van Tienhoven Geertjan 
Published: December 2020

Objectives:
To investigate the accrual proportion and patients’ reasons for not participating in the PREOPANC trial on neoadjuvant chemoradiotherapy versus immediate surgery in resectable and borderline resectable pancreatic cancer, and to compare these patients’ outcomes with those of patients who had been randomized in the trial.

Summary of Background Data:
The external validity of multicenter randomized trials in cancer treatment has been criticized for suboptimal non-representative inclusion. In trials, it is unclear how outcomes compare between randomized and nonrandomized patients.

Methods:
At 8 of 16 participant centers, this multicenter observational study identified validation patients, who had been eligible but not randomized during recruitment for the PREOPANC trial. We assessed the accrual proportion, investigated their most common reasons for not participating in the trial, and compared resection rates, radical (R0) resection rates, and overall survival between the validation patients and PREOPANC patients, who had been randomized in the trial to immediate surgery.

Results:
In total, 455 patients had been eligible during the recruitment period, 151 of whom (33%) had been randomized. Fifty-five percent of the 304 validation patients had refused to participate. Median overall survival in the validation group was 15.2 months, against 15.5 months in the PREOPANC group (P = 1.00). The respective resection rates (76% vs 73%) and R0 resection rates (51% vs 46%) did not differ between the groups.

Conclusions:
The PREOPANC trial included a reasonable percentage of 33% of eligible patients. In terms of the outcomes survival, resection rate, and R0 resection rate, this appeared to be a representative group.
Individual variation underlying brain age estimates in typical development
Authors: Ball Gareth , Kelly Claire E , Beare Richard , Seal Marc L 
Published: December 2020

AbstractTypical brain development follows a protracted trajectory throughout childhood and adolescence. Deviations from typical growth trajectories have been implicated in neurodevelopmental and psychiatric disorders. Recently, the use of machine learning algorithms to model age as a function of structural or functional brain properties has been used to examine advanced or delayed brain maturation in healthy and clinical populations. Termed ‘brain age’, this approach often relies on complex, nonlinear models that can be difficult to interpret. In this study, we use model explanation methods to examine the cortical features that contribute to brain age modelling on an individual basis.In a large cohort of n=768 typically-developing children (aged 3-21 years), we build models of brain development using three different machine learning approaches. We employ SHAP, a model-agnostic technique to estimate sample-specific feature importance, to identify regional cortical metrics that explain errors in brain age prediction. We find that, on average, brain age prediction and the cortical features that explain model predictions are consistent across model types and reflect previously reported patterns of regional brain development. However, while several regions are found to contribute to brain age prediction, we find little spatial correspondence between individual estimates of feature importance, even when matched for age, sex and brain age prediction error. We also find no association between brain age error and cognitive performance in this typically-developing sample.Overall, this study shows that, while brain age estimates based on cortical development are relatively robust and consistent across model types and preprocessing strategies, significant between-subject variation exists in the features that explain erroneous brain age predictions on an individual level.
Molecular characterization of projection neuron subtypes in the mouse olfactory bulb
Authors: Zeppilli Sara , Ackels Tobias , Attey Robin , Klimpert Nell , Ritola Kimberly D. , Boeing Stefan , Crombach Anton , Schaefer Andreas T. , Fleischmann Alexander 
Published: December 2020

AbstractProjection neurons (PNs) in the mammalian olfactory bulb (OB) receive direct input from the nose and project to diverse cortical and subcortical areas. Morphological and physiological studies have highlighted functional heterogeneity, yet no molecular markers have been described that delineate PN subtypes. Here, we used viral injections into olfactory cortex and fluorescent nucleus sorting to enrich PNs for high-throughput single nucleus and bulk RNA deep sequencing. Transcriptome analysis and RNAin situhybridization identified three mitral and five tufted cell populations with characteristic transcription factor network topology and cell adhesion and excitability-related gene expression. Finally, by integrating bulk and snRNA-seq data we propose that different mitral cell populations selectively project to different regions of olfactory cortex. Together, we have identified potential molecular and gene regulatory mechanisms underlying PN diversity and provide new molecular entry points into studying the diverse functional roles of mitral and tufted cell subtypes.
CovidRiskCalc: An online app to calculate the risk of COVID infection in a gathering
Authors: Artzrouni Marc 
Published: December 2020

ABSTRACTCovidRiskCalc is an evidence based online app which calculates the risk of COVID-19 infection for a person coming into contact during a specific event/gathering with a group of individuals, some of whom may be infected (available at CovidRiskCalc.eu). The user is helped in providing a rough estimate of the COVID-19 prevalence rate in the group. She also inputs the size of the group, the number (and duration) of her contacts and the level of precautions (masks, social distancing, etc.). The app calculates the user’s risk of transmission in a single infected contact; her probability of infection during the entire event and the number of new infections within the group. Two numerical examples are given. The tool, designed for both professionals and the general public, thus quantifies the risks of infection in special populations (social gatherings, prisons, etc.), but also in general ones (stores, stadiums, etc.).
Associations between vaping and Covid-19: cross-sectional findings from the HEBECO study
Authors: Kale Dimitra , Herbec Aleksandra , Perski Olga , Jackson Sarah E , Brown Jamie , Shahab Lion 
Published: December 2020

AbstractAimsTo explore i) associations between vaping and self-reported diagnosed/suspected Covid-19; ii) changes in vaping since Covid-19 and factors associated with these changes; iii) whether Covid-19 motivated current or recent ex-vapers to quit.MethodsCross-sectional online survey of 2791 UK adults recruited 30/04/2020–14/06/2020. Participants self-reported data on sociodemographic characteristics, diagnosed/suspected Covid-19, vaping status, changes in vaping and motivation to quit vaping since Covid-19.ResultsThere were no differences in diagnosed/suspected Covid-19 between never, current and ex-vapers. Bayes factors indicated there was sufficient evidence to rule out small negative (protective) associations between vaping status and diagnosed/suspected Covid-19. Among current vapers (n=397), 9.7% (95% CI 6.8-12.6%) reported vaping less than usual since Covid-19, 42.0% (37.2-46.9%) reported vaping more, and 48.3% (43.4-53.2%) reported no change. In adjusted analyses, vaping less was associated with being female (aOR=3.40, 95% CI 1.73-6.71), not living with children (aOR=4.93, 1.15-21.08) and concurrent smoking (aOR=8.77, 3.04-25.64), while vaping more was associated with being younger (aOR=5.26, 1.37-20.0), living alone (aOR=2.08, 1.14-3.85), and diagnosed/suspected Covid-19 (aOR=4.72, 2.60-8.62). Of current vapers, 32.2% (95% CI 27.5-36.8%) were motivated to quit vaping since Covid-19, partly motivated by Covid-19, and 17.4%, (9.7-26.3%) of recent ex-vapers quit vaping due to Covid-19.ConclusionsAmong UK adults, self-reported diagnosed/suspected Covid-19 was not associated with vaping status. Half of current vapers changed their vaping consumption since Covid-19, with the majority reporting an increase, and a minority was motivated to quit due to Covid-19.RegistrationThe analysis plan was pre-registered, and it is available at https://osf.io/6j8z3/HighlightsNo difference found in diagnosed/suspected Covid-19 between never, current and ex-vapersHalf of current vapers changed their vaping consumption since Covid-19Motivation to quit vaping was partly related to Covid-19
Assessing the risk of vaccine-driven virulence evolution in SARS-CoV-2
Authors: Miller Ian F. , Metcalf C. Jessica E. 
Published: December 2020

AbstractHow might COVID-19 vaccines alter selection for increased SARS-CoV-2 virulence, or lethality? Framing current evidence surrounding SARS-CoV-2 biology and COVID-19 vaccines in the context of evolutionary theory indicates that prospects for virulence evolution remain uncertain. However, differential effects of vaccinal immunity on transmission and disease severity between respiratory compartments could select for increased virulence. To bound expectations for this outcome, we analyze an evo-epidemiological model. Synthesizing model predictions with vaccine efficacy data, we conclude that while vaccine driven virulence evolution remains a theoretical risk, it is unlikely to threaten prospects for herd immunity in immunized populations. Given that this event would nevertheless impact unvaccinated populations, virulence should be monitored to facilitate swift mitigation efforts.Significance statementVaccines can provide personal and population level protection against infectious disease, but these benefits can exert strong selective pressures on pathogens. Virulence, or lethality, is one pathogen trait that can evolve in response to vaccination. We investigated whether COVID-19 vaccines could select for increased SARS-CoV-2 virulence by reviewing current evidence about vaccine efficacy and SARS-CoV-2 biology in the context of evolutionary theory, and subsequently analyzing a mathematical model. Our findings indicate that while vaccine-driven virulence evolution in SARS-CoV-2 is a theoretical risk, the consequences of this event would be limited for vaccinated populations. However, virulence evolution should be monitored, as the ramifications of a more virulent strain spreading into an under-vaccinated population would be more severe.
Variants in SARS-CoV-2 Associated with Mild or Severe Outcome
Authors: Voss Jameson D. , Skarzynski Martin , McAuley Erin M. , Maier Ezekiel J. , Gibbons Thomas , Fries Anthony C. , Chapleau Richard R. 
Published: December 2020

AbstractIntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered.MethodsWe downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID and evaluated whether variants improved prediction of reported severity beyond age and region. We also evaluated specific variants to determine the magnitude of association with severity and the frequency of these variants among the genomes.ResultsLogistic regression models that included viral genomic variants outperformed other models (AUC=0.91 as compared with 0.68 for age and gender alone; p<0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with ≤ 0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.ConclusionNumerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.
Risk Factors for Cerebral Palsy in Brazilian Children: A Case-Control Study
Authors: Peixoto Marcus Valerius da Silva , Duque Andrezza Marques , dos Santos Allan Dantas , Melo Almeida Lima Shirley Verônica , Nunes Ribeiro Caíque Jordan , Voci Silvia Maria , de Carvalho Susana , Antônio Prado Nunes Marco 
Published: December 2020

ABSTRACTBackgroundCerebral palsy is the main cause of physical disability in childhood.ObjectivesThis study analyzed prenatal and perinatal risk factors that contribute to cerebral palsy in Brazilian children.MethodsA case-control study was conducted with 2- to 10-year-old children in the city of Aracaju, Sergipe, Brazil. The cases were population-based, selected from the Primary Health Care services. The controls were selected from the database of the Brazilian Live Births Information System. Controls were paired with cases by gender, year, and hospital of birth.ResultsA total of 570 participants (114 cases and 456 controls) were studied. Most of the participants were male, with bilateral spastic cerebral palsy. Among the prenatal factors examined, the presence of congenital anomalies was significantly different between cases and controls (OR = 54.28, [95% CI 12.55, 234.86]). The analysis of perinatal factors revealed significant differences between cases and controls in low birth weight (OR = 3.8, [95% CI 2.34, 6.16]), preterm birth (OR = 2.31, [95% CI 1.41, 3.80]), and low Apgar scores (OR = 14.73, [95% CI 5.27, 41.15]).ConclusionsThe main prenatal and perinatal factors associated with cerebral palsy in our population were congenital anomalies, low Apgar scores, low birth weight, and preterm birth. The perinatal period had more risk factors, demanding a deeper study of their causes and of possible preventive measures.
Imputed Gene Expression Risk Scores: A Functionally Informed Component of Polygenic Risk
Authors: Pain Oliver , Glanville Kylie P. , Hagenaars Saskia , Selzam Saskia , Fürtjes Anna , Coleman Jonathan R. I. , Rimfeld Kaili , Breen Gerome , Folkersen Lasse , Lewis Cathryn M. 
Published: December 2020

AbstractBackgroundIntegration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results.MethodsThe predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study (TEDS). GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed SNP-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable tocis-regulated gene expression.ResultsGeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for Height (p=0.023) to 4% for Rheumatoid Arthritis (p=5.9×10-8). The proportion of SNP-based heritability attributable tocis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalised genes.ConclusionGeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.