bluuebunny/crossref_metadata_2025 huggingface dataset:
Promoting the propensity for blood donation through the understanding of its determinants.
Authors: Mugion Roberta Guglielmetti , Giovina Pasca Maria , Laura Di Pietro , Renzi Maria Francesca
Published: December 2020

Background. The paper is aimed at understanding the main antecedents related to the blood donation propensity related to both donors and non-donors. With our research, we are going to analyze the two perspectives in order to identify similarities and differences concentrating on the Italian context. Our findings can be useful also in the COVID-19 epoch in which blood availability continues to be a primary need for hospitals. Blood is a vital resource that strongly affects the efficacy and sustainability of every national healthcare system and the system's ability to achieve the goal of universal coverage. Methods. The purpose of this paper is to understand the main antecedents of citizens’ blood donation intention and the propensity to encourage communication about blood donation among both donors and non-donors. To fulfil this purpose, the Theory of Planned Behaviour is adopted as a theoretical lens. An empirical investigation was performed in Italy, adopting a mixed methods research design. First, a qualitative analysis was carried out through 30 in-depth interviews. Then, a survey was used to quantitatively investigate the intention to donate among both donors (N=173) and non-donors (N=87). A conceptual model was developed and tested through Structural Equation Modelling, developing a multi-group approach. Results. The present study confirms the relations proposed by the Theory of Planned Behaviour, even though some differences between the two groups are shown. The construct Information and Communication is crucial for donors, non-donors, and non-donor inhibitors. Service quality has an impact on the propensity to recommend and communicate the value of blood donation.Conclusion. This paper reveals the main differences between donor and non-donor perspectives. Fruitful insights for enhancing blood donation awareness are provided. Our findings can also be useful in the COVID-19 epidemic, in which there is more need for blood in hospitals.
A systematic and meta-analysis review on the diagnostic accuracy of antibodies in the serological diagnosis of COVID-19.
Authors: Vengesai Arthur , Midzi Herald , Kasambala Maritha , Mutandadzi Hamlet , Mduluza-Jok Tariro L. , Rusakaniko Simbarashe , Mutapi Francisca , Naicker Thajasvarie , Mdul Takafira
Published: December 2020

Background: Serological testing based on different antibody types are an alternative method being used to diagnose SARS-CoV-2 and has the potential of having higher diagnostic accuracy compared to the current gold standard rRT-PCR. Therefore, the objective of this review was to evaluate the diagnostic accuracy of IgG and IgM based point-of-care (POC) lateral flow immunoassay (LFIA), chemiluminescence enzyme immunoassay (CLIA), fluorescence enzyme-linked immunoassay (FIA) and ELISA systems that detect SARS-CoV-2 antigens.Method: A systematic literature search was carried out in PubMed, Medline complete and MedRxiv. Studies evaluating the diagnostic accuracy of serological assays for SARS-CoV-2 were eligible. Study selection and data-extraction were performed by two authors independently. QUADAS-2 checklist tool was used to assess the quality of the studies. The bivariate model and the hierarchical summary receiver operating characteristic curve model were performed to evaluate the diagnostic accuracy of the serological tests. Subgroup meta-analysis analyses was performed to explore the heterogeneity. Results: The pooled sensitivity for IgG, IgM and IgG-IgM based LFIA tests were 0.5856, 0.4637 and 0.6886, respectively compared to rRT-PCR method. The pooled sensitivity for IgG and IgM based CLIA tests were 0.9311 and 0.8516, respectively compared to rRT-PCR. The pooled sensitivity the IgG, IgM and IgG-IgM based ELISA tests were 0.8292, 0.8388 and 0.8531 respectively compared to rRT-PCR. All tests displayed high specificities ranging from 0.9693 to 0.9991. Among the evaluated tests, IgG based CLIA expressed the highest sensitivity signifying its accurate detection of the largest proportion of infections identified by rRT-PCR. ELISA and CLIA tests performed better in terms of sensitivity compared to LFIA. IgG based tests performed better compared to IgM except for the ELISA. Conclusions: We report that IgG-IgM based ELISA tests have the best overall diagnostic test accuracy. Moreover, irrespective of the method, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody type independently. Given the poor performances of the current LFIA devices there is need for more research on the development of highly sensitivity and specific POC LFIA that are adequate for most individual patient applications and attractive for large sero-prevalence studies.Systematic review registration: PROSPERO Registration Number is: CRD42020179112
Do Household Perceptions Influence Enrolment Decisions into Community-Based Health Insurance Schemes in Tanzania?
Authors: Kagaigai Alphoncina , Anaeli Amani , Mori Amani Thomas , Grepperud Sverre
Published: December 2020

Background: Several countries including Tanzania, have established voluntary non-profit insurance schemes, commonly known as community-based health insurance schemes (CBHIs), that typically target rural populations and the informal sector. This paper considers the importance of household perceptions towards CBHIs in Tanzania and their role in explaining the enrolment decision of households. Methods: This was a cross-sectional household survey that involved 722 households located in Bahi and Chamwino districts in the Dodoma region. A three-stage sampling procedure was used, and the data were analyzed using both factor analysis (FA) and principal component analysis (PCA). Statistical tests such as Bartlett’s test of sphericity, Kaiser-Meyer-Olkin (KMO) for sampling adequacy, and Cronbach’s alpha test for internal consistency and scale reliability were performed to examine the suitability of the data for PCA and FA. Finally, multivariate logistic regressions were run to determine the associations between the identified factors and the insurance enrolment status. Results: The PCA identified seven perception factors while FA identified four factors. The quality of healthcare services, preferences (social beliefs), and accessibility to insurance scheme administration (convenience) were the most important factors identified by the two methods. Multivariate logistic regressions showed that the factors identified from the two methods differed somewhat in importance when considered as independent predictors of the enrollment status. The most important perception factors in terms of strength of association (odds ratio) and statistical significance were accessibility to insurance scheme administration (convenience), preferences (beliefs), and the quality of health care services. However, age and income were the only socio-demographic characteristics that were statistically significant. Conclusion: Household perceptions were found to influence households’ decisions to enroll in CBHIs. Policymakers should recognize and consider these perceptions when designing policies and programs that aim to increase the enrolment into CBHIs.
Prediction of risk factors of bronchial mucus plugs in children with Mycoplasma pneumoniae pneumonia
Authors: zhang Jiahui , Wang Ting , Ji Wei , Yan Yongdong , Sun Zhichao , Tan Jiahong , Wu Jinfeng , Huang Li , Chen Zhengrong , Li Rongrong
Published: December 2020

Background: Recently, many cases of pneumonia in children with Mycoplasma pneumoniae infection have been shown to have varying degrees of intrabronchial mucus plug formation. The clinical, laboratory, radiological characteristics, and treatment of patients with Mycoplasma infection are analyzed in this study. The risk factors for M. pneumoniae pneumonia (MPP) mucus plug formation in children are explored, and a risk factor scoring system is established.Methods: MPP patients treated with bronchoscopy were retrospectively enrolled in the study from February 2015 to December 2019. The children were divided into a mucus plug group and a control group according to the presence or absence of mucus plug formation. The clinical, laboratory, radiological characteristics, and treatment of the two groups of children were compared. Univariate and multivariate logistic regression models were used to identify the risk factors for MPP mucus plug formation. The receiver operating characteristic (ROC) curve was drawn to evaluate the regression model and establish the MPP mucous plug risk factor scoring system.Results: A univariate analysis showed that the children in the mucous group were older and had a longer fever duration, longer hospital stay, higher fever peak, more cases of wheezing symptoms and allergies, and azithromycin or corticosteroids were administered later. In addition, neutrophil, C-reactive protein (CRP), lactate dehydrogenase (LDH), D-dimer (DD), sputum MP-DNA copy number, and total immunoglobulin A (IgA) levels were higher, while prealbumin (PA) levels were lower. The ROC curve analysis showed that children with MPP had PA ≤144.5 mg/L, had used corticosteroids during the course of the illness of ≥4.5 days, CRP ≥12.27 mg/L, an LDH≥462.65 U/L, and there was a possibility of intra-airway mucus formation. The independent risk factors were scored according to their odds ratio (OR) value. Among the 255 children with MPP, the high-risk group had 44 (83.02%) mucus plugs out of 53; the middle-risk group had 35 (34.3%) mucus plugs out of 102; and the low-risk group had 11 (11%) mucus plugs out of 100.Conclusions: PA levels, timing of corticosteroid use (use in the first few days), CRP levels, and LDH levels were independent risk factors for MPP mucus plug formation. This provides a basis for the early identification of MPP in children combined with mucus plug formation.
Genomic analysis of Helicobacter himalayensis sp. nov. isolated from Marmota himalayana
Authors: Hu Shouhui , Niu Lina , Wu Lei , Zhu Xiaoxue , Cai Yu , Jin Dong , Yan Linlin , Zhao Fan
Published: December 2020

Background: Helicobacter himalayensis was isolated from Marmota himalayana in the Qinghai-Tibet Plateau, China, and is a new non-H. pylori species, with unclear taxonomy, phylogeny, and pathogenicity. Results: A comparative genomic analysis was performed between the H. himalayensis type strain 80(YS1)T and other the genomes of Helicobacter species present in the National Center for Biotechnology Information (NCBI) database to explore the molecular evolution and potential pathogenicity of H. himalayensis. H. himalayensis 80(YS1)T formed a clade with H. cinaedi and H. hepaticus that was phylogenetically distant from H. pylori. The H. himalayensis genome showed extensive collinearity with H. hepaticus and H. cinaedi. However, it also revealed a low degree of genome collinearity with H. pylori. The genome of 80(YS1)T comprised 1,829,936 bp, with a 39.89% GC content, a predicted genomic island, and 1,769 genes. Comparatively, H. himalayensis has more genes for functions in “cell wall/membrane/envelope biogenesis” and “coenzyme transport and metabolism” sub-branches than the other compared helicobacters, and its genome contained 42 virulence factors genes, including that encoding cytolethal distending toxin (CDT). Conclusions: We characterized the H. himalayensis 80(YS1)T genome, its phylogenetic position, and its potential pathogenicity. However, further understanding of the pathogenesis of this potentially pathogenic bacterium is required, which might help to manage H. himalayensis-induced diseases.
Drug-Induced Cell Viability Prediction from LINCS-L1000 through WRFEN-XGBoost Algorithm
Authors: Lu Jiaxing , Chen Ming , Qin Yufang
Published: December 2020

Background: Predicting the drug response of the cancer diseases through the cellular perturbation signatures under the action of specific compounds is very important in personalized medicine. In the process of testing drug responses to the cancer, traditional experimental methods have been greatly hampered by the cost and sample size. At present, the public availability of large amounts of gene expression data makes it a challenging task to use machine learning methods to predict the drug sensitivity. Results: In this study, we introduced the WRFEN-XGBoost cell viability prediction algorithm based on LINCS-L1000 cell signatures. We integrated the LINCS-L1000, CTRP and Achilles datasets and adopted a weighted fusion algorithm based on random forest and elastic net for key gene selection. Then the FEBPSO algorithm was introduced into XGBoost learning algorithm to predict the cell viability induced by the drugs. The proposed method was compared with some new methods, and it was found that our model achieved good results with 0.83 Pearson correlation. At the same time, we completed the drug sensitivity validation on the NCI60 and CCLE datasets, which further demonstrated the effectiveness of our method. Conclusions: The results showed that our method was conducive to the elucidation of disease mechanisms and the exploration of new therapies, which greatly promoted the progress of clinical medicine.
Trends in the use of health services and their relationship with multimorbidity in Brazil, 1998–2013
Authors: de Souza Ana Sara Semeão , Braga Jose Ueleres
Published: December 2020

Background: Chronic non-communicable diseases (NCDs) are the leading cause of multimorbidity. Access to effective and equitable health services that meet NCDs’ needs is still limited in many countries. This constitutes the main barrier to coping with NCDs, especially in minimising the suffering of those who are already sick. The present study aimed to identify the relationship between multimorbidity and the use of different health services in Brazil from 1998 to 2013. Methods: This is a panel study using data from the health supplement of the National Household Sample Survey of 1998, 2003 and 2008 and data from the National Health Survey carried out in 2013. Three health service utilization outcomes were considered: 1. search for health services in the last 15 days (excluding dental services), 2. medical consultation in the previous 12 months and 3. hospitalisations over the last 12 months. Multimorbidity was assessed by counting the number of morbidities from a list of 10 morbidities. Poisson regression models stratified by sex were used to estimate the crude and adjusted prevalence ratios and their respective 95% confidence intervals for each outcome of health service use and multimorbidity, per year. Results: There was an increase in the prevalence of demand for health services and medical consultations in the last 12 months between 1998 and 2013, regardless of the multimorbidity classification. The prevalence of hospitalisations has decreased over the study period and increased twofold in individuals with multimorbidity. Having multimorbidity increased the use of health services for the three outcomes under the study, being more expressive among men. Conclusions: This study found that individuals with multimorbidity have higher levels of use of health services. Better understand the multimorbidity epidemiology and the associated impacts on the use and costs of health services can increase the quality of care provided to these patients and reduce rising health care costs.
Why do healthcare professionals fail to escalate as per the Early Warning System (EWS) protocol? A qualitative evidence synthesis of the barriers and facilitators of escalation
Authors: Neill Sinead M O , Clyne Barbara , Bell Miriam , Casey Avilene , Leen Brendan , Smith Susan M , Ryan Mairin , O’Neill Michelle
Published: December 2020

Background: Early warning systems (EWSs) are used to assist clinical judgment in the detection of acute deterioration to avoid or reduce adverse events including unanticipated cardiopulmonary arrest, admission to the intensive care unit and death. Sometimes healthcare professionals (HCPs) do not trigger the alarm and escalate for help according to the EWS protocol and it is unclear why this is the case. The aim of this qualitative evidence synthesis was to answer the question ‘why do HCPs fail to escalate care according to EWS protocols?’ The findings will inform the update of the National Clinical Effectiveness Committee (NCEC) National Clinical Guideline No. 1 Irish National Early Warning System (INEWS). Methods: A systematic search of the published and grey literature was conducted (until February 2018). Data extraction and quality appraisal were conducted by two reviewers independently using standardised data extraction forms and quality appraisal tools. A thematic synthesis was conducted by two reviewers of the qualitative studies included and categorized into the barriers and facilitators of escalation. GRADE CERQual was used to assess the certainty of the evidence.Results: Eighteen studies incorporating a variety of HCPs across seven countries were included. The barriers and facilitators to the escalation of care according to EWS protocols were developed into five overarching themes: Governance, Rapid Response Team (RRT) Response, Professional Boundaries, Clinical Experience, and EWS parameters. Barriers to escalation included: Lack of Standardisation, Resources, Lack of accountability, RRT behaviours, Fear, Hierarchy, Increased Conflict, Over confidence, Lack of confidence, and Patient variability. Facilitators included: Accountability, Standardisation, Resources, RRT behaviours, Expertise, Additional support, License to escalate, Bridge across boundaries, Clinical confidence, Empowerement, Clinical judgment, and a tool for detecting deterioration. These are all individual yet inter-related barriers and facilitators to escalation. Conclusions: The findings of this qualitative evidence synthesis provide insight into the real world experience of HCPs when using EWSs. This in turn has the potential to inform policy-makers and HCPs as well as hospital management about emergency response system-related issues in practice and the changes needed to address barriers and facilitators and improve patient safety and quality of care.
Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling
Authors: Yamawaki Tracy M , Lu Daniel R , Ellwanger Daniel C , Bhatt Dev , Manzanillo Paolo , Zhou Hong , Yoon Oh-Kyu , Homann Oliver , Wang Songli , Arias Vanessa , Li Chi-Ming Kevin
Published: December 2020

Background: Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results: Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5’ v1 and 3’ v3 methods. We demonstrate that these methods have fewer drop-out events which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures.Conclusion: Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.
Evidence of coupled oscillator to wave packet dynamics in human brain
Authors: Pal Mayukha , . Neeraj , Panigrahi Prasanta
Published: December 2020

Clear evidence of oscillator dynamics to wave packet collapse and revival in the brain EEG signals is demonstrated for the first time, with distinct differences in healthy individuals and epileptic patients. The low frequency components exhibit single oscillator type behavior in a phase-space description, with the potentials as coordinates and their instantaneous changes as the corresponding velocities. The closed paths reveal periodic motion, well described by one linear oscillator or possibly coupled ones with limit cycle dynamics and synchronization at the macroscopic level. The epileptic patients reveal dynamical features of bi-stability, originating from non-linearity, a prominent feature in the signals from the epileptogenic zone and much enhanced during the periods of seizure. Analogy from the phase-space of oscillator dynamics reveals dominance of potential energy in the signals from the epileptogenic zone, as also in the patients during occurrence of seizure. The acceleration, arising from the change of velocity, is found to be particularly strong in epileptic patients, when the phase space shows bi-stability and bursty behavior. Wave behavior with characteristics of superposition emerges in the frequency range corresponding to the observed unstable periodic orbits, that appear at the boundary of alpha and beta waves of 8-14Hz, centered at 10Hz. A modulated carrier wave is observed for all subjects at 18Hz, higher in width for patients. Coherent wave dynamics, with interference playing a key role in the wave packet collapse and revival, is observed starting from 18Hz, with the coherence getting significantly enhanced around 40-45Hz. Mechanism of intra frequency energy transfer is shown to be neutral turbulence.
Experiment and fitting calculation of migration critical velocity of small-sized sediment particles erosion in rainwater pipeline
Authors: Liu Cuiyun , Chen Yanzhi , Yang Yuting , Zhou Jingqin , Wang Yiyang , Zhou Jie , Zhang Xiaohua
Published: December 2020

The migration critical velocity of small-sized sediment particles was investigated through experiments under different particle sizes, pipe wall roughness, and sediment thickness. Such experiments were carried out to simulate the erosion process of small-sized sediment particles in a rainwater pipeline during rainfall. The mathematical models were established via quadratic fitting to calculate the critical velocity of migration. Results showed that small particles had powerful cohesive force, and aggregates had strong erosion resistance. So, for the small-sized particles (in the range of 0.33–0.83 mm), the smaller the particle size, the larger the critical velocity. When the pipe wall roughness was large, the ‘starting’ particle resistance was high. A large flow dynamic was needed to overcome such resistance. Thus, the critical velocity was great. The critical velocity was also large when the sediment thickness was large. The difference rate between the critical velocity calculated by mathematical models and the measured value was within the range of −3.60% to 5.33% and had good consistency. Under the research conditions, the critical velocity ranges of the four commonly used pipes; namely, plexiglass, steel/PVC, galvanized/clay, and cast iron pipes, were calculated.
Post-translational Modifications of bZIP Transcription Factors in Abscisic Acid Signaling and Drought Responses
Authors: Joo Hyunhee , Baek Woonhee , Lim Chae Woo , Lee Sung Chul
Published: December 2020

Under drought stress, plants have developed various mechanisms to survive in the reduced
water supply, of which the regulation of stress-related gene expression is responsible for several
transcription factors. The basic leucine zippers (bZIPs) are one of the largest and most diverse
transcription factor families in plants. Among the 10 Arabidopsis bZIP groups, group A bZIP transcription
factors function as a positive or negative regulator in ABA signal transduction and
drought stress response. These bZIP transcription factors, which are involved in the drought response,
have also been isolated in various plant species such as rice, pepper, potato, and maize. Recent
studies have provided substantial evidence that many bZIP transcription factors undergo the
post-translational modifications, through which the regulation of their activity or stability affects
plant responses to various intracellular or extracellular stimuli. This review aims to address the modulation
of the bZIP proteins in ABA signaling and drought responses through phosphorylation,
ubiquitination and sumoylation.
IL-8 and MCP-1 Impact on Tau Phosphorylation and Phosphatase Activity
Authors: Vaz Margarida , Domingues Catarina , Trindade Dário , Barra Cátia , Oliveira Joana M. , Rosa Ilka M. , da Cruz e Silva Odete A.B. , Henriques Ana G.
Published: December 2020

Background:

Chronic inflammation is a feature of Alzheimer´s disease (AD), resulting in
excessive production of inflammatory mediators that can lead to neuroinflammation, contributing to
alterations in Aβ production and deposition as Senile Plaques (SPs), and to neurofibrillary tangles
(NFTs) formation, due to hyperphosphorylated Tau protein.

Objective:

This work addressed the impact of the interleukin-8 (IL-8) and monocyte chemoattractant
protein-1 (MCP-1), two chemokines, on Tau phosphorylation; and also evaluated the chemokines’ levels
in plasma using samples from a regional cohort.

Methods:

Human neuronal SH-SY5Y cells exposed to IL-8 and MCP-1 chemokines were monitored for
their protein and phosphorylated protein levels by western blotting analysis. A serine/threonine protein
phosphatase (PPs) activity assay was employed to monitor PPs activity. Subsequently, flow cytometry
was used to monitor chemokines levels in plasma samples from individuals with cognitive deficits.

Results:

Chemokines’ exposure resulted only in minor cytotoxicity effects on SH-SY5Y, and in
increased Tau phosphorylation, particularly at the S396 residue. Tau phosphorylation correlated with
PPs inhibition and was consistent with GSK3β phosphorylation-mediated inhibition. Subsequent analysis
of plasma from individuals with cognitive deficits showed that IL-8 levels were decreased.

Conclusion:

Data shows that both chemokines tested can exert an effect on GSK3β phosphorylation and
modulate PPs activity, potentially resulting in increased Tau phosphorylation and subsequent NFTs formation.
One can deduce that increased chemokines stimulation during chronic inflammation can exacerbate
this event. The work contributes to a better understanding of the mode of action of these chemokines
on AD pathogenesis and opens novel research avenues.
Multimodality Imaging in Acute Ischemic Stroke
Authors: Zameer Shahla , Siddiqui Ayesha Shamim , Riaz Ramish
Published: December 2020

Stroke is the most common cause of mortality and morbidity worldwide. The prognosis
of stroke depends upon the area affected and its early treatment. Time is of the essence in the care
of stroke patients as it is estimated that approximately 1.9 million neurons, 14 billion synapses, and
12 km myelinated nerve fibers are lost per minute. Therefore, early diagnosis and prompt treatment
are necessary. The primary goal of imaging in acute stroke is to diagnose the underlying cause, estimate
the area affected, predict response towards thrombolytic therapy and to exclude the conditions
mimicking stroke. With advancements in radiology, multiple imaging modalities are available
for diagnosis and predicting prognosis. None of them is considered alone to be perfect. In this
era of multimodality imaging, the decision of choosing appropriate techniques depends upon purpose
and availability. Non-Contrast Computed Tomography is time effective, and helps in excluding
other causes, Trans Cranial Doppler is time-effective and cost-effective with wide availability,
however, is operator dependent and less sensitive. It holds a great future in sonothrombolysis. Magnetic
Resonance Imaging is so far considered to be the most superior one in terms of early diagnosis,
planning for interventional treatment and predicting the response of treatment. However, it is
limited due to high cost and lack of availability. The current review gives a detailed account of all
imaging modalities available for imaging stroke and their associated pros and cons.
PECS vs. iPad Intervention for Students with Autism Spectrum Disorders: A Literature Review
Authors: Ariwijaya Toni
Published: December 2020

Autism Spectrum Disorders (ASD) refers to a neurodevelopmental disorder that affects communication, behaviour and socialization of the individuals diagnosed with ASD. In children, ASD is considered as a high incidence disability since it affects one in eight children. In regard to functional communication skills of the children, effective augmentative or alternative communication process and device is highly important to facilitate positive outcomes. Both Picture Exchange Communication System (PECS) and the iPad with its communication applications are considered emerging treatment children with autism spectrum disorders (ASD). The purpose of this literature review is to compare the effectiveness of low tech intervention (through the utilization of PECS) and high tech intervention (through the utisation of iPad). The study was conducted by selecting electronic articles from several databases which were published between 2008-2018. The findings show that PECS is highly effective for increasing intentional communication skills and independence in requesting and making decisions as well as beneficial for non-English speakers. Meanwhile, iPad-based intervention is beneficial to solve children’s literacy problems, to reduce stressors during interventions, and to increase the children’s effective intra-verbal responses. It is then suggested that teachers, parents and care givers employ the combination of both low tech and high tech interventions as combining the two will lead to better outcomes.
Определение модуля упругости композиционной керамики на основе SiC
Authors: Кияшко М.В. , Гринчук П.С. , Кузнецова Т.А. , Крень А.П. , Abuhimd H.M.
Published: December 2020

Young's modulus of composite heterophase SiC-ceramics with different phase ratios is determined on the base of two independent methods. The Voight-Reuss-Hill model is demonstrated to be applicable for calculation of the Young's modulus using measured characteristics of ceramic components. The calculation results are close to the results of independent dynamic indantation measurements. Lower uncertainty of Young's modulus is shown to be the advantage of the calculation method. At the same time, the application of this method requires additional measurements of ceramics composition and mechanical properties of all components.
Optimizing an Obesity Treatment Using the Multiphase Optimization Strategy Framework: Protocol for a Randomized Factorial Trial
Authors: Bennett Gary G , Steinberg Dori , Bolton Jamiyla , Gallis John A , Treadway Cayla , Askew Sandy , Kay Melissa C , Pollak Kathryn I , Turner Elizabeth L
Published: December 2020

Background

Effective weight loss interventions exist, yet few can be scaled up for wide dissemination. Further, none has been fully delivered via text message. We used the multiphase optimization strategy (MOST) to develop multicomponent interventions that consist only of active components, those that have been experimentally determined to impact the chosen outcome.

Objective

The goal of this study is to optimize a standalone text messaging obesity intervention, Charge, using the MOST framework to experimentally determine which text messaging components produce a meaningful contribution to weight change at 6 months.

Methods

We designed a 6-month, weight loss texting intervention based on our interactive obesity treatment approach (iOTA). Participants are randomized to one of 32 experimental conditions to test which standalone text messaging intervention components produce a meaningful contribution to weight change at 6 months.

Results

The project was funded in February 2017; enrollment began in January 2018 and data collection was completed in June 2019. Data analysis is in progress and first results are expected to be submitted for publication in 2021.

Conclusions

Full factorial trials are particularly efficient in terms of cost and logistics when leveraged for standalone digital treatments. Accordingly, MOST has the potential to promote the rapid advancement of digital health treatments. Subject to positive findings, the intervention will be low cost, immediately scalable, and ready for dissemination. This will be of great potential use to the millions of Americans with obesity and the providers who treat them.

Trial Registration

ClinicalTrials.gov NCT03254940; https://clinicaltrials.gov/ct2/show/NCT03254940

International Registered Report Identifier (IRRID)

RR1-10.2196/19506
Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives
Authors: Lennartz Simon , Dratsch Thomas , Zopfs David , Persigehl Thorsten , Maintz David , Große Hokamp Nils , Pinto dos Santos Daniel
Published: December 2020

Background

Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients’ opinions on the use of AI in medicine are scarce.

Objective

This study aimed to investigate patients’ opinions on the use of AI in different aspects of the medical workflow and the level of control and supervision under which they would deem the application of AI in medicine acceptable.

Methods

Patients scheduled for computed tomography or magnetic resonance imaging voluntarily participated in an anonymized questionnaire between February 10, 2020, and May 24, 2020. Patient information, confidence in physicians vs AI in different clinical tasks, opinions on the control of AI, preference in cases of disagreement between AI and physicians, and acceptance of the use of AI for diagnosing and treating diseases of different severity were recorded.

Results

In total, 229 patients participated. Patients favored physicians over AI for all clinical tasks except for treatment planning based on current scientific evidence. In case of disagreement between physicians and AI regarding diagnosis and treatment planning, most patients preferred the physician’s opinion to AI (96.2% [153/159] vs 3.8% [6/159] and 94.8% [146/154] vs 5.2% [8/154], respectively; P=.001). AI supervised by a physician was considered more acceptable than AI without physician supervision at diagnosis (confidence rating 3.90 [SD 1.20] vs 1.64 [SD 1.03], respectively; P=.001) and therapy (3.77 [SD 1.18] vs 1.57 [SD 0.96], respectively; P=.001).

Conclusions

Patients favored physicians over AI in most clinical tasks and strongly preferred an application of AI with physician supervision. However, patients acknowledged that AI could help physicians integrate the most recent scientific evidence into medical care. Application of AI in medicine should be disclosed and controlled to protect patient interests and meet ethical standards.
Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study (Preprint)
Authors: Goyal Dev , Guttag John , Syed Zeeshan , Mehta Rudra , Elahi Zahoor , Saeed Mohammed
Published: December 2020

BACKGROUND

Patients’ choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital choices.

OBJECTIVE

This paper aims to compare differences in outcomes and costs between hospitals ranked using popular internet-based consumer ratings, quality stars, reputation rankings, average volumes, average outcomes, and precision machine learning–based rankings for hospital settings performing hip replacements in a large metropolitan area.

METHODS

Retrospective data from 4192 hip replacement surgeries among Medicare beneficiaries in 2018 in a the Chicago metropolitan area were analyzed for variations in outcomes (90-day postprocedure hospitalizations and emergency department visits) and costs (90-day total cost of care) between hospitals ranked through multiple approaches: internet-based consumer ratings, quality stars, reputation rankings, average yearly surgical volume, average outcome rates, and machine learning–based rankings. The average rates of outcomes and costs were compared between the patients who underwent surgery at a hospital using each ranking approach in unadjusted and propensity-based adjusted comparisons.

RESULTS

Only a minority of patients (1159/4192, 27.6% to 2078/4192, 49.6%) were found to be matched to higher-ranked hospitals for each of the different approaches. Of the approaches considered, hip replacements at hospitals that were more highly ranked by consumer ratings, quality stars, and machine learning were all consistently associated with improvements in outcomes and costs in both adjusted and unadjusted analyses. The improvement was greatest across all metrics and analyses for machine learning–based rankings.

CONCLUSIONS

There may be a substantive opportunity to increase the number of patients matched to appropriate hospitals across a broad variety of ranking approaches. Elective hip replacement surgeries performed at hospitals where patients were matched based on patient-specific machine learning were associated with better outcomes and lower total costs of care.
Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study (Preprint)
Authors: Richter Maike Frederike , Storck Michael , Blitz Rogério , Goltermann Janik , Seipp Juliana , Dannlowski Udo , Baune Bernhard T , Dugas Martin , Opel Nils
Published: December 2020

BACKGROUND

Predictive models have revealed promising results for the individual prognosis of treatment response and relapse risk as well as for differential diagnosis in affective disorders. Yet, in order to translate personalized predictive modeling from research contexts to psychiatric clinical routine, standardized collection of information of sufficient detail and temporal resolution in day-to-day clinical care is needed. Digital collection of self-report measures by patients is a time- and cost-efficient approach to gain such data throughout treatment.

OBJECTIVE

The objective of this study was to investigate whether patients with severe affective disorders were willing and able to participate in such efforts, whether the feasibility of such systems might vary depending on individual patient characteristics, and if digitally acquired assessments were of sufficient diagnostic validity.

METHODS

We implemented a system for longitudinal digital collection of risk and symptom profiles based on repeated self-reports via tablet computers throughout inpatient treatment of affective disorders at the Department of Psychiatry at the University of Münster. Tablet-handling competency and the speed of data entry were assessed. Depression severity was additionally assessed by a clinical interviewer at baseline and before discharge.

RESULTS

Of 364 affective disorder patients who were approached, 242 (66.5%) participated in the study; 88.8% of participants (215/242) were diagnosed with major depressive disorder, and 27 (11.2%) had bipolar disorder. During the duration of inpatient treatment, 79% of expected assessments were completed, with an average of 4 completed assessments per participant; 4 participants (4/242, 1.6%) dropped out of the study prematurely. During data entry, 89.3% of participants (216/242) did not require additional support. Needing support with tablet handling and slower data entry pace were predicted by older age, whereas depression severity at baseline did not influence these measures. Patient self-reporting of depression severity showed high agreement with standardized external assessments by a clinical interviewer.

CONCLUSIONS

Our results indicate that digital collection of self-report measures is a feasible, accessible, and valid method for longitudinal data collection in psychiatric routine, which will eventually facilitate the identification of individual risk and resilience factors for affective disorders and pave the way toward personalized psychiatric care.
Academic Nurse-Managed Community Clinics Transitioning to Telehealth: Case Report on the Rapid Response to COVID-19 (Preprint)
Authors: Sutter Rebecca , Cuellar Alison E , Harvey Megan , Hong Y Alicia
Published: December 2020

BACKGROUND

In response to the COVID-19 pandemic, many health care organizations have adopted telehealth. The current literature on transitioning to telehealth has mostly been from large health care or specialty care organizations, with limited data from safety net or community clinics.

OBJECTIVE

This is a case report on the rapid implementation of a telehealth hub at an academic nurse-managed community clinic in response to the national COVID-19 emergency. We also identify factors of success and challenges associated with the transition to telehealth.

METHODS

This study was conducted at the George Mason University Mason and Partners clinic, which serves the dual mission of caring for community clinic patients and providing health professional education. We interviewed the leadership team of Mason and Partners clinics and summarized our findings.

RESULTS

Mason and Partners clinics reacted quickly to the COVID-19 crisis and transitioned to telehealth within 2 weeks of the statewide lockdown. Protocols were developed for a coordination hub, a main patient triage and appointment telephone line, a step-by-step flowchart of clinical procedure, and a team structure with clearly defined work roles and backups. The clinics were able to maintain most of its clinical service and health education functions while adapting to new clinic duties that arose during the pandemic.

CONCLUSIONS

The experiences learned from the Mason and Partners clinics are transferable to other safety net clinics and academic nurse-led community clinics. The changes arising from the pandemic have resulted in sustainable procedures, and these changes will have a long-term impact on health care delivery and training.
Behavior Change Techniques in Popular Mobile Apps for Smoking Cessation in France: Content Analysis (Preprint)
Authors: Bustamante Luz Adriana , Gill Ménard Cédric , Julien Sabrina , Romo Lucia
Published: December 2020

BACKGROUND

The mobile app market differs from country to country, and to date, no previous review of the content quality of smoking cessation apps has been conducted in France.

OBJECTIVE

This study aimed to examine the general quality of the most popular smoking cessation apps in France and also determine the degree to which apps adhere to established behavioral and cognitive techniques (BCTs) proven effective in clinical practice.

METHODS

A systematic research of smoking cessation apps was conducted in both the Google Play Store and Apple Store in the French market. The general quality of popular apps was rated with the Mobile App Rating Scale (MARS), and the therapeutic quality was assessed with the ratio of adherence of the behavior change technique taxonomy for smoking cessation treatment.

RESULTS

A total of 14 mobile apps met all the inclusion criteria of the content analysis. The interrater reliability varied from “substantial” (0.79) to “almost perfect” (0.9) for the two measures. The mean MARS score was 3.5 out of 5 (median 3.6, IQR 0.6 [3.2-3.8]). The findings suggest that popular apps focus primarily on the functionality dimension of the MARS scale (4.2/5). The mean number of BCTs was 22, with a large difference between apps (minimum 4, maximum 38). At least half of the apps addressed motivation (8.8/14, 63%) and advised on using behavioral skills in order to quit smoking or stay a nonsmoker (8.7/14, 62%). However, only a handful of apps gathered important information (5.9/14, 42%) in order to deliver proper advice regarding the use of approved medication or the implementation of behavioral techniques (4.3/14, 31%). The mean MARS score was positively correlated with the price (r=0.70, P=.007) and the number of BCTs used (r=0.67, P=.01). User rating was not correlated with any quality scale (P=.67).

CONCLUSIONS

The content quality of popular smoking cessation apps in France varied by app type and price. Most popular apps propose in general good quality content but lack implementation of evidence-based BCTs associated with effectiveness on smoking cessation treatment. Further research is needed to evaluate the improvement in the content quality of smoking cessation apps in France.
Preliminary Estimates of Years of Life Lost (YLL) Due to COVID-19 in India (Preprint)
Authors: Indrayan Abhaya , Mishra Aman , Pathak Mona
Published: December 2020

BACKGROUND

More than 7 million cases of COVID have been detected in India by the middle of October 2020 and more than 100 thousand deaths have occurred.It is not known yet how much years of life are being lost due to this disease.

OBJECTIVE

In this communication, we present an estimate of the years of life lost (YLL) due to COVID-19 so far and the projection for the full year so that the health damage by this new disease can be compared with some other ailments such as road injuries.

METHODS

The YLL by one premature death is the expectation of life at that age. To calculate YLL, the age-wise distribution of COVID cases and deaths was obtained from various sources. Similar calculations were done for the general population from all causes for comparison.

RESULTS

A total of more than 2 million years of life have already lost due to COVID-19 and the pattern indicates that we may end up with nearly 4 million YLL due to this disease in India. This is nearly 20 years lost per COVID death, 303 years lost per 1000 cases of COVID, and about 3 years lost per 1000 population in a full year. The age-group 50-59 years has been particularly affected. Other important findings are summarized as key messages.

CONCLUSIONS

The years of life lost so far and anticipated in full-year are enormous but may still be lower compared with some other causes such as road injuries.