bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of sample temperature variations during sample preparation on measured blood ethanol concentration
Authors: Kosecki Patrick Allan , Brooke Phillip , Canonico Erika 
Published: June 2021

AbstractSince the accuracy of headspace gas chromatographic analysis of blood for ethanol concentration has been so well established over the past several decades, it has become commonplace in court proceedings to attack preanalytical handling of the blood samples including the lack of measuring sample temperature prior to sample preparation. The impact on measured ethanol concentration of allowing refrigerated (~4℃) samples varying amounts of time to equilibrate with room temperature, 24, 4, 3, 2, and 1 h, prior to sample preparation was evaluated. Samples were diluted 1:10 with an internal standard using a diluter/dispenser and analyzed using headspace gas chromatography. The mean ethanol concentration measured for the sixteen samples at each of the five equilibration times was 0.153 g/dl. The F‐critical from the one‐way ANOVA was 2.4937. The calculated F value was 0.4209. Additionally, the effect on measured ethanol concentration of having calibrators at different temperatures than case samples was investigated. Three groups were analyzed: all calibrators, controls, and samples given 24 h to equilibrate with room temperature, all calibrators, controls, and samples prepared immediately after removal from refrigeration, and calibrators sampled immediately after removal from refrigerator with samples and controls allowed 24 h to equilibrate with room temperature. The mean ethanol concentration measured for the thirty blood samples in each of the three groups was 0.197 g/dl. The F‐critical from the one‐way ANOVA was 3.1013. The calculated F value was 0.0188. Measured ethanol concentrations were insensitive to the variations in preanalytical conditions evaluated in this study.
Dorsal and ventral striatum activity in individuals with buying‐shopping disorder during cue‐exposure: A functional magnetic resonance imaging study
Authors: Trotzke Patrick , Starcke Katrin , Pedersen Anya , Brand Matthias 
Published: June 2021

AbstractBackground and AimsBuying‐shopping disorder (BSD) is a clinical condition in which individuals lose control over their buying behaviour and continue buying despite negative consequences such as indebtedness, loss of family and friends. BSD has been considered a behavioural addiction and first studies provide evidence for cue‐reactivity and craving as potential pathomechanisms. The current study aimed at investigating neural correlates of cue‐reactivity and craving in individuals with BSD using functional magnetic resonance imaging (fMRI).MethodsA cue‐reactivity paradigm comprising individualised shopping‐related and control cues was applied in n = 18 individuals diagnosed with BSD and n = 18 gender, age, and handedness matched control participants using fMRI. Outside the scanner, symptoms of BSD and craving reactions towards shopping (before and after the cue‐reactivity paradigm) were assessed via questionnaires.FindingsHigher subjective craving reactions towards shopping, prior and after exposure to shopping cues, were observed in individuals with BSD compared to control participants. Consistent with studies in addiction research, we found increased activations in the dorsal striatum for individuals with BSD compared to control participants during exposure to shopping cues. Activity in the ventral striatum was associated with symptoms of BSD in affected individuals, but not in control participants.ConclusionsConsistent with studies investigating cue‐reactivity in substance‐use and behavioural addictions, the association between cue‐exposure and activities in reward‐related brain structures such as the dorsal and ventral striatum in BSD participants may contribute to a neural explanation of why individuals experience irresistible urges to buy and lose control over their behaviour.
Comorbidity before and after a diagnosis of inflammatory bowel disease
Authors: Bernstein Charles N. , Nugent Zoann , Shaffer Seth , Singh Harminder , Marrie Ruth Ann 
Published: June 2021

SummaryBackgroundComorbidity is an important predictor of how disease course in inflammatory bowel (IBD) evolves.AimsTo determine pre‐diagnosis relative rates (RR) and post‐diagnosis hazard ratios (HR) of component diseases of the Charlson Comorbidity Index (CCI) in a cohort study of persons with IBD.MethodsThe University of Manitoba IBD Epidemiology Database includes all Manitobans with IBD from 1 April 1984 through 31 March 2018 and matched controls. All outpatient physician claims and hospital discharge abstracts were searched for diagnostic codes for CCI component diseases. Some diseases were collapsed into one group such that we assessed 12 conditions. We report the RR of these conditions prior to IBD and the incidence of these diagnoses after IBD. Using Cox proportional hazards regression we report post‐diagnosis HR. Confidence intervals were adjusted for Bonferroni correction.ResultsThe RR of cardiovascular diseases, peripheral vascular diseases, chronic pulmonary diseases, connective tissue disease/rheumatic diseases, renal disease, liver diseases, peptic ulcer disease, and cancer were all increased prior to diagnoses of IBD compared to controls. All comorbidities were increased post IBD diagnosis. The increased HR for dementia in persons with Crohn's disease was a concerning novel finding. The increased association with paraplegia/hemiplegia was unexpected. For all comorbidities, except diabetes, the age at diagnosis was younger in IBD than controls.ConclusionsPersons with IBD have a higher comorbidity burden than persons without IBD. Optimal care plans for persons with IBD should include an assessment for other comorbidities that include just about every other organ system.
Managing the uncertainty associated with being a parent of a child with a long‐term disability
Authors: Reeder Jim , Morris Jane 
Published: June 2021

AbstractAimThis article aims to explore the important theme of uncertainty and how this is experienced by parents of children with long‐term disability or illness. It also aims to consider how health professionals might offer support to parents to manage their uncertainty without taking away their hope.BackgroundBefore taking up their role in a collaborative partnership with health professionals, parents first need to ‘get used’ to being a parent of a child with long‐term disability. During this time, parents experience considerable uncertainty and employ different strategies to try to manage this.MethodsThe study was guided by a constructivist grounded theory methodology. This involved an iterative process of repeated cycles of data collection and analysis, which consisted of 12 semi‐structured, in‐depth interviews with 14 parents of children accessing paediatric services within a single National Health Service (NHS) Trust.ResultsThe overarching theme of ‘managing uncertainty’ is presented with its constituent core categories/subthemes of ‘minimizing concerns’, ‘getting an answer’ and ‘prioritizing the diagnosis’.ConclusionsThis article presents and discusses a new understanding of how parents might be supported to manage the uncertainty associated with having a child with a long‐term disability. It is suggested that support needs to move beyond the provision of accurate and timely information, to include measures/strategies that help parents to accept and make sense of their situation. Re‐centring the child and reducing focus on diagnosis may help to allow space for continued hope.
Infants’ Mapping of New Faces to New Voices
Authors: Orena Adriel John , Werker Janet F. 
Published: June 2021

The ability to identify individuals by voice is fundamental for communication. However, little is known about the expectations that infants hold when learning unfamiliar voices. Here, the voice‐learning skills of 4‐ and 8‐month‐olds (N = 53; 29 girls, 14 boys of various ethnicities) were tested using a preferential‐looking task that involved audiovisual stimuli of their mothers and other unfamiliar women. Findings reveal that the expectation that novel voices map on to novel faces emerges between 4 and 8 months of age, and that infants can retain learning of face‐voice pairings via nonostensive cues by 8 months of age. This study provides new insights about infants’ use of disambiguation and fast mapping in early voice learning.
State‐of‐the‐art machine learning algorithms for the prediction of outcomes after contemporary heart transplantation: Results from the UNOS database
Authors: Kampaktsis Polydoros N. , Tzani Aspasia , Doulamis Ilias P. , Moustakidis Serafeim , Drosou Anastasios , Diakos Nikolaos , Drakos Stavros G. , Briasoulis Alexandros 
Published: June 2021

AbstractPurposeWe sought to develop and validate machine learning (ML) models to increase the predictive accuracy of mortality after heart transplantation (HT).Methods and resultsWe included adult HT recipients from the United Network for Organ Sharing (UNOS) database between 2010 and 2018 using solely pre‐transplant variables. The study cohort comprised 18 625 patients (53 ± 13 years, 73% males) and was randomly split into a derivation and a validation cohort with a 3:1 ratio. At 1‐year after HT, there were 2334 (12.5%) deaths. Out of a total of 134 pre‐transplant variables, 39 were selected as highly predictive of 1‐year mortality via feature selection algorithm and were used to train five ML models. AUC for the prediction of 1‐year survival was .689, .642, .649, .637, .526 for the Adaboost, Logistic Regression, Decision Tree, Support Vector Machine, and K‐nearest neighbor models, respectively, whereas the Index for Mortality Prediction after Cardiac Transplantation (IMPACT) score had an AUC of .569. Local interpretable model‐agnostic explanations (LIME) analysis was used in the best performing model to identify the relative impact of key predictors. ML models for 3‐ and 5‐year survival as well as acute rejection were also developed in a secondary analysis and yielded AUCs of .629, .609, and .610 using 27, 31, and 91 selected variables respectively.ConclusionMachine learning models showed good predictive accuracy of outcomes after heart transplantation.
Academia is racist: Barriers women faculty face in academic public contexts
Authors: Mousa Mohamed 
Published: June 2021

AbstractThrough addressing four public universities in Egypt, the author of this paper aims to uncover the main barriers women faculty face when fulfilling their academic roles. The author employed a qualitative research method through conducting semi‐structured interviews with 40 female academics. Moreover, he subsequently used thematic analysis to determine the main ideas in the transcripts. The author of the present study has identified the poor representation of women faculty at both professorial levels and in managerial academic positions. The study indicated that heavy teaching loads, lengthy working hours, accusations of low productivity, growth of masculine power distance and limited empowerment opportunities are the main barriers hindering the status and representation of women faculty in the addressed universities. The findings also showed that social realities, which include the implicit relations among humans (male and female faculty in this case) in the workplace and also relations between humans and their surrounding natural world (stakeholders in the surrounding environment in the present case) decide the volume of knowledge and level of power women might attain. This paper contributes by filling a gap in HR management and higher education, in which empirical studies on the status of women faculty and the barriers they face have been limited so far.
Patients as partners in health research: A scoping review
Authors: McCarron Tamara L. , Clement Fiona , Rasiah Jananee , Moran Chelsea , Moffat Karen , Gonzalez Andrea , Wasylak Tracy , Santana Maria 
Published: June 2021

AbstractBackgroundThe role of patient involvement in health research has evolved over the past decade. Despite efforts to engage patients as partners, the role is not well understood. We undertook this review to understand the engagement practices of patients who assume roles as partners in health research.MethodsUsing a recognized methodological approach, two academic databases (MEDLINE and EMBASE) and grey literature sources were searched. Findings were organized into one of the three higher levels of engagement, described by the Patient and Researcher Engagement framework developed by Manafo. We examined and quantified the supportive strategies used during involvement, used thematic analysis as described by Braun and Clarke and themed the purpose of engagement, and categorized the reported outcomes according to the CIHR Engagement Framework.ResultsOut of 6621 records, 119 sources were included in the review. Thematic analysis of the purpose of engagement revealed five themes: documenting and advancing PPI, relevance of research, co‐building, capacity building and impact on research. Improved research design was the most common reported outcome and the most common role for patient partners was as members of the research team, and the most commonly used strategy to support involvement was by meetings.ConclusionThe evidence collected during this review advanced our understanding of the engagement of patients as research partners. As patient involvement becomes more mainstream, this knowledge will aid researchers and policy‐makers in the development of approaches and tools to support engagement.Patient/User InvolvementPatients led and conducted the grey literature search, including the synthesis and interpretation of the findings.
Can existing electronic medical records be used to quantify cardiovascular risk at point of care?
Authors: Klimis Harry , Shaw Tim , Von Huben Amy , Charlston Emma , Usherwood Tim , Jennings Garry , Messom Ray , Thiagalingam Aravinda , Gunja Naren , Shetty Amith , Chow Clara K. 
Published: June 2021

AbstractBackgroundUsing electronic data for cardiovascular risk stratification could help in prioritising healthcare access and optimise cardiovascular prevention.AimsTo determine whether assessment of absolute cardiovascular risk (Australian absolute cardiovascular disease risk (ACVDR)) and short‐term ischaemic risk (History, ECG, Age, Risk factors, and Troponin (HEART) score) is possible from available data in Electronic Medical Record (EMR) and My Health Record (MHR) of patients presenting with acute cardiac symptoms to a Rapid Access Cardiology Clinic (RACC).MethodsAudit of EMR and MHR on 200 randomly selected adults who presented to RACC between 1 March 2017 and 4 February 2020. The main outcomes were the proportion of patients for which ACVDR score and HEART score could be calculated.ResultsMean age was 55.2 ± 17.8 years and 43% were female. Most (85%) were referred from emergency for chest pain (52%). Forty‐six percent had hypertension, 35% obesity, 20% diabetes mellitus, 17% ischaemic heart disease and 18% were current smokers. There was no significant difference in MHR accessibility with age, gender and number of comorbidities. An ACVDR score could be estimated for 17.5% (EMR) and 0% (MHR) of patients. None had complete data to estimate HEART score in either EMR or MHR. Most commonly missing variables for ACVDR score were blood pressure (MHR) and high‐density lipoprotein cholesterol (EMR), and for HEART score the missing variables were body mass index and comorbidities (MHR and EMR).ConclusionsSignificant gaps are apparent in electronic medical data capture of key variables to perform cardiovascular risk assessment. Medical data capture should prioritise the collection of clinically important data to help address gaps in cardiovascular management.
Parasitism and host dispersal plasticity in an aquatic model system
Authors: Zilio Giacomo , Nørgaard Louise S. , Petrucci Giovanni , Zeballos Nathalie , Gougat‐Barbera Claire , Fronhofer Emanuel A. , Kaltz Oliver 
Published: June 2021

AbstractDispersal is a central determinant of spatial dynamics in communities and ecosystems, and various ecological factors can shape the evolution of constitutive and plastic dispersal behaviours. One important driver of dispersal plasticity is the biotic environment. Parasites, for example, influence the internal condition of infected hosts and define external patch quality. Thus, state‐dependent dispersal may be determined by infection status and context‐dependent dispersal by the abundance of infected hosts in the population. A prerequisite for such dispersal plasticity to evolve is a genetic basis on which natural selection can act. Using interconnected microcosms, we investigated dispersal in experimental populations of the freshwater protistParamecium caudatumin response to the bacterial parasiteHolospora undulata. For a collection of 20 natural host strains, we found substantial variation in constitutive dispersal and to a lesser degree in dispersal plasticity. First, infection tended to increase or decrease dispersal relative to uninfected controls, depending on strain identity, indicative of state‐dependent dispersal plasticity. Infection additionally decreased host swimming speed compared to the uninfected counterparts. Second, for certain strains, there was a weak negative association between dispersal and infection prevalence, such that uninfected hosts dispersed less when infection was more frequent in the population, indicating context‐dependent dispersal plasticity. Future experiments may test whether the observed differences in dispersal plasticity are sufficiently strong to be picked up by natural selection. The evolution of dispersal plasticity as a strategy to mitigate parasite effects spatially may have important implications for epidemiological dynamics.
Heat transfer analysis of convective and microwave drying of dragon fruit
Authors: Bhagya Raj Gurajala V.S. , Dash Kshirod K. 
Published: June 2021

AbstractThe purpose of this study was to develop a predictive three‐dimensional analytical model for predicting the temperature profile during microwave and convective drying of dragon fruit. A combined electromagnetic (Maxwell's equation) and heat transfer model was used for modeling of microwave drying. This heat transfer modeling is applicable to describe the thermal dissipation during the microwave and convective drying of agricultural produces. In this process, the dragon fruit cube of 15 mm was dried at a microwave power of 200, 400, and 600 W during the microwave drying process and hot air temperature of 60°C during the convective drying process. During microwave drying, the core or center temperature was maximum compared with the temperature at the surface of the dragon fruit cube. The predicted temperature at the center of the dragon fruit cube exposed to the microwave power of 200, 400, and 600 W for 60 s of drying time was 34.67, 44.34, and 54.02°C, respectively. In convective drying, the temperature at the edges was higher than the temperature at the center point of the dragon fruit cube. During convective drying, the fruit sample attained the maximum temperature of 60°C after being exposed to hot air for 8 min. The RMSE and values between experimental and model projected values were less than 0.988 and 0.029 in microwave drying and less than 0.891 and 0.018 in convective drying, indicating that the model projected values were in good agreement with the experimental values.Practical ApplicationsThe importance of thermal processes in deciding the safety and quality of food products is emergent. This model can predict food product temperature distribution during the hot air drying and microwave drying of Dragon fruit cubes. The economy of the drying process is often influenced by the nature and operation of these processes and hence modeling of the drying process is a crucial factor for the industry. These results can be used to quantify heat and moisture distribution, as well as to monitor the drying process of fruits and vegetables, saving energy and time.
Predictors of short‐term hospitalization and emergency department presentations in aged care
Authors: Inacio Maria C. , Jorissen Robert N. , Khadka Jyoti , Whitehead Craig , Maddison John , Bourke Alice , Pham Clarabelle T. , Karnon Jonathon , Wesselingh Steve L. , Lynch Elizabeth , Harvey Gillian , Caughey Gillian E. , Crotty Maria 
Published: June 2021

AbstractObjectivesTo examine individual, medication, system, and healthcare related predictors of hospitalization and emergency department (ED) presentation within 90 days of entering the aged care sector, and to create risk‐profiles associated with these outcomes.Design and settingRetrospective population‐based cohort study using data from the Registry of Senior Australians.ParticipantsOlder people (aged 65 and older) with an aged care eligibility assessment in South Australia between January 1, 2013 and May 31, 2016 (N = 22,130).MeasurementsPrimary outcomes were unplanned hospitalization and ED presentation within 90 days of assessment. Individual, medication, system, and healthcare related predictors of the outcomes at the time of assessment, within 90 days or 1‐year prior. Fine–Gray models were used to calculate subdistribution hazard ratios (sHR) and 95% confidence intervals (CI). Harrell's C‐index assessed predictive ability.ResultsFour thousand nine‐hundred and six (22.2%) individuals were hospitalized and 5028 (22.7%) had an ED presentation within 90 days. Predictors of hospitalization included: being a man (hospitalization sHR = 1.33, 95% CI 1.26–1.42), ≥3 urgent after‐hours attendances (hospitalization sHR = 1.21, 95% CI 1.06–1.39), increasing frailty index score (hospitalization sHR = 1.19, 95% CI 1.11–1.28), individuals using glucocorticoids (hospitalization sHR = 1.11, 95% CI 1.02–1.20), sulfonamides (hospitalization sHR = 1.18, 95% CI 1.10–1.27), trimethoprim antibiotics (hospitalization sHR = 1.15, 95% CI 1.03–1.29), unplanned hospitalizations 30 days prior (hospitalization sHR = 1.13, 95% CI 1.04–1.23), and ED presentations 1 year prior (hospitalization sHR = 1.07, 95% CI 1.04–1.10). Similar predictors and hazard estimates were also observed for ED presentations. The hospitalization models out‐of‐sample predictive ability (C‐index = 0.653, 95% CI 0.635–0.670) and ED presentations (C‐index = 0.647, 95% CI 0.630–0.663) were moderate.ConclusionsOne in five individuals with aged care eligibility assessments had unplanned hospitalizations and/or ED presentation within 90 days with several predictors identified at the time of aged care eligibility assessment. This is an actionable period for targeting at‐risk individuals to reduce hospitalizations.