bluuebunny/crossref_metadata_2025_split huggingface dataset:
The perirenal fat thickness was independently associated with serum uric acid level in patients with type 2 diabetes mellitus
Authors: Yang Yuxian , Ma Yan , Cheng Yanan , Xu Yuechao , Fang Yuan , Ke Jing , Zhao Dong 
Published: August 2022

Abstract
Background
Obesity is an important risk factor for hyperuricemia. We aimed to explore the relationship between perirenal fat thickness (PrFT) and paranephric fat thickness (PnFT) and serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM).

Methods
This was a cross-sectional study involving 257 patients with T2DM recruited from Beijing Luhe Hospital from September 2019 to May 2020. The basic and clinical information such as age, gender, duration of diabetes was collected through the medical records. All patients underwent a physical examination including height, weight, waist circumference, hip circumference, systolic blood pressures and diastolic blood pressure. The venous blood and urine samples were collected to measure SUA, fasting blood glucose, total cholesterol, triglyceride, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, serum creatinine, blood urea nitrogen and glycosylated hemoglobin. PrFT and PnFT were measured via ultrasonography. Pearson correlation test and linear regression analysis were used to analyze the association between PrFT and PnFT and SUA.

Results
We found that PrFT and PnFT increased according to the tertiles of SUA level (P = 0.001 and P = 0.009, respectively). In addition, the PrFT and PnFT were positively associated with SUA level (r = 0.25, P < 0.001, r = 0.23, P < 0.001, respectively). Moreover, this association was stronger in males, non-obesity patients and patients with normal renal function. In the multivariate analysis, the PrFT was independently associated with SUA level after adjusting confounding factors.

Conclusions
The PrFT was independently associated with SUA level in patients with T2DM.
Self-reported lifestyle behaviours in families with an increased risk for type 2 diabetes across six European countries: a cross-sectional analysis from the Feel4Diabetes-study
Authors: De Craemer Marieke , Van Stappen Vicky , Brondeel Ruben , Iotova Violeta , Chakarova Nevena , Rurik Imre , Lindström Jaana , Kivelä Jemina , Moreno Luis Alberto , Mavrogianni Christina , Manios Yannis , Cardon Greet 
Published: August 2022

Abstract
Background
A healthy lifestyle decreases the risk of developing type 2 diabetes mellitus. The current cross-sectional study aimed to describe self-reported lifestyle behaviours and compare them to current health guidelines in European Feel4Diabetes-families at risk for developing type 2 diabetes across six countries (Belgium, Finland, Spain, Greece, Hungary and Bulgaria).

Methods
Parents and their children were recruited through primary schools located in low socio-economic status areas. Parents filled out the FINDRISC-questionnaire (eight items questioning age, Body Mass Index, waist circumference, PA, daily consumption of fruit, berries or vegetables, history of antihypertensive drug treatment, history of high blood glucose and family history of diabetes), which was used for the risk assessment of the family. Sociodemographic factors and several lifestyle behaviours (physical activity, sedentary behaviour, water consumption, fruit and vegetable consumption, soft drink consumption, sweets consumption, snack consumption, breakfast consumption) of both adults and children were assessed by parental questionnaires. Multilevel regression analyses were conducted to investigate families’ lifestyle behaviours, to compare these levels to health guidelines and to assess potential differences between the countries. Analyses were controlled for age, sex and socio-economic status.

Results
Most Feel4Diabetes-families at risk (parents and their children) did not comply with the guidelines regarding healthy behaviours, set by the WHO, European or national authorities. Less than half of parents and children complied with the physical activity guidelines, less than 15% of them complied with the fruit and vegetable guideline, and only 40% of the children met the recommendations of five glasses of water per day. Clear differences in lifestyle behaviours in Feel4Diabetes-families at risk exist between the countries.

Conclusions
Countries are highly recommended to invest in policy initiatives to counter unhealthy lifestyle behaviours in families at risk for type 2 diabetes development, taking into account country-specific needs. For future research it is of great importance to focus on families at risk in order to counter the development of type 2 diabetes and reduce health inequity.
The effect of preoperative sodium-glucose cotransporter 2 inhibitors on the incidence of perioperative metabolic acidosis: A retrospective cohort study
Authors: Iwasaki Yudai , Sasabuchi Yusuke , Horikita Sho , Furukawa Taku , Shiotsuka Junji , Lefor Alan Kawarai , Sanui Masamitsu 
Published: August 2022

Abstract
Background
Sodium-glucose cotransporter 2 inhibitors are a novel class of anti-hyperglycemic agents. Although several cases of perioperative euglycemic diabetic ketoacidosis have been linked to these medications, the association remains unclear. This study aimed to examine the association between sodium-glucose cotransporter 2 inhibitor use and the incidence of perioperative metabolic acidosis with euglycemia, the surrogating outcome of perioperative euglycemic diabetic ketoacidosis.

Method
This was a retrospective, matched cohort study, which was conducted in the intensive care unit of a tertiary care facility in Japan. We identified patients aged 20 years or older with diabetes mellitus who received pharmacologic therapy and were admitted to the intensive care unit after elective surgery between April 2014 and March 2019. We extracted the following data from the electronic medical record for matching: age, sex, surgery year, surgical site, hemoglobin A1c level, and prescription for sodium-glucose cotransporter 2 inhibitors.
Eligible patients were divided into two groups, those who were prescribed sodium-glucose cotransporter 2 inhibitors (SGLT2-i group) and those who were not (control group). For each patient in the SGLT2-i group, we randomly selected four patients from the control group matched for the extracted characteristics. The primary outcome was the incidence of metabolic acidosis with an elevated anion gap and euglycemia. The secondary outcome was the lowest pH value of each patient during their ICU stay.

Results
A total of 155 patients were included in this study. Patients receiving sodium-glucose cotransporter 2 inhibitors had comparable characteristics to control participants; however, the proportions of patients undergoing dialysis were not similar. Metabolic acidosis with euglycemia was seen in 7/31 (22.6%) patients receiving sodium-glucose cotransporter 2 inhibitors and in 10/124 (8.1%) control patients (p = 0.047).

Conclusions
This study shows that the use of sodium-glucose cotransporter 2 inhibitors is associated with a significantly higher incidence of metabolic acidosis with euglycemia. Patients receiving sodium-glucose cotransporter 2 inhibitors who are scheduled to undergo invasive surgical procedures should be closely monitored for the development of euglycemic diabetic ketoacidosis.
Simulation applications to support teaching and research in epidemiological dynamics
Authors: Getz Wayne M , Salter Richard , Vissat Ludovica Luisa 
Published: August 2022

Abstract
Background
An understanding of epidemiological dynamics, once confined to mathematical epidemiologists and applied mathematicians, can be disseminated to a non-mathematical community of health care professionals and applied biologists through simple-to-use simulation applications. We used Numerus Model Builder RAMP Ⓡ (Runtime Alterable Model Platform) technology, to construct deterministic and stochastic versions of compartmental SIR (Susceptible, Infectious, Recovered with immunity) models as simple-to-use, freely available, epidemic simulation application programs.

Results
We take the reader through simulations used to demonstrate the following concepts: 1) disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that ‘burn’ through the population to become extinguished when the proportion of the susceptible population drops below a critical level; 2) if immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase; 3) the steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R0, which must exceed 1 for an epidemic to occur; 4) the probability that a single infectious individual in a closed population (i.e. no migration) gives rise to an epidemic increases with the value of R0>1; 5) behavior that adaptively decreases the contact rate among individuals with increasing prevalence has major effects on the prevalence curve including dramatic flattening of the prevalence curve along with the generation of multiple prevalence peaks; 6) the impacts of treatment are complicated to model because they effect multiple processes including transmission, recovery and mortality; 7) the impacts of vaccination policies, constrained by a fixed number of vaccination regimens and by the rate and timing of delivery, are crucially important to maximizing the ability of vaccination programs to reduce mortality.

Conclusion
Our presentation makes transparent the key assumptions underlying SIR epidemic models. Our RAMP simulators are meant to augment rather than replace classroom material when teaching epidemiological dynamics. They are sufficiently versatile to be used by students to address a range of research questions for term papers and even dissertations.
Machine learning-based prediction of fainting during blood donations using donor properties and weather data as features
Authors: Suessner Susanne , Niklas Norbert , Bodenhofer Ulrich , Meier Jens 
Published: August 2022

Abstract
Background and objectives
Fainting is a well-known side effect of blood donation. Such adverse experiences can diminish the return rate for further blood donations. Identifying factors associated with fainting could help prevent adverse incidents during blood donation.

Materials and methods
Data of 85,040 blood donations from whole blood and apheresis donors within four consecutive years were included in this retrospective study. Seven different machine learning models (random forests, artificial neural networks, XGradient Boosting, AdaBoost, logistic regression, K nearest neighbors, and support vector machines) for predicting fainting during blood donation were established. The used features derived from the data obtained from the questionnaire every donor has to fill in before the donation and weather data of the day of the donation.

Results
One thousand seven hundred fifteen fainting reactions were observed in 228 846 blood donations from 88,003 donors over a study period of 48 months. Similar values for all machine learning algorithms investigated for NPV, PPV, AUC, and F1-score were obtained. In general, NPV was above 0.996, whereas PPV was below 0.03. AUC and F1-score were close to 0.9 for all models. Essential features predicting fainting during blood donation were systolic and diastolic blood pressure and ambient temperature, humidity, and barometric pressure.

Conclusion
Machine-learning algorithms can establish prediction models of fainting in blood donors. These new tools can reduce adverse reactions during blood donation and improve donor safety and minimize negative associations relating to blood donation.
Supporting adjuvant endocrine therapy adherence in women with breast cancer: the development of a complex behavioural intervention using Intervention Mapping guided by the Multiphase Optimisation Strategy
Authors: Green Sophie M. C. , French David P. , Graham Christopher D. , Hall Louise H. , Rousseau Nikki , Foy Robbie , Clark Jane , Parbutt Catherine , Raine Erin , Gardner Benjamin , Velikova Galina , Moore Sally J. L. , Buxton Jacqueline ,   ROSETA investigators, Collinson Michelle , Ellison Rachel , Wilkes Hollie , Hartley Suzanne , Mason Ellen , Farrin Amanda , Walwyn Rebecca , Waller Jo , Howdon Daniel , Metherell Jamie , Smith Samuel G. 
Published: August 2022

AbstractBackgroundAdjuvant endocrine therapy (AET) reduces the risk of breast cancer recurrence and mortality. However, up to three-quarters of women with breast cancer do not take AET as prescribed. Existing interventions to support adherence to AET have largely been unsuccessful, and have not focused on the most salient barriers to adherence. This paper describes the process of developing four theory-based intervention components to support adherence to AET. Our aim is to provide an exemplar of intervention development using Intervention Mapping (IM) with guidance from the Multiphase Optimisation Strategy (MOST).MethodsIterative development followed the six-stage IM framework with stakeholder involvement. Stage 1 involved a literature review of barriers to adherence and existing interventions, which informed the intervention objectives outlined in Stage 2. Stage 3 identified relevant theoretical considerations and practical strategies for supporting adherence. Stage 4 used information from Stages 1-3 to develop the intervention components. Stages 1-4 informed a conceptual model for the intervention package. Stages 5 and 6 detailed implementation considerations and evaluation plans for the intervention package, respectively.ResultsThe final intervention package comprised four individual intervention components: Short Message Service to encourage habitual behaviours surrounding medication taking; an information leaflet to target unhelpful beliefs about AET; remotely delivered Acceptance and Commitment Therapy-based guided self-help to reduce psychological distress; and a website to support self-management of AET side-effects. Considerations for implementation within the NHS, including cost, timing and mode of delivery were outlined, with explanation as to how using MOST can aid this. We detail our plans for the final stage of IM which involve feasibility testing. This involved planning an external exploratory pilot trial using a 24-1fractional factorial design, and a process evaluation to assess acceptability and fidelity of intervention components.ConclusionsWe have described a systematic and logical approach for developing a theoretically informed intervention package to support medication adherence in women with breast cancer using AET. Further research to optimise the intervention package, guided by MOST, has the potential to lead to more effective, efficient and scalable interventions.
Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study
Authors: Wood Richard M. , Moss Simon J. , Murch Ben J. , Vasilakis Christos , Clatworthy Philip L. 
Published: August 2022

Abstract
Background
Optimising capacity along clinical pathways is essential to avoid severe hospital pressure and help ensure best patient outcomes and financial sustainability. Yet, typical approaches, using only average arrival rate and average lengths of stay, are known to underestimate the number of beds required. This study investigates the extent to which averages-based estimates can be complemented by a robust assessment of additional ‘flex capacity’ requirements, to be used at times of peak demand.

Methods
The setting was a major one million resident healthcare system in England, moving towards a centralised stroke pathway. A computer simulation was developed for modelling patient flow along the proposed stroke pathway, accounting for variability in patient arrivals, lengths of stay, and the time taken for transfer processes. The primary outcome measure was flex capacity utilisation over the simulation period.

Results
For the hyper-acute, acute, and rehabilitation units respectively, flex capacities of 45%, 45%, and 36% above the averages-based calculation would be required to ensure that only 1% of stroke presentations find the hyper-acute unit full and have to wait. For each unit some amount of flex capacity would be required approximately 30%, 20%, and 18% of the time respectively.

Conclusions
This study demonstrates the importance of appropriately capturing variability within capacity plans, and provides a practical and economical approach which can complement commonly-used averages-based methods. Results of this study have directly informed the healthcare system’s new configuration of stroke services.
K205R specific nanobody-horseradish peroxidase fusions as reagents of competitive ELISA to detect African swine fever virus serum antibodies
Authors: Zhang Angke , Wu Shuya , Duan Xiaohong , Zhao Huijun , Dong Haoxin , Ren Jiahui , Zhang Mingfang , Li Jiaji , Duan Hong , Zhang Gaiping 
Published: August 2022

AbstractBackgroundAfrican swine fever virus (ASFV) is a highly contagious hemorrhagic disease and often lethal, which has significant economic consequences for the swine industry. Due to lacking of commercial vaccine, the prevention and control of ASF largely depend on early large-scale detection and screening. So far, the commercial ELISA kits have a long operation time and are expensive, making it difficult to achieve large-scale clinical applications. Nanobodies are single-domain antibodies produced by camelid animals, and have unique advantages such as smaller molecular weight, easy genetic engineering modification and low-costing of mass production, thus exhibiting good application prospects.ResultsThe present study developed a new method for detection of ASFV specific antibodies using nanobody-horseradish peroxidase (Nb-HRP) fusion proteins as probe. By using camel immunization, phage library construction and phage display technology, five nanobodies against K205R protein were screened. Then, Nb-HRP fusion proteins were produced using genetic modification technology. Based on the Nb-HRP fusion protein as specific antibodies against K205R protein, a new type of cELISA was established to detect ASFV antibodies in pig serum. The cut-off value of the cELISA was 34.8%, and its sensitivity, specificity, and reproducibility were good. Furthermore, the developed cELISA exhibited 99.3% agreement rate with the commercial available ELISA kit (kappa value = 0.98).ConclusionsThe developed cELISA method has the advantages of simple operation, rapid and low-costing, and can be used for monitoring of ASFV infection in pigs, thus providing a new method for the prevention and control of ASF.
Costs of treating childhood malaria, diarrhoea and pneumonia in rural Mozambique and Uganda
Authors: Batura Neha , Kasteng Frida , Condoane Juliao , Bagorogosa Benson , Castel-Branco Ana Cristina , Kertho Edmound , Källander Karin , Soremekun Seyi , Lingam Raghu , Vassall Anna ,   the inSCALE study group, Tibenderana James , Meek Sylvia , Hill Zelee , Strachan Daniel , Ayebale Godfrey , Nakirunda Maureen , Counihan Helen , Ndima Sozinho , Muiambo Abel , Salomao Nelson , Kirkwood Betty 
Published: August 2022

Abstract
Background
Globally, nearly half of all deaths among children under the age of 5 years can be attributed to malaria, diarrhoea, and pneumonia. A significant proportion of these deaths occur in sub-Saharan Africa. Despite several programmes implemented in sub-Saharan Africa, the burden of these illnesses remains persistently high. To mobilise resources for such programmes it is necessary to evaluate their costs, costs-effectiveness, and affordability. This study aimed to estimate the provider costs of treating malaria, diarrhoea, and pneumonia among children under the age of 5 years in routine settings at the health facility level in rural Uganda and Mozambique.

Methods
Service and cost data was collected from health facilities in midwestern Uganda and Inhambane province, Mozambique from private and public health facilities. Financial and economic costs of providing care for childhood illnesses were investigated from the provider perspective by combining a top-down and bottom-up approach to estimate unit costs and annual total costs for different types of visits for these illnesses. All costs were collected in Ugandan shillings and Mozambican meticais. Costs are presented in 2021 US dollars.

Results
In Uganda, the highest number of outpatient visits were for children with uncomplicated malaria and of inpatient admissions were for respiratory infections, including pneumonia. The highest unit cost for outpatient visits was for pneumonia (and other respiratory infections) and ranged from $0.5 to 2.3, while the highest unit cost for inpatient admissions was for malaria ($19.6). In Mozambique, the highest numbers of outpatient and inpatient admissions visits were for malaria. The highest unit costs were for malaria too, ranging from $2.5 to 4.2 for outpatient visits and $3.8 for inpatient admissions. The greatest contributors to costs in both countries were drugs and diagnostics, followed by staff.

Conclusions
The findings highlighted the intensive resource use in the treatment of malaria and pneumonia for outpatient and inpatient cases, particularly at higher level health facilities. Timely treatment to prevent severe complications associated with these illnesses can also avoid high costs to health providers, and households.
Trial registration: ClinicalTrials.gov, identifier: NCT01972321.