bluuebunny/crossref_metadata_2025_split huggingface dataset:
Co-designing a digital mental health platform, “Momentum”, with young people aged 7–17: A qualitative study
Authors: Ludlow Kristiana , Russell Jeremy K , Ryan Brooke , Brown Renee L , Joynt Tamsin , Uhlmann Laura R , Smith Genevieve E , Donovan Caroline , Hides Leanne , Spence Susan H , March Sonja , Cobham Vanessa E 
Published: November 2023

Introduction Digital mental health interventions (DMHIs) offer a promising alternative or adjunct treatment method to face-to-face treatment, overcoming barriers associated with stigma, access, and cost. This project is embedded in user experience and co-design to enhance the potential acceptability, usability and integration of digital platforms into youth mental health services. Objective To co-design a digital mental health platform that provides self-directed, tailored, and modularised treatment for young people aged 7–17 years experiencing anxiety, depression and other related problems. Methods Sixty-eight participants, aged 7–17 years, engaged in one of 20 co-design workshops. Eight workshops involved children (n  =  26, m  =  9.42 years, sd  =  1.27) and 12 involved adolescents (n  =  42, m  =  14.57 years, sd  =  1.89). Participants engaged in a variety of co-design activities (e.g., designing a website home page and rating self-report assessment features). Workshop transcripts and artefacts (e.g., participants’ drawings) were thematically analysed using Gale et al.'s Framework Method in NVivo. Results Six themes were identified: Interactive; Relatable; Customisable; Intuitive; Inclusive; and Personalised, transparent and trustworthy content. The analysis revealed differences between children's and adolescents’ designs and ideas, supporting the need for two different versions of the platform, with age-appropriate activities, features, terminology, and content. Conclusions This research showcased co-design as a powerful tool to facilitate collaboration with young people in designing DMHIs. Two sets of recommendations were produced: 1) recommendations for the design, functionality, and content of youth DMHIs, supported by child- and adolescent-designed strategies; and 2) recommendations for clinicians and researchers planning to conduct co-design and intervention development research with children and adolescents.
Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: Data from the osteoarthritis initiative study
Authors: Chen Tianrong , Or Calvin Kalun 
Published: November 2023

Objective This study aimed to examine the performance of machine learning models in predicting the progression of knee pain, functional decline, and incidence of knee osteoarthritis (OA) in high-risk individuals, with automated machine learning (AutoML) being used to automate the prediction process. Design There were four stages in the process of our AutoML-integrated prediction. Stage 1—Data preparation: The data of 3200 eligible individuals in the Osteoarthritis Initiative (OAI) study who were considered at high risk of knee OA at the baseline visit were extracted and used. Specifically, 1094 variables from the OAI study were used to predict the changes in knee pain, physical function, and incidence of knee OA (i.e. the first occurrence of frequent knee symptoms and definite tibial osteophytes (Kellgren and Lawrence grade ≥2)) over a 9-year period. Stage 2—Model training: The AutoML approach was used to automatically train nine widely used machine learning (ML) models. Stage 3—Model testing: The AutoML approach was used to automatically test the performance of the ML models. Stage 4—Selection of important input variables: The AutoML approach automated the process of computing the importance scores of all input variables and identifying the most important ones, using the technique of permutation feature importance. Results Using the AutoML approach, the weighted ensemble model and the CatBoost model showed the best performance among all nine ML models. For the prediction of each outcome in each year, the five most important input variables were identified, most of which were obtained from self-reported questionnaire surveys and radiographic imaging reports. Conclusion The AutoML approach has shown potential in automating the process of using ML models to predict long-term changes in knee OA-related outcomes. Its use could support the deployment of ML solutions, facilitating the provision of personalized interventions to prevent the deterioration of knee health and incident knee OA.
Cost of maternal complications and its associated factors among mothers attending Hawassa public hospitals, Southern Ethiopia
Authors: Loko Dassalegn , Ayele Angefa , Dessie Yadata , Hawulte Behailu , Ayele Gudeta , Tolossa Tadesse 
Published: November 2023

Background: The cost of maternal complications is considered as an important factor hindering the utilization of maternal health care services. However, information of estimate of spending on maternal complication was lacking. This study was aimed to estimate the cost of maternal complications and associated factors among mother’s attending Hawassa public hospitals, Sidama Regional state, Ethiopia. Methods: A cross-sectional study design was conducted among 348 randomly selected mothers attending public hospitals in Hawassa from November 15 to December 15, 2021. Data was coded and entered into Epi Data version 3.1 and exported to STATA version 16.0 for analysis. Simple and multiple linear regression analysis was done. Correlation coefficient along with 95% CI was used to present the finding and p < 0.05 was used to declare statistical significance. Results: This study found that total median cost of maternal complications was 4895.5 (IQR = 3779) ETB. The total median direct medical cost was 1765.5 (IQR = 1649.5) ETB. Number of days absent [( R = 0.028; 95% CI: (0.023, 0.033)], distance from facility [( R = 0.001; 95% CI: (0.000, 0.002)], site of laboratory diagnosis [( R = 0.230; 95% CI: (0.140, 0.320)], number of laboratory test conducted [( R = 0.045; 95% CI: (0.021, 0.069)] were found to be significance predictors of maternal complications costs. Conclusions: Total median cost of maternal complications in current study was high. Respondents’ site of diagnosis, number of days missed from work, number of laboratory tests, and distance from hospitals were independent predictors of maternal complications cost. Thus, we will recommend governments to introduce strategies that specifically help mothers with maternal complications.
Evaluations of Student's Satisfaction with Externship Education in the Academic Departments of the Medical School of Kermanshah University of Medical Sciences in July and August 2021
Authors: Keramati Ali , Rezaei Mnsour , Veisipour Mohammad , Esmaeli Mojtaba 
Published: November 2023

OBJECTIVES Determining the level of satisfaction in each field will help to examine and eliminate the existing problems and shortcomings. Using this information, students’ satisfaction can be provided as much as possible while strengthening the positive factors and correcting the negative factors. The aim of this study was to evaluate the Student's Satisfaction with externship Education in the Academic Departments of the Medical School of Kermanshah University of Medical Sciences in 2021. METHODS This descriptive cross-sectional study, was performed in the medical school of Kermanshah University of Medical Sciences. The statistical population was all externship students. The validity of the questionnaire's content was determined by consulting experts, and its reliability was obtained by Cronbach's alpha method based on a sample of 20 students. The questionnaires were completed virtually on the Google site using the Google Form. Data analysis was performed Stata V14.2 software using descriptive statistics, t-test, and chi-square, and the significant level was considered 0.05. RESULTS The results showed that 55% of the participants were female and 45% were male. The level of students ‘satisfaction with the quality of supervisors’ education was moderate to high and in other cases was moderate to low. Students were more satisfied with teaching anesthesia than other departments and were dissatisfied with the infectious department. No statistically significant difference was found between people's satisfaction with the overall clinical education process in terms of age. CONCLUSION The results of this study showed that students have moderate to poor satisfaction with externship education in educational groups.
A Markov analysis of azacitidine and venetoclax vs induction chemotherapy for medically fit patients with AML
Authors: Ravindran Mithunan , Mozessohn Lee , Cheung Matthew , Buckstein Rena , Teichman Jennifer 
Published: November 2023

Abstract
Although induction chemotherapy (IC) is the standard of care in medically fit patients with newly diagnosed acute myeloid leukemia (AML), limited retrospective data indicate that patients at adverse-risk may benefit from azacytidine and venetoclax (aza-ven). Our goal was to perform a Markov decision analysis to determine whether IC or aza-ven is the optimal induction regimen in this population. Using the TreeAge software, Markov models were created for adverse-risk and intermediate-risk cohorts. A systematic review of the literature informed the transition probabilities and utilities included in the analyses. Our primary outcome was quality-adjusted life years (QALYs) gained over 5 years after diagnosis. Overall, patients at adverse risk treated with IC gained 1.4 QALYs, compared with 2.0 QALYs in patients treated with aza-ven. Patients at adverse risk treated with IC and allogeneic stem cell transplantation (allo-SCT), IC, aza-ven and allo-SCT, or aza-ven gained 2.1, 1.5, 3.0, and 1.9 QALYs, respectively. Meanwhile, patients at intermediate risk treated with IC gained 2.0 QALY, compared with 1.7 QALY in patients treated with aza-ven. Patients at intermediate risk treated with IC and allo-SCT, IC, aza-ven and allo-SCT, and aza-ven gained 2.7, 2.3, 2.6, and 1.8 QALYs, respectively. We have demonstrated that medically fit patients with newly diagnosed adverse-risk AML may benefit from treatment with aza-ven over those treated with IC, whereas IC remains the preferred approach for patients at intermediate risk. Our work challenges the use of the European LeukemiaNet risk classification for patients treated with aza-ven and highlights the need for prospective investigation into aza-ven as induction therapy for medically fit patients.
Recombinant erythropoietin in autoimmune hemolytic anemia with inadequate bone marrow response: a prospective analysis
Authors: Fattizzo Bruno , Pedone Giacinto Luca , Brambilla Caterina , Pettine Loredana , Zaninoni Anna , Passamonti Francesco , Barcellini Wilma 
Published: November 2023

Abstract
Up to 30% of patients with autoimmune hemolytic anemia (AIHA) show inadequate bone marrow (BM) compensatory response with inappropriately low levels of reticulocytes and endogenous erythropoietin. Ineffective BM compensation is associated with more severe anemia, transfusion need, and hospital admission, and treatment with recombinant erythropoietin (rEPO) may be beneficial. Here, we prospectively analyzed the efficacy and safety of rEPO in a single-center cohort of 47 patients with AIHA with inadequate reticulocytosis and endogenous erythropoietin at baseline. Epoetin alpha 40 000 international units per week were administered subcutaneously until hemoglobin (Hb) &gt;11 g/dL and then tapered off. Overall response was 55% at 15 days, 74% at 1 month, 74% at 3 months, 80% at 6 months, and 91% at 12 months. Consistently, Hb values significantly increased from baseline to each subsequent time point (P&lt;.001) with a median increase of +1.4, +2.4, +3.4, +3.8, and +4.4 g/dL, respectively. Transfusion needs reduced from 30% to &lt;10% at 15 days and thereafter (P &lt; .001). Concomitant medications included prednisone or methylprednisolone (N = 40, stable since &gt;2 weeks from enrollment), mycophenolate mofetil (N = 1, ongoing since &gt;3 months from enrollment), and rituximab (N = 7 patients with cold agglutinin disease from day 8). No association between concomitant medications and response to rEPO was found. Treatment was generally safe without rEPO-related severe adverse events. The comparison with an AIHA population not treated with rEPO showed a significant benefit of rEPO at 15 days and 1 month on response and Hb increase. These data support the use of rEPO as an add on to standard immunosuppression in AIHA with inadequate BM compensation. This trial was registered at www.clinicaltrials.gov as #NCT05931718.
Metagenomic analysis reveals distinct changes in the gut microbiome of obese Chinese children
Authors: Li Ping , Jiang Jiyang , Li Yifei , Lan Yue , Yang Fan , Wang Jiao , Xie Yuxin , Xiong Fei , Wu Jinhui , Liu Hanmin , Fan Zhenxin 
Published: November 2023

Abstract
Background
The prevalence of obese children in China is increasing, which poses a great challenge to public health. Gut microbes play an important role in human gut health, and changes in gut status are closely related to obesity. However, how gut microbes contribute to obesity in children remains unclear. In our study, we performed shotgun metagenomic sequencing of feces from 23 obese children, 8 overweight children and 22 control children in Chengdu, Sichuan, China.

Results
We observed a distinct difference in the gut microbiome of obese children and that of controls. Compared with the controls, bacterial pathogen Campylobacter rectus was significantly more abundant in obese children. In addition, functional annotation of microbial genes revealed that there might be gut inflammation in obese children. The guts of overweight children might belong to the transition state between obese and control children due to a gradient in relative abundance of differentially abundant species. Finally, we compared the gut metagenomes of obese Chinese children and obese Mexican children and found that Trichuris trichiura was significantly more abundant in the guts of obese Mexican children.

Conclusions
Our results contribute to understanding the changes in the species and function of intestinal microbes in obese Chinese children.
Detection of virulence genes of Staphylococcus aureus isolated from raw beef for retail sale in the markets of Ulaanbaatar city, Mongolia
Authors: Dorjgochoo Amgalanzaya , Batbayar Anujin , Tsend-Ayush Altansukh , Erdenebayar Otgontsetseg , Byambadorj Bayarlakh , Jav Sarantuya , Yandag Munkhdelger 
Published: November 2023

Abstract
Background
Staphylococcus aureus (S. aureus) is a highly virulent pathogen that causes food-borne illness, food poisoning, skin and soft tissue infections, abscesses, mastitis, and bacteremia. It is common for meat and meat products to become contaminated with S. aureus due to dirty hands, food storage conditions, food production processes, and unhygienic conditions, causing food poisoning. Therefore, we aimed to isolate S. aureus strain from the raw beef and reveal virulence genes and antibiotic resistance profile from isolated S. aureus strains.

Methods
In this study, 100 samples of raw beef were collected from 4 major market stalls in Ulaanbaatar city, Mongolia. S. aureus was detected according to the ISO 6888–1:2021 standard, and the nucA gene encoding the species-specific thermonuclease was amplified and confirmed by polymerase chain reaction (PCR). In the strains of S. aureus isolated from the samples, the genes encoding the virulence factors including sea, sed, tsst, eta, etb, and mecA were amplified by multiplex PCR. These genes are encoded staphylococcal enterotoxin A, enterotoxin D, toxic shock syndrome toxin, exotoxin A, exotoxin B and penicillin-binding protein PBP 2A, respectively. Antibiotic sensitivity test was performed by the Kirby–Bauer disc diffusion method. The Clinical and Laboratory Standard Institute guidelines as CLSI M100-S27 was used for analysis of the data.

Results
Thirty-five percent of our samples were detected contaminated with of the S. aureus strains. Subsequently, antibiotic resistance was observed in the S. aureus contaminated samples. Among our samples, the highest rates of resistance were determined against ampicillin (97.1%), oxacillin (88.6%), and penicillin (88.6%), respectively. Three genes including mecA, sea, and tsst from six virulence genes were detected in 17% of S. aureus strain-contaminated samples by multiplex PCR. The sed, etb and eta genes were detected in the 2.9%, 11.4% and 5.7% of our samples, respectively.

Conclusion
The results show that S. aureus related contamination is high in the raw beef for retail sale and prevalent S. aureus strains are resistant to all antibiotics used. Also, our results have demonstrated that there is a high risk for food poisoning caused by antibiotic resistant S. aureus in the raw beef and it may establish public health issues. Genes encoding for both heat-resistant and nonresistant toxicity factors were detected in the antibiotic resistant S. aureus strains and shown the highly pathogenic. Finally, our study is ensuring to need proper hygienic conditions during beef’s preparation and sale.
Deep Learning Approaches for Automatic Quality Assurance of Magnetic Resonance Images Using ACR Phantom
Authors: Torfeh Tarraf , Aouadi Souha , Yoganathan SA , Paloor Satheesh , Hammoud Rabih , Al-Hammadi Noora 
Published: November 2023

Abstract
Background
In recent years, there has been a growing trend towards utilizing Artificial Intelligence (AI) and machine learning techniques in medical imaging, including for the purpose of automating quality assurance. In this research, we aimed to develop and evaluate various deep learning-based approaches for automatic quality assurance of Magnetic Resonance (MR) images using the American College of Radiology (ACR) standards.

Methods
The study involved the development, optimization, and testing of custom convolutional neural network (CNN) models. Additionally, popular pre-trained models such as VGG16, VGG19, ResNet50, InceptionV3, EfficientNetB0, and EfficientNetB5 were trained and tested. The use of pre-trained models, particularly those trained on the ImageNet dataset, for transfer learning was also explored. Two-class classification models were employed for assessing spatial resolution and geometric distortion, while an approach classifying the image into 10 classes representing the number of visible spokes was used for the low contrast.

Results
Our results showed that deep learning-based methods can be effectively used for MR image quality assurance and can improve the performance of these models. The low contrast test was one of the most challenging tests within the ACR phantom.

Conclusions
Overall, for geometric distortion and spatial resolution, all of the deep learning models tested produced prediction accuracy of 80% or higher. The study also revealed that training the models from scratch performed slightly better compared to transfer learning. For the low contrast, our investigation emphasized the adaptability and potential of deep learning models. The custom CNN models excelled in predicting the number of visible spokes, achieving commendable accuracy, recall, precision, and F1 scores.
Health and wellbeing outcomes associated with loneliness for people with disability: a scoping review
Authors: Bailie Jodie , Bishop Glenda M. , Badland Hannah , Emerson Eric , Aitken Zoe , Stancliffe Roger , Ekanayake Kanchana , Llewellyn Gwynnyth 
Published: November 2023

AbstractBackgroundLoneliness is a significant public health concern due to its detrimental impact on health and wellbeing. Despite people with disability reporting higher levels of loneliness than the general population, there has been little research into how this is affecting their health and wellbeing. In light of this, the aim of our study was to scope both the existing evidence about the health and wellbeing outcomes associated with loneliness for people with disability, as well as the conceptual frameworks and measures utilised in this field of research.MethodsTo conduct this scoping review, we followed the methodology outlined by JBI and searched MEDLINE, Scopus, Informit, Embase, and Web of Science for peer-reviewed, English-language articles published between 1 January 2000 and 8 February 2023. Two independent reviewers completed screening, full-text review and data extraction, with consensus sought at each stage. Data were analysed using content analysis and presented both numerically and narratively.ResultsOut of the initial 1602 publications identified in the scoping review, only nine were included after duplicate removal, title and abstract screening, and full-text review. This limited number of studies, with the earliest study one published in 2015, represents a key finding. Eight of the nine studies were quantitative, and all were conducted in high income countries. Most of these studies utilised a version of the University of Los Angles Loneliness Scale to measure loneliness and addressed specific impairment groups. Notably, most of the studies identified associations between loneliness and health and wellbeing outcomes for people with disability.ConclusionsThis scoping review highlights the current scarcity of studies examining the effect that loneliness has on the health and wellbeing outcomes of people with disability. As most of the reviewed studies relied on loneliness measures designed for individuals without disability, they potentially overlook the unique life experiences of people with disability. Given that loneliness is an international public health concern, it is imperative that people with disability are not left behind or overlooked in efforts to address the impact of loneliness on health and wellbeing.