bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of Reoperation in 30 days in Subdural Hematoma Evacuation
Authors: Sayed Rahman , Zamarud Aroosa , Gross Suzanne , Ramos Rafael De La Garza , Holland Ryan , Eikermann Matthias , Rupp Samuel , Kim Jinu , Babar Mustufa , Basam Mudaser , Yassari Reza , Gelfand Yaroslav 
Published: August 2023

Abstract
Introduction:
Subdural hematoma (SDH) represents one of the most common types of intracranial hemorrhages, particularly in the elderly. Despite a long history of diagnoses and procedures, there is conflicting data on predictive parameters to predict outcomes.
Methods
We conducted a large retrospective review of patients that underwent a SDH evacuation at a single urban institution between 2015–2022. Data were collected from the electronic medical record on prior comorbidities, anticoagulation use, mental status on presentation, pre-op labs, and pre/post-op imaging parameters. Univariate and multivariate analyses were conducted to analyze predictors of reoperation.
Results
Of the 329 patients, 35 patients were excluded due to missing data in the EMR. 10% of the patients underwent reoperation with the average time to reoperation being 17 days. Univariate analysis showed that a prior history of chronic kidney disease was associated with higher rates of reoperation. Lab data showed that those presenting with elevated PTT were more likely to undergo reoperation. Analysis of the imaging data showed that patients with a post-op shift of 6 mm or greater were more likely to undergo reoperation. Multivariate analysis showed that only having a post-op shift of greater than 6 mm was a significant predictor of reoperation. Twenty-two percent of patients with post-op shifts over 6 mm needed re-op. We briefly compared those below and above 65 and found no increase in instances of persistent shift over 6 mm in the older group. Interestingly, having a higher PTT lead to lower rates of reoperation
Conclusion
On multivariate analysis, a post-op shift of over 6 mm is the only independent predictor of re-operations. Further analysis would be beneficial to better understand predictors of reoperation. A review of the current literature showed that this is one of the largest series from a single institution with granular data available for analysis.
Performance of SARS-CoV-2 antigen-detection rapid diagnostic tests for COVID-19 self-testing and self-sampling in comparison to molecular and professional-use antigen tests: A systematic review and meta-analysis
Authors: Katzenschlager Stephan , Brümmer Lukas E. , Schmitz Stephani , Tolle Hannah , Manten Katharina , Gaeddert Mary , Erdmann Christian , Lindner Andreas , Tobian Frank , Grilli Maurizio , Pollock Nira R. , Macé Aurélien , Erkosar Berra , Carmona Sergio , Ongarello Stefano , Johnson Cheryl C. , Sacks Jilian A. , Denkinger Claudia M. , Yerlikaya Seda 
Published: August 2023

Abstract
Purpose
Self-testing is an effective tool to bridge the testing gap for several infectious diseases; however, its performance in detecting SARS-CoV-2 using antigen-detection rapid diagnostic tests (Ag-RDTs) has not been systematically reviewed. To inform WHO guideline development, we evaluated the accuracy of COVID-19 self-testing and/or self-sampling using Ag-RDTs.
Methods:
We searched multiple databases for articles evaluating the accuracy of COVID-19 self-testing or self-sampling through November 7th, 2022. Cohen’s kappa was estimated to assess concordance between self-testing/self-sampling and fully professional-use Ag-RDT results. Bivariate meta-analysis was performed to obtain pooled performance estimates compared to molecular testing. The QUADAS-2 and GRADE tools were used to evaluate quality and certainty of evidence.
Results:
Among 43 studies included in the review, twelve reported on self-testing, while 31 studies assessed self-sampling only. The risk of bias was low in 49.6% of the studies. Overall concordance with professional-use Ag-RDTs (n = 7 datasets) was high (kappa 0.92 [95% confidence interval (CI) 0.89 to 0.95]). Overall pooled sensitivity and specificity of Ag-RDT testing using self-testing/self-sampling (n = 54 datasets) was 70.5% (95% CI 64.3 to 76.0) and 99.4% (95% CI 99.1–99.6), respectively.
Conclusion:
Despite high heterogeneity among studies, COVID-19 self-testing/self-sampling exhibits high concordance with professional-use Ag-RDTs. This suggest that self-testing/self-sampling can be offered as part of COVID-19 testing strategies.
Trial registration
PROSPERO: CRD42021250706
Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer’s disease
Authors: Liang Xuhong , Xue Chen , Zheng Darui , Yuan Qianqian , Qi Wenzhang , Ruan Yiming , chen Shanshan , Song Yu , Wu Huimin , Lu Xiang , Xiao Chaoyong , Chen Jiu 
Published: August 2023

Abstract
Objectives
Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer’s disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function.
Methods
A cross-sectional analysis using the spectral dynamic causal model was conducted to examine effective connectivity patterns in the DMN and CEN among the three groups. Subsequently, longitudinal analysis assessed the changes in effective connectivity patterns and cognitive function before and after rTMS in patients with SCD and aMCI, exploring the correlation between them.
Results
Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged.
Conclusions
This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum.
Investigation and modeling on electroformed micro electrolysis pump using regression analysis
Authors: Behagh Amir Masoud , Tehrani Alireza Fadaei 
Published: August 2023

Abstract
The purpose of this study is to investigate using electroforming process for manufacturing an electrolysis micro pump. Also characterization and modelling of prepared micro pump was explored. For this reason, firstly a setup for mandrel shaping using abrasive assisted chemical machining was built. Secondly, another experimental setup for copper electroforming process using copper sulfate bath was made. After manufacturing micro pump's body using electroforming process, it assembled and characterized. For characterization, mean flow rate for discharging a fix volume of liquid, 0.3 milliliters of water, by applying 2 to 10 Volts of electrical voltage in five steps was measured. The mean flow rate measured between 0.09 to 0.56 (mL/min) at different applied electrical voltage. Furthermore, regression model was developed that described the relation between applied voltage and pump's mean flow rate as linear. Confirmation tests were conducted for verification of proposed regression model too.
Clinical study of blood lipid and amylase levels in children with type 1 diabetes complicated with ketoacidosis
Authors: Wang Weixu 
Published: August 2023

Abstract
Background
Diabetic ketoacidosis (DKA) is common in children with type 1 diabetes (T1D) and can further lead to dyslipidaemia and amylase elevation. The purpose of our study was to explore the correlation among DKA, blood lipid levels and amylase levels in children with T1D.
Methods
The clinical data and laboratory indicators of 120 patients with T1D were retrospectively analysed. The patients were divided into two groups: those without DKA (30 patients) and those with DKA (90 patients). Differences between the groups were analysed. ROC curves were used to explore the diagnostic value of blood lipid and amylase levels. The Mantel‒Haenszel test, Spearman correlation and logistic regression analysis were used to explore the correlation among DKA, blood lipid levels and amylase levels.
Results
HbA1c levels (p=0.003), triglyceride levels (p<0.001), total cholesterol levels (p<0.001) and the incidence of abdominal pain (p=0.009) were all higher in patients with DKA than in patients without DKA, and high-density lipoprotein (HDL) levels (p=0.002) were lower. The Mantel‒Haenszel test showed that the risk of triglyceride elevation was higher for DKA patients (OR = 6.118, p < 0.001), and amylase elevation was not found to have a significant impact on this risk (p=0.502). In multivariate logistic regression analyses, the presence of DKA was associated with a higher risk of triglyceride elevation (OR=5.362, p = 0.003).
Conclusions
Abdominal pain, elevated HbA1c, triglyceride, and total cholesterol levels and decreased HDL levels are common in children with T1D and DKA, and the presence of DKA is a risk factor for triglyceride elevation. In the absence of acute pancreatitis, DKA or triglyceride elevation will not increase blood amylase levels.
Construction and Evaluation of a Prognostic Model Based on Metastasis-Associated Genes in Breast Cancer
Authors: Liao Zhixiao , Deng Yueyang 
Published: August 2023

Abstract
Objective: The aim of the study was to investigate the gene expression profile features in distant metastatic breast cancer (BC) patients, identify the metastasis-associated genes correlated with prognosis, and construct a survival rate nomogram.
Methods: Transcriptome data of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database, and divided into metastatic and non-metastatic groups. Differentially expressed genes (DEGs) were analyzed between the two groups, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to explore the potential functions of DEGs. Univariate COX, LASSO regression, and multivariate Cox regression models were applied to screen prognostic-related genes, and a prediction model was established.
Results: A total of 215 DEGs were identified. FAM9C, CRISP2, TFPI2, TUBA3E, IL12Rβ2, BP1 and CSN3 were independent influencing factors for overall survival (OS) rate. Area under the curve (AUC) values outweighed 0.6, and calibration curves did not deviate from the reference line.
Conclusion: The metastasis-related genes prognostic nomogram for BC patients established in this study had favourablepredictive power that could provide a theoretical reference for subsequent studies.
92 Ir brachytherapy combined with external beam radiation and biliary stenting can improve the local control rate of unresectable hilar cholangiocarcinoma
Authors: Yang Wenbo , Yang Hongjuan , Xiao Li , Liu Fei , Sun Yunchuan 
Published: August 2023

Abstract
Objective
This study aimed to evaluate the prognostic efficacy and safety of 192Ir brachytherapy combined with external beam radiation in the treatment of unresectable hilar cholangiocarcinoma.
Methods
In this study, the clinical data of unresectable hilar cholangiocarcinoma patients admitted to our hospital from January 2014 to March 2019 were analyzed retrospectively. The treatment mode was concurrent chemoradiotherapy + biliary stent +/- brachytherapy. Survival was analyzed using the Kaplan–Meier method.
Results
A total of 62 patients were in covered in this study, including 32 who underwent 192Ir brachytherapy combined with external beam radiation and percutaneous hepatobiliary stenting, which were assigned to the Ir-192 group, and 30 who received external beam radiation and percutaneous hepatobiliary stenting, which were assigned to the EBRT group. After the patients of the Ir-192 group and the EBRT group received 3 months of treatment, the complete remission rates (CRs) reached 15.6% and 6.7%, the partial remission rates (PRs) were 78.1% and 63.3%, and the objective remission rates (ORRs) reached 93.7% and 70%, respectively. Moreover, the median progression-free survival (PFS) was obtained as 11.0 months and 8.5 months, respectively. Besides, the 1-year PFS rates reached 37.5% and 6.3%, and the 2-year PFS rates were 16.7% and 0%, respectively (P = 0.032). In addition, the median overall survival (OS) was 14.5 months and 12.2 months, respectively. Furthermore, the 1-year OS rates were 58.8% and 27.9%, and the 2-year OS rates were 51.6% and 14.7%, respectively (P = 0.361). It is noteworthy that TBIL, DBIL, ALT, AST, and CA19-9 in the Ir-192 group were notably lower than those prior to treatment and 3 months after treatment in the EBRT group.
Conclusion
192Ir brachytherapy combined with external beam irradiation and biliary stenting is capable of increasing the local control rate of unresectable hilar cholangiocarcinoma, with reliable prognostic efficacy and tolerable adverse reactions, such that it serves as a feasible and safe treatment method for clinical practice.
Successful Repair of Recurrent Ventricular Septal Perforation after Myocardial Infarction using Double Patch Technique via Right Ventriculotomy: A Case Report
Authors: Ashsholih Khoirur Rijal , Takasaki Taiichi , Tomota Mayu , Tokumoto Taika , Go Seimei , Emura Shogo , Ozawa Masamichi , Takahashi Shinya 
Published: August 2023

Abstract

Background
Post-myocardial infarction (MI) ventricular septal perforation (VSP) is a rare but life-threatening complication. Surgical repair is challenging and carries significant risks, particularly in the context of recurrent VSPs. This case study presents a patient with recurrent VSP after initial surgical repair following myocardial infarction.
Case Presentation
A 65-year-old male with recurrent VSP was referred to our hospital. He had undergone emergency VSP closure surgery 2 months earlier, utilizing the bovine double patch technique via left ventriculostomy. The initial VSP was located in the apical part of the interventricular septum, while the recurrent VSP appeared in the upper middle portion of the interventricular septum (Fig. 1). As the previous patch remained intact, the second surgery employed the bovine double patch technique via right ventriculostomy. The patient's condition remained stable without the development of heart failure symptoms.
Conclusion
Repairing recurrent VSPs remains a challenge, necessitating the mastery of appropriate approaches to achieve optimal outcomes. Further research and guidelines are required to refine management strategies for recurrent VSPs.
When is health inequality acceptable? Appraisals of inevitability, complexity and causal explanations
Authors: Bridger Emma K , Tufte-Hewett Angela , Comerford David , Nettle Daniel 
Published: August 2023

Abstract
Background: Health inequalities are typically presented with respect to separate groupings or bases of categorization, such as income-related health inequality or life expectancy by education. We sought to characterize the cognitive consequences of presenting health inequality by bases of categorization.
Methods:Across two studies (N = 1,321), UK and US participants made a number of judgments about life expectancy differences (including how acceptable they are and whether they should be addressed) attributed to distinct bases of categorization: income, education, social class, neighbourhood, lifestyle choices and genetics.
Results:Health inequality was perceived as least acceptable when attributed to the four socioeconomic bases, and most acceptable for lifestyle choices and genetics. Six appraisal dimensions – complexity, malleability, inevitability, extent driven by biological, psychological and sociocultural causes - varied with basis of categorization and predicted views on health inequality. These dimensions could explain the majority (47-57%) of the drop in acceptability for health inequality attributed to neighbourhood, social class and education differences relative to a condition with no categorization.
Conclusions:These findings illustrate for the first time some of the causal explanations and affiliated inferences that underpin views on health inequality, and the corresponding consequences for communicating about health and health inequalities.
A Bi-Directional Engine for Transformation of Big Data Between NoSQL and SQL Data
Authors: Samanta Ashis Kumar , Chaki Nabendu 
Published: August 2023

Abstract
Big Data emerges as a solution with the continual and massive growth of different types of data streams at high speed. The customized storage and retrieval of data has indeed become a challenge. Over the last few decades, users of all levels had been more conversant with the relational model and SQL (Structured Query Language). However, several limitations of the relational model has been observed and discussed in the existing literature. As of day, a significant number of the applications are cloud-based or web-based. These handle either structured data (SD), semi-structured data (SSD), or completely unstructured data (USD). The volume of the transactions might even be at the petabytes level. NoSQL have drawn considerable attention for successfully handling massive volumes of heterogeneous data efficiently and irrespective of the type of data. It often requires the conversion of unstructured data into a structured format for possible data analysis, etc. This aims to transform the unstructured data stored in JSON format in the MongoDB data model to SQL structured table data format and vice-versa. The primary rigor of this research work is towards designing an interface facility to change the unstructured data into a structured format for its proper re-usability and simplicity. The focus is to design and develop a bi-directional transformation engine that can simplify the complex data in JSON structure to convert the simplified table structure keeping the normalization features and also to transform the data from normalized SQL format to single collection data of JSON format. Therefore, the proposed bi-directional transformation engine will be an interface between the SQL and NoSQL data model. The algorithms are evaluated using appropriate data. The broader vision of this work is to remove the structural differences between unstructured and structured data in respect of its reuse.
Accurate and Fast model for single Rotor Double Stator Interior Permanent Magnet Brushless Synchronous Machine with Spoke-Type structure at no-Load
Authors: Shirzad Ehsan 
Published: August 2023

Abstract
In this paper a 2-dimensional model by solving partial differential equations for single Rotor Double Stator Interior Permanent Magnet Brushless Synchronous Machine with Spoke-Type structure (SRDSIPMBSMWSTS) is formulated to predict flux density in air-gaps at only no load. After extracting relations are governing in each domain (magnetic potential vector and magnetic field intensity), boundary conditions between each two domain that are in adjacent to each other are applied to determine unknown coefficients. Output results are compared to finite element analysis (FEA) yield from Maxwell software to validate this fast and accurate model.
Compressed Deep Neural Networks for Segmentation of Cutaneous Malignant Wounds in Images
Authors: Costa Rafael Cardoso Ribeiro da , Silva Bruna Cristina Andrade Lira da , de Souza Rafael Roque , Lins Robson Cavalcanti , Rodrigues Iago Richard 
Published: August 2023

Abstract

Automatic segmentation of the areas of cutaneous malignant wounds in images is an integral part of the diagnosis and care process. It is essential to measure the wound area and provide quantitative data in treatment. Several deep-learning neural network models exist for this purpose. However, the problem with many of these models is that their architecture is cumbersome and has a high computational cost. Therefore, we propose to evaluate the techniques of four deep-learning neural networks followed by applying a pruning technique to compact these models and obtain a qualitative comparison of the results. One of the models (U-Net) is commonly used in medical image segmentation; the model (DeepLabV3) uses base convolutions used in MobileNetV2 networks, which provides more compact models. The model (SegNet) uses a decoder that uses clustering indices computed in the maximum clustering step of the corresponding encoder to perform non-linear upsampling, this architecture significantly reduces the number of trainable parameters, and finally, the model (FCN-VGG19) uses 19 depth layers, its downsampling layer is mainly used to improve the anti-distortion capability of the network for the image, keeping the main features of the sample and reducing the number of parameters. Given the models, we apply the pruning method from TensorFlow Model Optimization Toolkit, using the polynomial decay technique and experimenting with various sparsity settings. With this evaluation of the segmentation models applied to the pruning technique, we concluded that the neural networks that obtained a better result in computational efficiency and accuracy were FCN and U-Net.
Network Indicators of Public Bus Transportation in Klang Valley and their correlations
Authors: Rashid Nur Umaisara , Chan Kar Tim , Halim Umair Abdul 
Published: August 2023

Abstract
Complex network-based analysis on the real-world system has frequently assists researchers in providing a crucial and extensive understanding on a variety of interconnected useful data especially on public transportation services. In this paper, we construct a public bus transportation network of eight zones in Klang Valley before evaluating their characteristics based on some network measurements such as average degree and clustering coefficient followed by calculation on five network indicators namely accessibility, centralization, robustness, directness, and service connectivity. These network indicators are helpful in providing extensive analysis on the network performance. Other than that, we also analyse the correlation between the network indicators. It is found that the different network indicator is beneficial in describing the network performance based on different network components and characteristics such as how betweenness centrality and closeness centrality is being applied as part of the centralization and accessibility measurement respectively.
Shuffle-RDSNet: A Method for Side-Scan Sonar Image Classification with Residual Dual-Path Shrinkage Network.
Authors: Ge Qiang , Liu Huaizhou , Ma Yuxiang , Han Daojun , Zuo Xianyu , Dang Lanyue 
Published: August 2023

Abstract
The authors have requested that this preprint be removed from Research Square.