Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis by Yiyuan Shen, Xu Zhang, Jinlong Zheng, Simin Wang, Jie Ding, Shiyun Sun, Qianming Bai, Caixia Fu, Junlong Wang, Jing Gong, Chao You, Yajia Gu

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Factors that affect the development of acute hemorrhagic rectal ulcer syndrome and rebleeding by Natsumi Uehara, Kazuaki Inoue, Yuichiro Kuroki, Naoki Miyao, Kenta Iwahashi, Reika Suzuki, Toshiyuki Endo, Kunio Asonuma, Erika Yoshida, Naoko Koshibu, Akihiro Tabuchi, Misako Tohata, Shotaro Hanamura, Kuniyo Gomi, Yorimasa Yamamoto, Masatsugu Nagahama

“…The relationship with episodes of rebleeding was analyzed by multivariate logistic regression analysis. …”
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The Effect of Internal Control Factors on the Accountability of the Auditor at the Inspectirate of Jombang District by Ludfa Febriana, Siti Maria Wardayati, Whedy Prasetyo

“…This study aims at testing and analyzing the influence of internal control factors to auditors who work in the inspectorate of Jombang District. …”
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Factors that contribute to loss to follow-up in the medium term after initiation of anti-vascular endothelial growth factor therapy for neovascular age-related macular degeneration... by Takaaki Sugisawa, Fumi Gomi, Yuri Harada, Hiroko Imaizumi, Shuichiro Aoki, Akiko Miki, Maya Kishi, Tomofusa Yamauchi, Daisuke Nagasato, Yoko Ozawa, Masatoshi Haruta, Nobuhiro Kato, Hisashi Matsubara, Tsutomu Yasukawa, Aki Kato, Hiroto Terasaki, Takao Hirano, Yasuhiro Iesato, Hiroki Tsujinaka, Tomoya Murakami, Yoshinori Mitamura, Makiko Wakuta, Kazuhiro Kimura, Masahiko Shimura, J-CREST (Japan Clinical Retina Study) Group

“…Stepwise regression analysis identified factors that were significantly associated with LTFU at a very early stage to be greater central retinal thickness at baseline and a prior treatment history, those associated with early LTFU to be worse baseline best-corrected visual acuity (BCVA), anti-VEGF treatment combined with photodynamic therapy, and a follow-up period that overlapped with the COVID-19 pandemic, and that associated with medium-term LTFU to be worse BCVA at 3 months. …”
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Factors Influencing The Disclosure Of Islamic Social Reporting In Islamic Commercial Banks by Euis Sahara, Ibram Pinondang Dalimunthe

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Determinant Factors Of Electric Bicycle Purchase Decisions: Evidence From Indonesia by Sulismawati Sulismawati, Ida Nuryana

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Risk factors for multidrug resistance in pulmonary tuberculosis patients with diabetes mellitus by Lianpeng Wu, Lianpeng Wu, Na Chen, Na Chen, Dandan Xia, Dandan Xia, Xiangao Jiang, Xiangao Jiang

“…Multivariate logistic regression analysis was used to identify independent risk factors for MDR, and receiver operating characteristic (ROC) curves were constructed to evaluate the predictive value of these factors.ResultsA total of 318 patients were analyzed, with 253 in the non-MDR group and 65 in the MDR group. …”
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Ecological Factors Determining Abundance of Parasitic Mites on Aedes spp. Larvae by Nurhadi Eko Firmansyah, Susi Soviana, Bambang Heru Budianto

“…The influence of ecological factors was analyzed using regression and correlation analysis. …”
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Cognitive Disorders Awareness and Associated Risk Factors in Xizang Autonomous Region by HAO Yu, WANG Junshan, ZHUO Ma, SUOLANG Quzhen, JI Shiyong, HU Yaxiong, DING Zhijie, CIDAN Zhuoga, YUAN Jing, ZHAO Yuhua

“…Demographic information and data on awareness of cognitive disorders were collected, and an ordered Logistic regression model was used to analyze influencing factors in the overall population and stratified by occupation.ResultsA total of 327 questionnaires were collected, with 14 excluded (13 for not meeting residency requirements and 1 for self-reported diagnosis of cognitive impairment), leaving 313 valid questionnaires. …”
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Clinical Factors Contributing to Age-Related Gait Dysfunction in Older Adults by Yoshihito Sakai MD, PhD, Tsuyoshi Watanabe MD, PhD, Norimitsu Wakao MD, PhD, Hiroki Matsui MD, PhD, Naoaki Osada MD, Yui Adachi MD, Yosuke Takeichi MD, Akira Katsumi MD, PhD, Ken Watanabe PhD

“…Results Among the 2083 participants, 1323 and 760 were included in the independent and assisted groups, respectively. The logistic regression analysis identified five significant factors ( P < 0.01): age, body mass index, red blood cell distribution width, skeletal muscle mass index, and sagittal vertical axis. …”
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Predicting the prognosis of patients with sudden sensorineural hearing loss by analyzing the audiometric curve of the unaffected ear by Xuan Sun, Yahan Zhao, Yi Li

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The Factors Influence the Biosecurity Management of Swine Farm in Mekong Delta, Vietnam by Nguyen Thi Anh Thu, Budi Guntoro

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Risk Factors for Gout in Taiwan Biobank: A Machine Learning Approach by Liu YR, Nfor ON, Zhong JH, Lin CY, Liaw YP

“…Five machine learning models were used: Bayesian Network (BN), Random Forest (RF), Gradient Boosting (GB), Logistic Regression (LR), and Neural Network (NN). The predictive performance was evaluated using a split dataset (80% training set and 20% test set).Results: Variable importance analysis was performed to identify key variables, with uric acid and gender emerging as the most influential risk factors. …”
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MAIN FACTORS AFFECTING CLASS MANAGEMENT ABILITY IN ISLAMIC PRIMARY SCHOOL by Nazilatul MIFROH, Siti FATONAH

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Exploring the optimal method for quantifying the contribution of driving factors of urban floods by Xi Huang, Linhan Yang, GuiCheng Yang, Jiufeng Li, Luo Liu, Yilun Liu, Xianzhe Tang

“…Effective UF management requires two key elements: (1) assessing susceptibility to identify flood-prone hotspots and (2) analyzing factor contributions to pinpoint primary drivers. …”
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Influencing factors of intraoperative blood transfusion and prognosis in lung transplant patients by YANG Huaying, QIANG Xinchen, SUN Lingling, SHAO Junliang

“…[Objective] To explore the risk factors of allogeneic blood transfusion during lung transplant surgery and prognostic effects of transfusion by analyzing the basic data, surgical details, laboratory tests results, and intraoperative blood transfusion details during the perioperative period of lung transplant, so as to guide clinical blood use. …”
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A machine learning framework for predicting healthcare utilization and risk factors by Yead Rahman, Prerna Dua

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Network structure and influencing factors of the quality of inbound tourism flows circulation by MA Lijun, LIANG Xiaoyao

“…[Objective] The objective of this study was to reveal the structural characteristics of the network of inbound tourism flows circulation quality and the role of various provinces within this network, and to analyze the influencing factors of the quality of inbound tourism flows. …”
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Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors by Xueliang Deng, Liang Zhao, Changchun Xiao, Rui Dai, Qianqian Xu, Yeqing Yao, Caimeng Liang, Lei Yao, Dongyan He

“…The relationship between heatstroke and meteorological conditions was discussed by statistical methods, such as correlation analysis, cluster analysis and linear regression analysis. …”
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Investigation on influencing factors and prognosis of complicated infection in patients with maintenance hemodialysis by YU Qian, LI Xiao-ying, WU Xin, MIN Ya-li, CHEN Song, ZHANG Chun, PAN Zhi-yu, HUANG Yun, QU Ling-ling, LUO An-dian

“…Objective To know about influencing factors of complicated infection in patients with maintenance hemodialysis(MHD),and to understand characteristics,prognosis and influencing factors of complicated infection in patients with MHD.Methods Clinical data of MHD patients hospitalized in Guiyang First People’s Hospital from January 2012 to December 2017 were collected,and divided into the infection group and the non-infection group based on presence of complicated infection.General information and laboratory test results of these patients were collected,so as to analyze infectious factors in them and summarize types of pathogens and infections in them.Based on prognosis of these patients with MHD,they were divided into the good prognosis group and the poor prognosis group,so as to analyze influencing factors of their prognosis.Results Through comparison of the data between the infection group and the non-infection group,it was found that the risk for complicated infection increased significantly for those patients with a primary disease of diabetic nephropathy.Kt/V<1.2,and use of a ferric preparation,hemoglobin<110 g/L and albumin<40 g/L in recent 3 months(P<0.05).In the MHD patients hospitalized due to infection,the most common infectious bacteria included Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa and,staphylococcus aureus,and infection of the respiratory system is the most common.Multi-factor regression analysis revealed that the factors influencing prognosis of complicated infection in the patients with MHD included age>65,bed time>10 days,requirement for blood transfusion,multiple drug-resistant bacterial infection,and malnutrition,with statistically significant difference(P<0.05).Conclusions Primary diabetic nephropathy,Kt/V<1.2,and use of a ferric preparation,hemoglobin<110 g/L and albumin<40 g/L in recent 3 months are the risk factors of complicated infection in MHD patients;infection of the respiratory tract is the most common;and,age>65,bed time>10 days,requirement for blood transfusion,multiple drug-resistant bacterial infection and malnutrition are the hazardous factors of prognosis of complicated infection in patients with MHD.…”
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