Predictive Value of AIP and AGR for Non-alcoholic Fatty Liver Disease and Significant Liver Fibrosis by Zhang Simin, Zhou Changyu, Shi Xianquan, Huang Lizhen

“…SPSS 27.0 and R 4.4.0 were used to analyze the data, single-factor Logistic regression analysis was applied to screen the influencing factors of NAFLD, stepwise regression was applied to screen the variables, and multi-factor Logistic regression was performed to construct the prediction model and draw the column graph. …”
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Determinants of choosing a foreign brand in emerging economy: lessons and implication for the local entrepreneurs by Md. Abdul Momen, Seyama Sultana, Farhana Ferdousi, Shamsul Huq Bin Shahriar

“…They are drawn randomly. Confirmatory factor analysis, regression analysis and a path model of structural equation model using AMOS graphics software are used in this study to analyze the data. …”
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Construction and Evaluation of Intimate Partner Homicide Prediction Model by LÜ Wei-ping, LIAO Xin-biao, REN Li-ju, KONG Xiao-ping, CHEN Yan-chang, CHANG Ya-fei, LUO Bin

“…A total of 126 court judgments from outside Guangdong Province from January 1, 2011, to December 31, 2020, were randomly collected for external validation.ResultsThrough multi-factor Logistic regression analysis, 7 variables were ultimately selected for inclusion in the model. …”
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Energy performance of an agricultural articulated tractor: Manual and automatic modes by Gabriel G. Zimmermann, Samir P. Jasper, Mariane C. da Costa, Gabriel A. de Oliveira, Daniel Savi

“…The variance of the data was analyzed using Tukey’s test for the first factor, and regression analysis for the second factor and interactions. …”
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Identification of ferroptosis-related gene signatures in temporal lobe epilepsy with hippocampal sclerosis by Fan Gao, Jinzi Li

“…Subsequently, ferroptosis-related differentially expressed genes (FR-DEGs) in TLE-HS were further analyzed. We used weighed gene co-expression network analysis (WGCNA) algorithm, single-factor logistic regression analysis, and LASSO algorithm to screen characteristic FR-DEGs. …”
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Association of restless legs syndrome with malnutrition,inflammation and sleep quality in hemodialysis patients by HUANG Hua-xing, SHEN Liang-lan, ZHANG Fen, WANG Chen, FANG Xing-xing, CHEN Dong-mei

“…Malnutrition-inflammation( MIS) and Pittsburgh Sleep Quality Index( PSQI) were evaluated. Single factor Logistic regression analysis was used to analyze the related factors. …”
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Novel miRNA markers and their mechanism of esophageal squamous cell carcinoma (ESCC) based on TCGA by Ping Yuan, Xiaoyan Gao, Mingjun Xu, Liangyu Qiu, Zijun Xiong, Jun Shen, Huanhuan Xing, Ruofan Yang, Liang Zhao, Xi Liu, Jiaowei Gu, Wenting Liu

“…For the other novel 10 DEMs, single-factor Cox regression analysis show that only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients. …”
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High expression of SOX10 is correlated with poor prognosis and immune infiltrates in skin cutaneous melanoma by Xu Sun, Yi-ming Cheng, Meng-wei Sun, Xu-dong Zhang, Xiao-yu Yu, Hai-bo Wang, Yi-fei Wang, Ning Li

“…The forest plot results showed that only OCA2 and TRAT1 had statistical significance (P < 0.05) by multi-factor COX regression analysis. SOX10, OCA2, TRAT1, pathologic stage, age and breslow depth were included in the nomogram prognostic model. …”
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Comparison of differences in hematogenous metastasis among cervical cancer patients by CT-guided three-tube intracavitary brachytherapy and hybrid intracavitary and interstitial br... by Bo Yang, Yinping Hu, Shuhui Yu, Chunfang Zhao, Zhongyan Dou, Lan Li, Kangming Li, Meiping Jiang, Lan Zhang, Xingrao Wu

“…By propensity score matching (PSM) between the two groups according to 1:1 matching, single factor logistic regression analysis revealed that there was no significant difference in the incidence of hematogenous metastasis between the two groups (OR = 0.382, 95% CI = 0.071–2.040; P = 0.260). …”
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Analysis of the inflammatory storm response and heparin binding protein levels for the diagnosis and prognosis of sepsis-associated encephalopathy by Dian Yu, Jun Liu, Xiaoyun Song, Yongfeng Ao, Xiaomin Li, Yi Han

“…In addition, the GCS score and serum cholinesterase levels in the SAE group were lower than in the non-SAE group (P < 0.05). Subsequently, Multi-factor logistic regression analysis revealed that ultra-high IL-6 (> 5000 pg/ml), IL-10 (> 1000 pg/ml), and HBP (> 300 ng/ml) levels and elevated SOFA and APACHE-II scores were risk cytokines for the development of SAE (P < 0.05). 28-day mortality was significantly higher in patients in the SAE group and in the IL-6 > 5000 pg/ml group compared to patients in the USAE and IL-6 < 5000 pg/ml groups(P < 0.001).The four screened predictors of HBP > 300 ng/ml, IL-6 > 5000 pg/ml, decreased GCS score, and decreased APACHEII score were combined into a new predictive data model (risk score).In the SAE group, patients with high risk scores had a higher 28-day mortality rate compared with the low risk score group (P < 0.001). …”
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